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The Different Tiers of Social Lives in Policies

Permanent Link: http://ufdc.ufl.edu/UFE0021349/00001

Material Information

Title: The Different Tiers of Social Lives in Policies Policy Beliefs and Different Aspects of Social Capital
Physical Description: 1 online resource (120 p.)
Language: english
Creator: Yun, Hyun Jung
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: activism, attitude, capital, government, morality, network, policy, redistributive, social, trust
Political Science -- Dissertations, Academic -- UF
Genre: Political Science thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: This study showed how specific policy beliefs are influenced by individuals' various levels of general social trust and multi-dimensional social networks such as intensiveness and extensiveness. By analyzing the 2004 General Social Survey, the study found that general social trust and network intensiveness and extensiveness conditionally influence policy beliefs based on various policy types. General social trust reinforces positive attitudes toward redistributive policies for the poor and morality policies on gay rights. Network intensiveness and extensiveness influence supportive tendencies for government regulations on morality policies, but do not do so for other types of policies. In addition, there are no statistical differences between single and multiple network intensiveness and extensiveness on policy beliefs as long as an individual is involved in any type of social network. Although there was a mixture of evidence, the study proved that various elements of social capital influence different policy attitudes.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Hyun Jung Yun.
Thesis: Thesis (Ph.D.)--University of Florida, 2007.
Local: Adviser: Hedge, David M.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021349:00001

Permanent Link: http://ufdc.ufl.edu/UFE0021349/00001

Material Information

Title: The Different Tiers of Social Lives in Policies Policy Beliefs and Different Aspects of Social Capital
Physical Description: 1 online resource (120 p.)
Language: english
Creator: Yun, Hyun Jung
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: activism, attitude, capital, government, morality, network, policy, redistributive, social, trust
Political Science -- Dissertations, Academic -- UF
Genre: Political Science thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: This study showed how specific policy beliefs are influenced by individuals' various levels of general social trust and multi-dimensional social networks such as intensiveness and extensiveness. By analyzing the 2004 General Social Survey, the study found that general social trust and network intensiveness and extensiveness conditionally influence policy beliefs based on various policy types. General social trust reinforces positive attitudes toward redistributive policies for the poor and morality policies on gay rights. Network intensiveness and extensiveness influence supportive tendencies for government regulations on morality policies, but do not do so for other types of policies. In addition, there are no statistical differences between single and multiple network intensiveness and extensiveness on policy beliefs as long as an individual is involved in any type of social network. Although there was a mixture of evidence, the study proved that various elements of social capital influence different policy attitudes.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Hyun Jung Yun.
Thesis: Thesis (Ph.D.)--University of Florida, 2007.
Local: Adviser: Hedge, David M.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021349:00001


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83c3a1df08c9b59d11bd8b7f8dda09a7
38b33046649e670bdcfd0051de6c9f5af146c6f7







THE DIFFERENT TIERS OF SOCIAL LIVES INT POLICIES:
POLICY BELIEFS AND DIFFERENT ASPECTS OF SOCIAL CAPITAL



















By

HYUN JUNG YUN


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2007

































O 2007 Hyun Jung Yun





























To all who nurtured my intellectual curiosity, academic interests, and sense of scholarship
throughout my lifetime, making this milestone possible









ACKNOWLEDGMENTS

Completing two doctoral programs has been a fabulous life j ourney for me. I have gone

through exciting, enjoyable, surprising, blissful, but sometimes stressful, depressing, and

heartbreaking moments. I believe that I am very lucky since I have been surrounded by amazing

people for the last seven years of this j ourney. I would like to express my gratitude to all of the

people who gave me endless support, encouragement, and love from the beginning of my

graduate program through to the point of completion of my two dissertations, one in Political

Science and the other in Journalism and Mass Communications.

First of all, I want to thank my life time advisers and chairs, Dr. David Hedge and Dr.

Lynda Lee Kaid. Dr. Hedge has guided me and corrected me whenever I need any direction to

go and added his sweetness to my journey with incredible encouragement and compliments. Dr.

Kaid has always stimulated me with research ideas through a weekly research meeting

throughout my doctoral program and taught me invaluable lesson of how the research is

supposed to be processed. I also deeply appreciate that Dr. Michael Martinez, Dr. Renee

Johnson, and Dr. Mary Ann Ferguson who have been always there for me and given me precious

advice at the right moments. Dr. Spiro Kiousis and Dr Lynn Leverty's endless support for my

academic proj ects has accelerated my academic progress. My interdisciplinary research was

able to be completed due to all of my committee members' special academic expertise and

emotional support and dedication.

I would also likely to express my special thanks to my mentors, Dr. Goran Hyden, Dr.

Seung Ik Yoo, Dr. Mi Kyung Jin, Dr. Chul Whan Kim, Dr. Sun Joo Yoon, Dr. Sung Hwa Yoon,

Dr. Jun Han Kim, Dr. Soo Bok Lee, and Dr. Kyung Ho Lee since my undergraduate program in

Korea. Their priceless lessons and guidance fueled my academic eagerness in the early years of

my university education. Moreover, Korean faculty members at the University of Florida, Dr.










Won-Ho Park, Dr. Chang-Hoan Cho, Dr. YooJin Choi, and Dr. Hyojin Kim, have always offered

to lend their hands to me. I also would like to give my special thanks to Dr. Joo Myung Song,

Dr. Dou Kyung Ahn, and Dr. Yoo Hyang Kim who have shared their hearts even giving me

'luck money' for my job interviews. In addition, Dr. Richard Scher and Dr. Badredine Arfi's

compliments and support on my teaching experience have built me up with positive confidence,

thus make me be able to overcome all unnecessary self-consciousness as an international student

My great colleagues and best friends, David Conklin, Dr. Monica Postelnicu, Dr. Jun Soo

Lim, Dr. Seung Eun Lee, Dr. Eyun Jung Ki, Soo Yeon Km, Dr. Nadia Ramutar, Sarah Urriste,

Dae Hyun Kim, Min Gil Kim, and Shari Kwon, deserve to have my whole heart. I was able to

stay human due to their sense of humor, faith, love, and trust. In addition, I would like to thank

to Mrs. Jody Hedge, Mrs. Debbie Wallen, and Mrs. Sue Lawless-Yanchisin who have been my

personal life advisers beyond academia by giving me important information and sharing our

stories. They always shared their great smiles and open-minds with me. They are the core people

for the programs of Journalism & Mass Communications and Political science. They made all

this process easier, smoother, and enjoyable. My special thanks also goes to Gordon Tapper,

who has a wonderful heart and cultural insights. Sharing my cultural background, he has

observed my pattern of English speaking to guide me in how a foreign speaker at the advanced

level can reach to the level of native English speaker, even dedicating his free Friday for me.

Lastly, I would like to express my special thanks to my parents. My daddy, who is very

protective and would do anything he can do for me, thus it was not easy for him in the beginning

to let me go away even for an academic program, has been an important reason for me to be a

good person. My mom has dedicated every single breath to me and has been the best supporter

for my choice for academic life. I was able to grow up in a happy environment due to my









wonderful parents. My final appreciation goes to my soul mate who has shared every single

moment with me for the last eleven years.

I always felt their affection and belief in me. It has given me my endless energy for my

academic progress. Due to them, I have never thought about 'giving up' in any single step of my

academic progress. I know how lucky I am having such wonderful people around me. I deeply

appreciate all of them and promise that I will try to be one who can make them happy.












TABLE OF CONTENTS


page

ACKNOWLEDGMENTS .............. ...............4.....


LIST OF TABLES ............ ...... ._._ ...............9....


AB S TRAC T ............._. .......... ..............._ 1 1..


CHAPTER


1 INTRODUCTION ................. ...............12.......... ......


2 LITERATURE REVIEW ................. ...............20................


Dimensions of Social Capital .............. ...............20....
Definitions of social capital ................... ...............20.......... ....
Different Dimensions of Social Capital ................. ... ....... ... ........2
Social networks: theoretical understandings & empirical evidence.........................22
General social trust: Theoretical understandings & empirical evidence .................. 28
Functions of Social Capital ............... .. .. ........... ...............33......
The Positive Consequences of Social Capital .............. ...............33....
The Negative Consequences of Social Capital ................. ...............37...............

3 HYPOTHESES AND THE PERSPECTIVES .............. ...............42....


On Redistributive Policies .............. ...............43....
On Government Activism............... ...............45
On Morality Policies............... ...............46

4 METHOD .............. ...............50....


D ata................. ....... ............5

Perspectives of Categorization .............. ............... .......51
Measuring Dimensions of Social Capital ................ ...............51........... ...
Measuring Public Policy Typology ................. ......... ...............57. ....
Conditional Factors of Demographics............... .............6
Analyses............... ...............63

5 RE SULT S .............. ...............65....


Demographics and Social Capital............... ...............65
Party Identification .............. ...............65....
G ender .............. ...............66....

A ge .............. ...............66....
Education............... ...............6
Ethnicity .............. ...............67....













R eligiosity............... ..............6
Incom e .............. ...............68....

R egion.................. ..... ...........6
Dimension of Social Capital ............... .. .......... .. .... ........ ............6
Correlations between Different Dimensions of Social Capital ................. ............ .........70
Social Capital and Policy Attitudes .............. ...............71....
On Redistributive policy............... ...............71.
On Government Actions ............. ...... ._ ...............73....

On M orality Policy .............. ... ......_ ...............74....
The Regional Context and Social Capital ............. .....___ ...............76.


6 DI SCUS SSION ............. ...... ._ ...............92....


Demographics............... ..............9
Social Networks............... ...............94
General Social Trust ........._... ...... ._._ ...............95...

Divergence of Policy Attitudes .............. ...............96....


APPENDIX ........._... ...... ._._ ...............101...


A. SOCIAL CAPITAL ........._... ...... ._._ ...............101...


Social Network Intensiveness............... ..... ... .........0

Social Network Extensiveness (Sum of memberships) ................ .......... ................1 01
General Social Trust (Mean of three trust scale) ................ ...............104.............


B POLICY AT TITUDE S ................. ................. 105........ ....


Re distributive Policy .............. ...............105....
Government Activism............... ...............10
M orality policy .............. ...............106....
On Abortion............... ............... 10
On Gay Rights ................ ...............107................


LIST OF REFERENCES ................. ...............109................


BIOGRAPHICAL SKETCH ................. ...............119......... ......











LIST OF TABLES

Table page

3-1 Hypotheses Matrix .........._. .. ...._.. ...............49....

5-1 Party Identification and Social Capital .............. ...............79....

5-2 Party Identification and Networks Intensiveness and Extensiveness .............. ................79

5-3 Gender and Social Capital .............. ...............80....

5-4 Gender and Network Intensiveness and Extensiveness ......... ................ ...............80

5-5 Age and Social Capital............... ...............80

5-6 Age and Network Intensiveness and Extensiveness .............. ...............81....

5-7 Education and Social Capital ................ ...............81........... ...

5-8 Education and Network Intensiveness and Extensiveness............... .............8

5-9 Ethnicity and Social Capital............... ...............82

5-10 Ethnicity and Network Intensiveness and Extensiveness ................. ................. ...._82

5-11 Religiosity and Social Capital............... ...............82

5-12 Religiosity and Network Intensiveness and Extensiveness .............. .....................8

5-13 Income and Social Capital .............. ...............83....

5-14 Income and Network Intensiveness and Extensiveness............... .............8

5-15 Region and Social Capital ................. ...............84........... ...

5-16 Region and Network Intensiveness and Extensiveness .............. ...............84....

5-17 Descriptive Social Capital............... ...............85

5-18 Correlations of Social Capital ................. ...............85........... ...

5-19 Correlations of Network Intensiveness, Extensiveness, and General Social Trust ...........86

5-20 Social Capital and Redistributive Policy Attitudes............... ...............8

5-21 Social Capital and Government Activism Attitudes ................. ................ ......... .87

5-22 Social Capital and Attitudes toward Abortion ................. ...............88........... ..











5-23 Social Capital and Attitudes toward Gay Rights .............. ...............89....

5-24 Regions with High Social Capital ............ ...... .._ ...............90...

5-25 Regions with Low Social Capital .............. ...............91....

A-1 Factor Analysis on Social Network Intensiveness ........._..._. ....._... ......._..._.......101

A-2 Factor Analysis on Social Network Extensiveness ................. ................ ......... .103

A-3 Factor Analysis on General Social Trust ................ ...............104........... ..

B-1 Factor Analysis on Redistributive Policies ................. ...............105..............

B-2 Factor Analysi s on Government Activi sm ......................._ ....__ .........10

B-3 Factor Analysis on Abortion ................. ...............107........... ...

B-4 Factor analysis on gay rights............... ...............108









Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy

THE DIFFERENT TIERS OF SOCIAL LIVES INT POLICIES:
POLICY BELIEFS AND DIFFERENT ASPECTS OF SOCIAL CAPITAL


By

Hyun Jung Yun

August 2007

Chair: David Hedge
Major: Political Science

This study showed how specific policy beliefs are influenced by individuals' various

levels of general social trust and multi-dimensional social networks such as intensiveness and

extensiveness. By analyzing the 2004 General Social Survey, the study found that general social

trust and network intensiveness and extensiveness conditionally influence policy beliefs based on

various policy types. General social trust reinforces positive attitudes toward redistributive

policies for the poor and morality policies on gay rights. Network intensiveness and

extensiveness influence supportive tendencies for government regulations on morality policies,

but do not do so for other types of policies. In addition, there are no statistical differences

between single and multiple network intensiveness and extensiveness on policy beliefs as long as

an individual is involved in any type of social network. Although there was a mixture of

evidence, the study proved that various elements of social capital influence different policy

attitudes.









CHAPTER 1
INTTRODUCTION

There is renewed interest in political science regarding the influence of individuals'

social lives on politics. For instance, prominent scholars in the study of social capital, such as

Robert Putnam and Margaret Levi, have successfully incorporated a discussion on the effects of

social lives within the political sphere. In his depiction of the lonely American isolated from

society due to thinning social connections, Putnam (2000) pulled individuals' social lives into the

academic arena by examining the impact of social capital, or social networks, and the

corresponding norms of trust and reciprocity on the quality of community and political life.

Similarly, Valerie Braithwaite and Margaret Levi (1998), Karen Cook (2001), and others

developed the concepts of communal trust and norms as explanations for social cooperation and

efficient government operation. Pamela Conover and Stanley Feldman (1984), and David

Boninger, Jon Krosnick, and Matthew Berent (1995) also contributed by uncovering the

importance of social groups to an individual's political beliefs.

These scholars used different approaches to introduce the various political implications of

individual's social lives. Putnam (2000) argued that social networks, trust, and group norms

allow the American society to accomplish collective actions and establish efficient information

flow, thus enabling society to overcome selfish social problems. Putnam's long-term study

comparing similar political regimes demonstrated that good governments were established by a

strong tradition of social networks and a higher level of trust among citizens, rather than by the

quality of the government system, party politics, ideology, social stability, political harmony, or

population movements (Putnam, 1993).

Karen Cook, Russell Hardin, Margaret Levi, and others have specifically explored the

concept of trust and emphasize its importance in a wide variety of social contexts across different









disciplines including philosophy, political science, sociology, history, economics, and

psychology. They defined trust as an alternative, informal means of sustaining social

cooperation and establishing a better society. Combining normative and empirical studies

supported their original hypotheses on the normative role of trust in a society (Russell Sage

Foundation). Henri Tajfel and John Turner's (1979) original works on social group attachments

and scholars' recent applications of social ties in macro-level studies of society and politics

suggested that individuals' psychological attachments to social groups affected their political

attitudes toward candidates, forms of government, and behaviors such as voting.

However, there are some critical issues that these scholars have overlooked. First,

scholarly works have not yet clarified definitions, ranges, or meanings of social capital. No

consensus or agreement exists on the different aspects of social capital despite the fact that

theoretical and empirical agreement is necessary to further applications of social capital studies.

Many scholars have either narrowed their focus to specific types of social capital or broadened

their understanding of social capital void of concrete definitions (Cook, 2001, p.23). Therefore,

no concise meaning or consistent measurement of social capital exists in the field.

Secondly, previous studies too often failed to look at the multiple dimensions of social

capital. Social capital studies are in the preliminary stages of identifying how various elements

of social capital differ from and relate to one another. The maj ority of scholarly works have not

differentiated specific trust from general trust, types of social networks from network

extensiveness, reciprocity from trust, and connectedness at the micro-level of the individuals

from identity at the macro-level of groups, regions, or states.

For instance, mainstream scholars in the study of trust, such as Cook, Hardin, and Levi,

argued the importance of only a specific type of trust in certain contexts, overlooking the









different levels of social connectedness in individuals' lives. Therefore, their studies simply

focused on a contextual understanding of social capital. Although some other scholars started to

analyze trust as a distinctive concept by looking at situational or contextual trust differently from

general social connectedness and even defined several types of trust for ordinary individuals-

public incumbents, general public organizations, and political institutions (Chanley, Rudolph,

and Rahn, 2000)- they did not provide any theoretical reasons or empirical evidence to support

how these categories were related to one another or how different levels of trust and other

aspects of social norms could be used to predict social and political consequences. Therefore,

their works failed to provide a complete explanation of how specific forms of trust at the

individual-level are influenced by broader social trust within the political sphere.

In addition, general networks, reciprocity, and trust were treated partially or broadly as

representatives of social capital according to the different purposes of each study. Previous

scholars did not exhaustively deal with multiple dimensions of social capital and explore how

these ideal concepts work together and are interrelated in societal contexts. For instance,

scholars in the social capital field view social networks through an even narrower perspective of

interpersonal attachment. Such scholars have used different types of social ties in various social

and political situations, resulting in studies that are too divergent to predict a coherent pattern of

political outcomes using such different perspectives of social capital. In other words, they have

not confirmed the overall the pattern linking the various aspects of social capital to a specific

political result. There are theoretical and empirical discrepancies that lead to difficulties in

explaining what social capital means, how each different element of social capital interacts in the

political contexts, and how they are developed into political consequences.









Social networks and trust are two different dimensions of social lives, each of which can

be interpreted in many different ways in political processes. Thus, the differing impacts of

individuals' social properties on their political beliefs need to be theoretically differentiated.

Without defining the concrete dimensions of such concepts, the research will lose the capacity to

deliver more accurate predictions (Braithwaite and Levi, 1998, p.69). Despite a number of great

scholarly works on social capital, the outlined limitations in understating its multiple

implications make the process of defining a firm theoretical approach to the subj ect more

difficult.

The third limitation is that the maj ority of scholarly research has focused only on the

positive or normative side of social capital, although a few insightful scholars, such as Putnam

(2000) and Hero (2003) argued the possibility of the negative impacts. Social capital indeed has

both positive and negative effects. One side of social ties is individuals' positive attachments to

certain groups, while the other side of excessive social group attachment, such as extreme

ethnocentrism or chauvinism, could isolate individuals from society. Individuals who

discriminate against out-group people in order to protect their own in-group against new

information could cause social conflicts and hinder social cooperation (Chong, 2000, pp.88-90).

Such bridging and bonding are typical political social scenes (Putnam, 2000). Even Putnam's

discussions on social networks and trustworthiness (1993 and 2000) overlooked all specific

social and political functions by overemphasizing overall optimistic consequences of social

capital (Franklin, 2003, p.352). Many well-known studies have overlooked the conflicting

values within social networks by failing to consider or define the multiple connotations of social

ties.









The Einal problem of previous research is a structural disconnect between individual

levels of social capital and macro levels of aggregate political consequences. There are

theoretical confusions between the two different levels of social capital at the individual and

aggregate state, and two different levels of individual political characteristics or aggregate

political outcomes. These connections have been vaguely explored without any specification.

The maj ority of previous research in the Hield dealt with aggregate social capital to predict

overall political tendencies and policy choices, ignoring micro level of dynamics. Thus, these

studies have struggled in finding a concrete connection between social capital that are initially

oriented from the micro-level of the individual and the macro-level of specific political attitudes

or choices. More interestingly, none of the previous research has looked at the impact of micro

levels of individual social capital on specific policy attitudes systemically as an intermediate

process before determining a final policy choice and other political outcomes.

For example, some previous empirical studies, such as Margit Tavits's work on social

capital and government performance, measured the links between micro levels of social capital

and governmental levels of political dynamics, such as policy activism and administrative

efficiency (Tavits, 2006). However, such studies omitted an important connection between the

diverse factors of social capital among individuals and the steps leading to policy outcomes. In

other words, the reasons of how individual levels of social capital turn out as a consequence at

the macro-level were not explained. The discrete measurement of two different micro-levels of

social lives and the macro-level of their political outcomes with a single indicator from each

level is problematic in answering the continuum level of research question.

In addition, although some studies, such as Oorschot' s research on the social

connectedness of European welfare states, differentiated various types of social connectedness,









they still retained the separation of micro- and macro-spheres by neglecting individuals'

intentions or motivations in state policies and separately analyzing national levels of aggregate

public sector outcomes. Putnam's perspectives on social capital in his books Bowling Alone

(2000) and Making Democracy Work (1993) looked at civic engagements or social networks as

the core of the individual social elements needed for a successful political system, and

considered trustworthiness a part of social networks. However, his research still did not clearly

answer the process of how individual levels of social capital could be developed as governmental

levels of political outcomes.

To deal with these limitations, my study intends to make an apparent connection between

the different aspects of individuals' social capital by attempting to show how these elements of

social capital are related to one another while rectifying the discrepancies between various

conceptualizations of social capital adopted by scholars in previous research. I also explore the

interrelation of various aspects of social capital to create a more reliable pattern and a more

consistent understanding of the multidimensional elements of social capital.

In the next step, my study intends to explore the intermediate connection between the

micro level of individual social capital and various policy attitudes accordingly. Moreover,

instead of regarding social capital as a single conceptual dimension and measuring a one-

dimensional relationship between the level of social capital and possible political outcomes, this

study presumes differences in individual levels of trustt and the various facets of social networks

as multi-dimensional components of individuals' social lives that lead to particular political

characteristics (Oorschot and Arts, 2005). In other words, it examines the ability of multiple

aspects of social capital at the individual level to predict particular policy attitudes rather than










simply connecting individuals and the aggregate political possibility or looking at the effect of a

single aspect of social capital on general political outcomes.

Finally, I create a pattern of the relationship between the multiple dimensions of social

capital and various policy attitudes by testing how individuals' single or collective social capital

elements influence their various political attitudes towards different types of public policy issues.

The specific policy attitudes and beliefs are explained through multidimensional social capital at

the micro level of the individual. Individuals develop particular attitudes and make various

political decisions about different political issues based on the cues they can easily take from the

views, preferences, evaluations, and actions of people who are part of their social lives and such

a tendency is reflected on larger aggregated political pictures. My study investigates the multiple

relationships between social connectedness within individuals' lives and multiple policy beliefs

and attitudes as an aggregate factor before policy outcomes. Using the 2004 General Social

Survey, the study determines whether different levels and various aspects of social capital shape

individuals' various policy beliefs and attitudes about different types of policies.

My study found that different elements of social capital, such as network intensiveness

and extensiveness, and levels of general social trust, contribute to different policy attitudes in

various ways. Although common elements of social capital occur by inducing positive

expectations toward government policies among individuals who are intensively involved in and

have extensive social networks or interactions, there are divergent elements of social networks

that are contradictory or even negatively influencing different types of policy attitudes. The

study confirmed that individuals who are intensively involved in a limited boundary of social

networks are less likely to be intensive in other types of social networks and less likely to trust

other people beyond their social networks; however, people who engage in multiple social









networks are more likely to engage intensively in any of those social networks, but again, less

likely to trust other members of the society.

In terms of redistributive policy attitudes, individuals who have higher levels of general

social trust are more likely to support government redistributive policies that would help the

'have-nots', however, social networks did not have a significant influence on such policy

attitudes. Moreover, multiple elements of social capital do not have any influence on policy

attitudes toward government activism that would often create public good. However, individual

social life patterns have a strong influence on policy attitudes toward government morality

policies on issues like abortion and gay rights. As long as individuals engage in any type of

social network, they tend to support government regulations on abortion and gay issues, placing

greater values on social morality over an individuals' freedom to choose. General social trust,

however, induces individuals' preferences on government regulations on gay rights, but not on

abortion.

These tendencies are still consistent when the relationships between social capital at the

individual level and policy attitudes are explored separately under different regional levels of

social capital. Multiple dimensions of social capital at the individual level in regions with either

higher or lower levels of social capital identically influence individuals' policy attitudes overall

besides the function of general social trust on morality policy attitudes. There is a stable positive

relationship between general social trust and supportive attitudes for different types of morality

policies in rich social capital regions, but the tendency becomes insignificant in low social

capital regions. Such tendencies are more stable at the regional level than at the individual level

where there are more fluctuating policy attitudes across different morality issues.









CHAPTER 2
LITERATURE REVIEW

This chapter discusses the definition and multi-dimensional elements of social capital.

Different elements of social capital, such as network intensiveness (bonding), network

extensiveness (bridging), and generalized social trust, have different political implications and

functions, and have both positive and negative features of general political and policy effects.

Therefore, I explore the components of social capital and their political implications on multiple

policies more closely using previous scholarly research.

Dimensions of Social Capital

Definitions of social capital

Scholars have looked at how individuals interact and what those interactions mean within

communities, demographic groups, or other political boundaries. Originally, Lyda Hanifan used

the notion of social capital for individuals' communal interactions. For Hanifan, social

connectedness interactions are "tangible substances [that] count for most in the daily lives of

people, particularly concerned with the cultivation of good will, fellowship, sympathy, and social

intercourse" (Hanifan, 1961, p.130). Several decades later, Robert Putnam (2000) introduced the

concept of reciprocal social relations to political research with greater concerns for declining

social networks in American society. According to Putnam, social capital is defined as

"connections among individuals- social networks and the norms of reciprocity and

trustworthiness that arise from them" (Putnam, 2000, p.19). Both the specific and generalized

reciprocity and trust that lubricate social and political processes are considered social capital,

which has "externalities" that affect the wider community beyond certain boundaries of social

networks or specific levels of trust (Putnam, 2000, pp. 19-21)









James Coleman (1988) views social capital as "a variety of different entities, with two

elements in common: they all consist of some aspect of social structure, and they facilitate

certain actions of actors" (p.598). Political scholars have used the concept of social capital

extensively, associating it with interpersonal social interaction, connectedness, or sense of

community to predict desirable political consequences such as positive policy outcomes, active

political participation, and economic growth.

Based on the characteristics of social capital that scholars have adopted, previous

research can theoretically be categorized into two broad areas: trust and social networks. For

researchers in the field of trust, trust is a kind of social connectedness used as a good or

commodity that helps members of society accomplish various purposes (Cook, 2001, p.21).

General social networks can also be interpreted in different ways such as the genre of

associations, extensiveness, or level of attachments. However, there is a blurred understanding

of social capital and none of its related concepts are fully defined. Based on the political

consequences scholars are looking at, their research has introduced various levels of trust,

different aspects of social networks, and some combinations of those two tenets of social

connectedness into the study of politics and policies. In general, social capital is "a glue that

holds society together" (Serageldin, 1996, p. 196), but we need to understand what it does and

how it works within a given field of research through a reliable pattern of predictions.

Different Dimensions of Social Capital

Multiple facets of social capital can stimulate and create different political outputs.

Although different elements of social capital are reinforced by each other for reciprocity and

collective actions, each of them plays a unique role in a society (Serageldin and Grootaert, 2000,

p.40). A number of scholars argue that social capital can be approached through dichotomous

dimensional tools: the elements of social capital can be structural vs. cognitive (Krishna, 2000),









horizontal vs. vertical (Putnam, 2000; Berman, 1997), heterogeneous vs. homogeneous (Portney

and Berry, 1997; Stolle, 1998), and formal vs. informal (Minkoff, 1997). Some also argue that

social capital is determined by the size and volume of social networks (Ihlen, 2005, p494). In

addition, social capital can be analyzed not only at the level of the individual, but also at the

macro level of groups, societies, or nations.

Scholars in the field of social capital have their own ways of viewing or measuring social

capital. For Putnam social capital is more likely to be based on horizontally organized formal

social networks, but for Newton (1997, p.582), social capital is more likely to be based on

informal social group networks. For Krishna (2000), cognitive elements of mutual collectivism

are different from the systemic structures that help such mutual actions (Bastelaer and Grootaert,

2002, p. 19-22). There is no theoretical agreement among scholars on the meaning of social

capital, but an increasing the number of studies on social capital means that the theories will get

more sophisticated and specific.

All possible macro-level political consequences depend on the dynamics of various social

capital issues on the micro-level of individuals. The field of social capital can be split broadly

into two schools based on the level of approach (whether research focuses on individuals or

groups) and the direction of approach (whether research focuses network intensiveness,

extensiveness, trust, or other substantive elements).

Social networks: theoretical understandings & empirical evidence

At the micro level of the individual's connectedness: Just as the definition and dimensions of

social capital are controversial, the theme of same level social networks has been explored

through different theoretical perspectives. Social networks at the individual level have been seen

through the effects of psychological group attachment or individual social interaction with

people who interact with each other in their daily lives. According to Conover (1988) and









Chong (2000), the degree to which social networks matter in political thinking differs based on

how much each individual likes or dislikes certain groups and how much each individual

identifies him- or herself with certain groups (Conover, 1988, p.54). Some scholars, like

Huckfeldt and Sprague (1993), however, defined contextual concepts of social networks through

individual physical interaction rather than cognitive attachment and examined the personal

political choices according to the situational contacts.

Huckfeldt and Sprague argued that "individual political preference is not a simple

function of individual characteristics alone, but rather the complex product of an individual's

own characteristics and predispositions of other surrounding individuals" (p.366). Individuals'

political lives extend far beyond self-evaluated partisanship. People place themselves in

neighborhoods, churches, workplaces, clubs, and associations, "they make these situational

choices for good reasons on rational grounds ..., [and these] multidimensional social structures

and exposures carry a political implication" (Huckfeldt and Sprague, 1993, pp.374, 380). This

approach emphasized the effect of social networks on individual level choices.

Conover was talking about people's attachments to groups at large, for instance; Blacks,

women, and Catholics, rather than groups that people actually see and talk with, which is what

Huckfeldt and Sprague referred to. Members of various groups are often likely to pay attention

to different things in the same political context. Individuals tend to evaluate others according to

different criteria, and they will adopt different perspectives when making judgments and

decisions on policy matters. "Group identification ... [fundamentally] shape[s] how people look

at politics ... [because] group identifiers differ in their viewpoints, it is expected that they will

evaluate public policies differently and subsequently assume distinct positions on issues"

(Conover, 1984, pp. 763-4, 770). Conover argued that an emotional closeness to certain social










groups initiate "political thinking on issues where the group cues are explicit and salient" (1988,

p.61).

Social attachments to groups or communities serve to form political thought and

behavior. Individuals' cultural norms, values, and group identification within a given society

accumulate in the political process over time. Conover's theoretical model (1988) demonstrated

successive information-filtering processes in long-term political attitude formation through social

networks. According to this model, issue preference is established in the following order:

accumulated social, biological, and cultural factors influence individual perceiver's

characteristics; these particular characteristics influence perceptions of outgroup, ingroup, self,

and/or policy related information; these perceptions influence evaluation of the issue through

identity associations; and the evaluations determine their issue preference (p.59).

As another example of individuals' psychological social attachments, Chong showed

political conflicts caused by resistant social connectedness against rational choice through

residents of a Texas community who needed to decide whether to compromise their long-term

emotional attachment to a political culture in exchange for business development that would

create jobs and fuel the local economy (Chong, 2000). His study proved that the strongly tied,

long-term group networks among the people of the community constrained their rational political

choices and shaped the pattern of their regional economic development.

Individuals' micro levels of social construction define their boundaries of political

information and perceptions on political issues (Huckfeldt, et al., 1995). Several studies have

illustrated different processes of policy perception and decision making using ranges of

particular social mobilization at the individual level, be they ideological bonds, socio-economic

ties, or just physical closeness within a given political boundary (Baker 1990; Erikson, McIver,









and Wright, 1987). Individuals who share relevant ideas within a group share similarities in their

political issues, and thereby provide guidance for policy makers by expressing homogeneous

desirability (Schneider and Jacoby, 2005, p.377). Therefore, levels of network intensiveness,

such as how actively, strongly, or intensively an individual engages in social networks,

determine various policy attitudes accordingly. Such community or individual level-focused

government approaches can be an efficient way to deal with public issues (Coppola, 2000).

At the macro level of group associations: Although there are a significant number of studies

looking at social networks at the individual level of differences in predicting political attitudes

and behaviors, there are more noticeable studies on social networks at the aggregate level of

group and political entities. In predicting political outputs, these macro-level theoretical

approaches to social networks look at the phenomena through a cultural, societal, or political

group rather than through the individual. These theoretical approaches portray social influence

as the product and residue of close and intimate ties, and thus it becomes a precondition for

political influence (Huckfeldt, Beck, Dalton, and Levine, J., 1995, pp.1025-27).

Several studies have found that different group memberships initiate different levels of

political attitudes and different forms of political involvement. For instance, members of unions,

farm associations, Greek associations, and church groups are less likely to be tolerant to a variety

of policies than non-members. And union memberships influence individual members' political

attitude more strongly than general community-type organizations (Cigler and Joslyn, 2002,

p.15).

Kwak, Shan, and Holbert (2004) also observed that association with religious attendance,

public attendance, or informal socializing results in different degrees of influence on civic

engagements. Among those three types of associations, public attendance is the strongest









indicator for active civic participation. Letki (2004) looked at the three distinct dimensions of

social organizations, professional/lifestyle organizations, and labor organizations during

democratization in East-Central Europe. He found that community associations are the most

significant indicator among the three dimensions of social interactions for active democratic

activities.

Additionally, group-level political tendencies were explored through various group-based

applications. A previous exit poll survey predicted political candidate popularity by assuming

"group voting." Individuals within a group, who share norms and beliefs based on ethnicity,

gender, or religion, invariably have a tendency to like or dislike a political candidate (Conover

and Feldman, 1984). For example, religious attachment is an important predictor for electoral

political activities and political protest activities. Strong religious traditionalists are against

liberal political movements such as gay rights and pro-choice legislation, so people in this group

tend to hesitate to vote for liberal Democratic Party candidates.

Furthermore, while there are some regional variations, White Americans are more likely

to be religious and less likely to engage in high-level political activity or protests, and they are

more conservative than ethnic minority groups on social and morality public issues (DeLeon and

Naff, 2004, pp.703 and 712). Different types of social networks and their standards for

belonging relate to each other in different ways of political tendency and preferences (Stolle and

Rochon, 2001).

Socio-economic categories representative of individual economic and social status also

create homogenous policy attitudes. According to Thomas Nelson and Donald Kinder' s study,

welfare beneficiaries as a group tended to interpret government support in terms of morality, and

have highly positive attitudes toward government assistance. General Americans' attitudes on










"poverty policy, federal spending on AIDS and affirmative action in employment and

educational settings reflect the degree of their importance to different social groups and the

broadness of social engagements. Group sentiment is a primary ingredient in public opinion"

(Nelson and Kinder, 1996, p.1071). Political arguments about group images that spotlight

certain social groups often activate people's stereotypes and prejudices towards the spotlighted

group. Such group sentiments then become the main clue for people to evaluate group-relevant

public policy in terms of "the cost and effectiveness of the proposed policy or the principles the

policy might advance" (Nelson and Kinder, 1996, p.1071-1074).

Different cities choose particular types of social services or civic inter-group programs

based on race, religion, or socio-economic status. Depending on the particular groups and social

networks that exist within a political boundary, policy makers need to devise different tools to

reflect what the public wants. Such a community composition is crucial for political processes

and the aspect is adopted in several studies on government in which the research proves that

community-friendly approaches are a cost-effieient means for public development (Walsh, 2006).

Moreover, James Gibson (2001) emphasized the roles of heterogeneous weak social ties,

which are relationships beyond family boundaries, during democratic transitions in Russia, Spain,

and Hungary. He found that the larger the heterogeneous social networks are, the more easily

they benefit the social and political movements at the national level (p.59). In addition, the

extensive social location of groups in issue networks affects the information available to them

about potential partners and the desirability of particular alliances. Groups of people in ranges of

social networks have aggregate policy desirability and a better level of policy efficacy than

people outside of certain networks. Interest groups especially, are formed through previous









interpersonal networks, and the networks become the basis of alliances to build a route of access

to the government (Heaney, 2004).

Casey (2002) found a moderate correlation between social capital and states' economic

performance. Putnam (2000) also added empirical evidence to the literature by proving that

broad social networks are positively correlated to the macro level of state outcome in low crime

rate, high economic prosperity, and a better child welfare system. Hetherington and Globetti

(2002) argued that general reciprocity through multiple social networks is a significant indicator

of state government performance by establishing greater accountability and efficiency for

government (p.272).

Margit Tavits (2006) measured the link between extensive social networks and

government performance by comparing Germany and the U.S. Her approach targeted the

national levels of social capital and the governments' levels of policy activism and

administrative efficiency. The study found that for both countries the level of trust, volunteerism,

membership, and informal socializing were positive indicators for policy activism although they

did not matter for administrative efficiency.

Overall, the factor of how broadly or extensively an individual engages in types of social

networks determines homogeneous political attitudes among members of a group, or groups, and

influences the macro-level of government policy outcomes. These approaches provide important

tools for the present study to observe social capital across different levels of single or multiple

group networks at an aggregate level by creating theoretical connections at multiple levels of

social and political interactions.

General social trust: Theoretical understandings & empirical evidence

At the micro level of individual confidence on general members of society: Unlike general

social networks, trust is a socially oriented emotional tie that creates a collective identity










(Braithwaite and Levi, 1998, p.378). It is a positive expectation on others in doing particular

things based on belief or knowledge rather than as a category of action and behavior (Cook, 2001,

pp. 7, 10). More importantly, trust is a cognitive process of moral commitments and

expectations (Coleman, 1990; Putnam, 2000). In social life, "trust sources include familiarity,

reliable information, and generalizations based on experience with similar actors, on-going

interactions, and confidence in the constraints provided by institutions" (Braithwaite and Levi,

1998, p.376). This multi-functional trust is dealt with as another component of social capital in

political applications in many studies.

There have been some disagreements about levels of trust, however. Recent scholars

tend to narrow down concepts of trust for their own purpose of study. For instance, Uslaner

conceptualized trust "as in stranger, not as in people we already know" (Uslaner, 2004, p.502).

Other scholars defined trust contextually by saying that "A trusts B to do X" (Braithwaite and

Levi, 1998, p.78). For the former scholar, trust is a general and broad concept of cognitive

reliance, but for the latter scholar, it is a very specific psychological status in a particular context.

Generally, people with a higher social status and who belong to the ethnic maj ority tend

to have a higher level of social trust than "have-nots" and ethnic minorities. In addition, people

from big cities are less likely to trust other people than people from small towns. These

tendencies are not inherent characteristics but accumulated from mistrustful experiences with

crimes and lies among people who are in a disadvantaged stage in a large, anonymous group.

Such a low level of social trust "easily generates vicious spirals" at the aggregate level of the

society (Putnam, 2000, p.138).

At the macro level of general social trust: There are also scholarly approaches at the aggregate

level of trust. In terms of theoretical approaches, trust is proven as a core concept in normative









social and political practices and it is suggested as an alternative solution for problems in those

practices (Cook, 2001, pp.307-20). Trust also often serves as an interesting element for smaller-

sector politics at the local or community level. One study investigated neighborhood effects in

Texas using trust as a mediator in welfare policy efficacy. The study found that the

neighborhood associated with lower trust had lower collective efficacy in health and education

policies and higher degrees of fear of crime and racism. Trust was a key factor for the

community to be better- or worse-off as a result of the social programs. Therefore, this

neighboring effect directly influences a state's particular policy direction (Franzini, et al., 2005).

Some argue that trust in government and political systems benefits democratic political

processes. Others argue that individual trust towards people with whom they have only little or

no direct interaction contributes to collective action. Theoretically, social trust is different from

"trust in institutions and political authorities." Social and political trust may empirically relate to

each other, but theoretically should be kept distinct (Putnam, 2000, p.137). Some scholars argue

that "with population groups and greater structural differentiation, a great number of social

relationships are based on cognitive or general trust rather than on emotional or specific trust"

(Lewis and Weigert, 1985, p.973).

There are various ways to conceptualize trust based on where trust activates, the persons

who are the targets of trust, and how fluctuating the trustful environment is. To explore trust in

its multiple levels of political attitudes and citizenships, we may need to adopt general social

trust or generalized expectancy as the core concept; to understand personal interactions we may

need to take specific emotional or institutional trust into account. Regardless of whether trust is

based on emotional ties among primary groups or cognitive rationality among more extensive









secondary groups, the level of trust contributes to optimistic views towards social systems and

allows cooperation to be more easily recognized and proceeded (Putnam, 2000; Scholz, 1998).

Levels of general trust fluctuate throughout political events. Schmierbach, Boyle, and

McLeod (2005) observed that increased levels of general trust among Americans after the

terrorist attack of September 11Ith CHCOuraged people's political participation and strengthened

conservative policy preferences and ideology among American citizens, meaning that American

citizens were more likely to support President Bush' s conservative policies and religious values

(pp.333, 341).

The trust level among a general group in an emergent national situation determines or

creates different political environments for the political actors. During the peak of a trust mood,

people were more likely to cooperate with national-level decisions and evaluate the outcomes of

government policies in a positive way. Such a surge in social connectedness creates active and

cooperative political attitudes among citizens, at least for a short time (Schmierbach, Boyle, and

McLeod, 2005).

Another study on 31 non-metropolitan Michigan residential units found that the

differential ability of political sectors to realize mutual trust and solidarity was a maj or source for

measuring residential units' variations in determining their political needs. Therefore, several

policy recommendations were endorsed based on resources of social connectedness, especially

trust, which could help to facilitate collective efficacy for improving citizens' life quality in

specific political sections (Cancino, 2005).

The macro level of general social trust within political boundaries is highly related to

social equality and active government actions for the citizens. John Scholz and Mark Lubell

(1998) found that both types of trust in government and other citizens provided conditions for a










collective solution, thus were more likely to lead to a better outcome such as tax compliance.

According to Bo Rothstein and Eric Uslaner (2005), countries with a high level of social trust

have higher levels of economic equality and more opportunities for individuals within the

political boundary, and their governments are more active in their social policies, such as

education and health.

Overall, there are specific tenets of social networks and trust, and they not only share

some commonality and reinforce each other's social and political functions, but also lessen the

function of other tenets. According to Gibson (2001), members of social networks are more

likely to trust others and think that others trust them. Political cooperation is not likely to take

place among perfect strangers. In addition, general social networks help convert strangers to

friends (p.61). "Social trust and civic engagement are strongly correlated; the greater the density

of associational membership in a society, the more trusting its citizens. Trust and engagement

are two facets of the same underlying factor social capital" (Putnam, 1995, p.73).

Yet as Hero (2003) argues, a high level of social capital, especially trust from particular

groups, can also reduce the positive political outcome for the minority groups. Different social

networks are activated by different issues and situations (Shore, 1993). Especially, particular

social groups that individuals are more attached to or more deeply controlled by, determine their

political preference. Policy attitudes are usually determined by personal orientations (Saris and

Sniderman, 2004, p.95). Therefore, specific categorizations and different consequences of

various levels of trust and different aspects of general networks need to be considered in order to

conduct more consistent research.









Functions of Social Capital

The Positive Consequences of Social Capital

The maj ority of scholars present the positive impacts of social capital, assuming that

individuals' collective engagement in public sectors is critical for effective economic and

societal management and political development, and that interpersonal networks are necessary

for satisfactory personal lives in both moralistic and practical benefits. Social capital is

particularly more helpful for general social policies over other political or economic policies

(Frank, 2003, pp.3-6). However, there are two opposite spill-over effects of social capital, which

can be meaningful in varying degrees along a positive-negative continuum (Hazleton and

Kennan, 2000, p.84), though it is theoretically and empirically more likely to veer toward the

positive side. Let' s discuss the optimistic understanding of social capital first.

At the micro level of social capital: Social capital makes more knowledge and information

available for individuals in a network web, and thus helps individuals to be more efficient to

cooperate with and behave among other members of a society. Thus, those with high social

capital are more likely to be 'hired, housed, healthy, and happy than others who have no social

connections', thus have more possibilities to relive from welfare program (Woolcock, 2001,

p.68)

One study found that locally-oriented businesses, civic organizations, and churches can

have positive effects on individuals' personal satisfactions (Tolbert, 2005). The study also

illustrated how a community's ability to satisfy residents in terms of school systems, sanitary

issues, or safety is highly related to civic involvement and active community networks (Keele,

2003). For instance, social capital within a company helps individuals develop "speed training,

improve employee morale, and enhance loyalty to the company" (Putnam, 2000, p.320). In









addition, general interaction helps individuals' physical and mental health and wellbeing within a

given community (Putnam, 2000, pp.288-89)

Ethnic networks often work as employment networks and business connections,

especially within immigrant groups. For instance, Chinese immigrants often dominate certain

services or industries through highly developed internal networks in big cities. Likewise, Korean

business owners tend to initiate their careers through family connections or support. Thus, social

ties within certain groups help individuals' economic wellbeing (Putnam, 2000, p.320).

Beyond ethnic group boundaries, individuals in a society tend to obtain jobs through the

people around them. In fact, church groups and neighborhoods are the very foundation for

individuals' social and economic activities (Putnam, 2000, p.321). Highly committed

neighborhoods stabilize family lives by reducing incidents of misbehavior among family

members. If parents know other parents with children attending the same school as their children,

kids are more likely to be actively engaged in class. Furthermore, caring neighborhoods reduce

drug use and teenage vandalism (Putnam, 2000, 314-15)

Allan Cigler and Mark Joslyn discovered that the extent of group affiliations is positively

correlated with political tolerance towards social policies. Individuals who are more involved in

voluntary associations tend to understand different viewpoints with greater ease. Although some

variances according to group-type exist, memberships in multiple group associations also

increase political tolerance towards various social issues (Cigler and Joslyn, 2002).

In sum, at the micro-level, social networks and trust enable community members to

contribute to society as a whole. More importantly, social capital provides 'non-economic

solutions' to any social issues (Portes, 1998)









At the macro-level of social capital: At the macro-level, intertwined networks and aggregate

trust create healthy communities in terms of social and political improvement. Social capital

does not work by one direction flow. Rather, it is achieved through links and relationships of

two way flow between top and bottom (Glaeser, 2001, pp.39-40). Putnam argues that social

networks among citizens act as a civic virtue in civil society and contain a set of predetermined

connotations of economic efficiency and political benefits at the macro-level of state and

national politics. The aggregate level of a community's ability to conduct collective activities is

positively related to the successfulness of all governmental-level of social, political, economic

programs (Putnam, 2000).

In Putnam's comparative study of Italian regional governments, he found that successful

regional political entities had stronger civic engagements, integrity, and more active community

organizations compared to the failed other local governments. Such civic involvements, social

solidity, and networks are accumulated as economic and political assets, and thus can help

political systems be more successful and economic development more efficient (Putnam, 1993).

Social networks and associations help citizens resolve collective problems easily, allow

communities to advance smoothly, develop character traits that are good for the rest of society

(Putman, 2000, pp.288-90), foster robust norms of reciprocity, facilitate communication,

improve the flow of information, and stabilize collaboration (Putnam, 1993, pp.173-74). In

addition, levels of social networks among citizens bring minorities into society, and as a result,

help ensure a more inclusive and flourishing democracy (Wolbrecht and Hero, 2005).

More specifically, studies show that social networks are relevant to several types of

public policy, such as education and health programs. In particular, information sharing, lower

transition costs, low turnover rates, and greater coherence of action are optimal situations for









maintaining social progress with minimal effort and governmental costs (Cohen and Prusak,

2001, p. 10). The existing social networks save a lot of cost for the government to build new

routes or frameworks to allocate resources to the society (Productivity Commission, 2003, p.56).

Social capital itself produces collective well-being, enhances confidence in political institutions,

naturally reduces crime rates, and accelerates government performance (Brehm and Rahn, 1997,

p.1000; Coleman, 1988; Fukuyama, 1995; Knack, 2002).

Furthermore, extensive civic engagement from citizens provides "free spaces" for

political discussions and the sharing personal ideals that would directly influence decision-

making processes (Barakso, 2005). As an example, the city of Omaha, Nebraska actually

provided a civic engagement program that encourages neighborhood associations to register

formal documents and get involved in several city proj ects in order to deal with community

issues more effectively. All city issues, such as natural disaster emergency management,

landscaping proj ects, clean water, and energy problems, have been handled with a great

efficiency in a shorter time period compared to other cities' local government management

processes without such devices (Fahey and Landow, 2005).

Another facet of social capital, interpersonal and societal trust, also enhances the

democratic process (Almond and Verba, 1963). Democracy is an institution that allows citizens

to make judgments not only about political platforms but also about the trustworthiness of people.

Trust in democracy allows people to believe in each other and is therefore necessary for an

effective political environment (Braithwaite and Levi, 1998, p.69). Some argue that social

assurance and confidence between individuals and institutions is an essential element to building

a civil society, creating invisible ties between general public and social institutions (Inglehart









1997; Mishler and Rose, 1997), as well as a shared set of values, virtues, and expectations among

members of a society (Beem, 1999, p.20).

Robert Axelrod (1984) showed how repeated trust among actors benefit given political

structures and maximize resources through empirical game exercises. Trust reduces the social

and economic complexity caused by rational predictions of individuals' interactions. Rather than

calculating rational outcomes, trust creates "a simple and confidence basis" (Lewis and Weigert,

1985, p.969). Social trust contributes to social equality and encourages government actions on

education, health care, labor-market opportunities, and gender equality (Rothstein and Uslaner,

2005).

The Negative Consequences of Social Capital

There are a significant numbers of scholars who remain suspicious about the potentials of

social capital. Depending on the different properties of social networks and trust, whether

relationship boundaries are exclusive or inclusive, or the structure of a relationship is hierarchical

or horizontal, there are possibilities of negative effects of social capital (Dasqupta and

Serageldin, 2000, p.47). In addition, political conservatism within elements of social capital can

also be a negative impact on liberal policy applications (Portes, 1998).

At the micro level of individual complexity: Social capital can disturb stable interpersonal

activities and does not always benefit every single member of a society. How strongly and

broadly an individual interacts with other people in a society determines the degree of the

personal level of social capital. Personal ranges of social interrelationships also vary, leading to

variations in emotional expectations and physical behavior boundaries. Some individuals tend to

take advantage of the high level of social capital around them, but others often face disappointing

outcomes from interpersonal relationships because of unwritten rules about reciprocal exchange

and different levels of social capital between individuals.









Due to the various levels of social capital in different individuals and groups, it is hard to

predict expected outcomes of group activities. Individuals in a society in which there is a high

level of social capital can easily violate expected reciprocity after they receive benefits. Trust

often creates demanding attitudes towards coworkers when completing given tasks, and unlocks

responsibility, thereby causing unnecessary conflicts in collaborative works. Unspecified

obligations and unpredictable outcomes with a high level of expectation can problematize task

completion and make it hard to achieve social stability (Hazleton and Kennan, 2000, p.85).

Moreover, individuals with an extremely high level of social capital could be even more

seriously disappointed and hurt after experiencing betrayal, and individuals who have higher

levels of trust tend to expect more from others. When subjective emotional trust has failed, the

emotional outrage can be more disastrous and the functional parts of the society become

uncontrollable. Therefore, future uncertainty about others' actions and "the violation of

particular expectations" after experiencing betrayals lead individuals to become much more

distrustful of others than during their initial stage of the interaction with no trust (Lewis and

Weigert, 1985, p.971).

Social capital can also create undesirable group attitudes and societal tendencies.

Individuals in small towns are highly engaged in their community life, but they are less tolerant

of differences and diversities (Putnam, 2000, p.352). Because social capital is often easily

established by race, gender, and political affiliations, individuals within such social networks are

less likely to understand people from other societal or political sectors. For instance, small

communities and highly committed neighborhoods are less tolerant of homosexual teachers and

interracial marriages for people of their own communities (Putnam, 2000, p.352-53). A strong









and narrow level of social capital can constrain an individual's freedom to choose (Schudson,

1998).

At the macro-level of political, societal and economic shortcomings: Discussing the NIMBY

("not in my backyard") movement and the Ku Klux Klan activism of racial discrimination,

Putnam admitted that "networks and the associated norms of reciprocity are generally good for

the inside of the network, but the external effects of social capital are by no means always

positive" (Putnam, 2000, pp.21-22). Intensively connected social networks or interest groups

"distort governmental decision making" and "trigger political polarization and cynicism"

(Putnam, 2000, p.340).

The density of social networks and bonding determines the capacity of specific

reciprocity and solidarity. Putman argues that inclusive networks "generate broader identities

and reciprocity" thus allowing for the diffusion of information and economic efficiency, but

tightly bonded networks "reinforce exclusive identities and homogeneous groups... undergirding

specific reciprocity" thus creating not only strong in-group loyalty but also strong out-group

antagonism (Putnam, 2000, pp22-23).

Kraign Beyerlein and Jone Hipp (2005) found that strong bonding networks among

Evangelical Protestants led to a greater percentage of crime rates, while weak-bridging bonds

between Protestants and Catholics reduced crime rates affHliated with those religious social

networks across nearly all U.S. counties. Individuals' ability to build social support is

constrained by their social bonding (Sachser, in press).

Rodney Hero (2003) is one of the scholars who challenge fully optimistic views of social

capital on specific political sectors of public policy. He argues that the level of social capital can

magnify inequality among society members. At state-level politics, Hero saw that rich social









capital benefits the racial maj ority but isolates the racial minority. States with high levels of trust

also tend to yield worse policy outcomes that directly address racial equality for minorities, such

as low-income black populations within a given political sector (Hero, 2003).

Although current public policies utilizing social capital, such as encouraging informal

relationship and engaging in social activities, have a great deal of benefits, the uncertainty of

social capital, the requirement of multiple reinforcements from multiple actors, and flexibility

based on localism make such policies much more difficult to apply to multiple situations in an

uniformed way, preserve possible effects, and measure the potential problems. Therefore, there

needs to be careful adjustment and design for social-capital oriented public policies (Productivity

Commission, 2003, pp. 58-60). In addition, "policies which strive towards social order and

cohesion have the potential to lose individual freedom and autonomy along the way" (Franklin,

2003, p.352).

Previous scholarly research tells us that social capital can have a number of different

meanings and serves as multiple causes and results in the political arena. More specifically,

social networks and general social trust have different elements of social capital; and the level

and range of social engagements are different dimensions of social networks. Social capital has

various ways of influencing policy attitudes and political tendencies, and the effects can be both

positive and negative. Considering the variety of policy types, my study assumes that

individuals' attitudes towards various types of policies may be influenced by different social

surroundings or connectedness of different degrees. Various levels of social trust and social

involvement filter individuals' particular aspects of political information differently and

determine levels of assessment to political information. Utilizing previous scholarly research

and arguments stating that different aspects of social capital affect different policy preference









and further induce policy choices, I explore the relationship between specific elements of social

capital and particular policy attitudes. I also attempt to develop reliable patterns of policy

tendency using multiple dimensions of social capital.









CHAPTER 3
HYPOTHESES AND THE PERSPECTIVES

As seen in the previous chapter, there are significant interactions between individuals'

policy perception/preferences and their daily interactions with other members of a society. This

study examines individuals' policy beliefs that would be triggered by social elements within their

interpersonal lives rather than pragmatic policy processes or policy outcomes. Previous research

found significant but varied correlations between social capital and specific types of public

policy consequences. For example, Putnam (2000) showed that states with intensive social

networks tended to have better welfare achievement, especially for the poor, weak, or

disadvantaged people (pp. 297-306, 317). People living where there are higher trust levels and

reciprocal community moods tend to have positive political expectations about governments'

decisions and policies (Schmierbach, Boyle, and McLeod, 2005), feel less of a necessity for

government actions (Wood, Owen, and Durham, 2005), and tend to be more tolerant and

understanding of differences and diversities (Cook, 2001, pp212-31).

Based on some common elements of individuals' beliefs toward certain policy type that are

activated mainly by different aspects of social capital, this study categorizes multiple dimensions

of social capital into social networks (intensiveness and extensiveness) and generalized social

trust and also sorts various policies into three different policy attitudinal groups. Theoretically,

network intensiveness is meant to measure how intensively and exclusively an individual is

involved in social networks. Thus, this concept is related to Putnam's understanding of

'bonding'. In contrasts, network extensiveness measures how broadly and inclusively an

individual engages in social networks, thus it is consistent with Putnam' s concept of 'bridging'.

Lastly, general social trust is meant to measure levels of general belief in people and society.

Therefore, general social trust is different from Hardin's (2002) trust built on physical personal









interaction basis or Cook' s (2001) specific social trust on particular targets. Rather, general

social trust has a non-specific range of positive perception on people in general.

In terms of policy categorization related to social capital, the first category is

'redistributive' types of policy that exclusively helps or encourages the have-nots (Levy, 1986)

(See Appendix B.1). The second type is 'government activism' policies that help overall societal

development for the collective public (Rudolph and Evans, 2005) (See Appendix B.2). The last

type is 'morality' policies that deal with morally controversial issues (Mcfarlane and Meier,

2000) (See Appendix B.3). Retrieving previous research and logical rationales, I posited these

hypotheses.

On Redistributive Policies

Previous research has argued that different types of trust have different political and

social potentials. Unfortunately, there is no clear answer for the function of generalized social

trust on various types of public policies. Individual levels of generalized social trust can have

multiple meanings, and the degrees of trust matter differently (Putnam, 2000, p. 136-39).

Although there are theoretical and empirical discrepancies, some research argues that

"high levels of generalized trust facilitate the provision of public goods and provides social spin-

offs in the forms of ...welfare dependence, lower health care expenditures ...and so on"

(Productivity Commission, 2003, p. 57). Assuming that the traits of redistributive public policies

are consistent with the tendency of trust in terms of benevolence, charity, and belief, my study

hypothesizes a positive relationship between general social trust and supportive attitudes toward

redistributive types of public policies.

HI.1: hIdividuals having higher levels of general social trust are more likely to support

redistributive tyipes of public policies than individuals having lower levels of general social trust,

controlling for individuals' demographic characteristics.











In pragmatic perspectives, social capital in particular, tends to contribute to a better

outcome with respect to welfare policies. Through multiple social networks, people who are

well connected are more likely to get greater benefits from the society, and thus have more

chances to be independent from government subsidies (Woolcock, 2001, p.68). In normative

perspectives, multiple heterogeneous social memberships widen and enlighten alternative

viewpoints about various social and political issues, while limited homogenous group

memberships could create isolated or narrow minded perspectives (Putnam, 2000, p.341). Based

on the broad nature of networks, and its relevance with supportive attitudes toward helping the

poor, I assume the positive relationship between network extensiveness and redistributive policy

attitudes.

H1. 2: hIdividuals involved in extensive social networks are more likely to support

redistributive tyipes of public policies than individuals who have no, or limited social networks,

controlling for individuals' demographic characteristics.

As Gibson (2001) argues, broader social connectedness is more important for macro-level

political changes or movements than a strong single primary group attachment that often

discouraged balanced democratic movements. Individuals intensively involved in broader social

networks, such as voluntary or religious groups, are more likely to be concerned and expressive

about overall social equality and well-being. However, people intensively involved in a limited

range of networks with limited perspectives, such as occupational/professional unions, tend to

care more about their direct self-interests (Boninger, Krosnick, and Berent, 1995). In addition,

the interpersonal relationship within an intensive single social network such as professional

organizations or associations is often temporary, formal, weak, and limited in the range of

socializations possible within the network rather than being a meaningful and close personal










interaction (Putnam, 2000, p.87-90). Therefore, my study assumes a negative relationship

between a single intensive network and redistributive policy attitudes that require the sense of

community for the general public rather than specific interests.

HI. 3: Individuals intensively involved in a limited range of social networks are less likely

to support redistributive tyipes of public policies than individuals who are not intensively

involved in any or in multiple social networks, controlling for individuals' demographic

characteristics.

On Government Activism

As mentioned, social trust is considered diverse in terms of target objects, degrees, and

the effects. For instance, 'thin trust' is more adequate for expanding individuals' personal

networks through loose connections and encourages individuals' supportive attitudes towards the

various social and political issues of others; more so than does the 'thick trust' of dense and tight

emotional attachments and social exchanges (Putnam, 2000, p.136). Thus, the ambiguity

suggests many different possibilities for the effect of general social trust on various policy

attitudes.

Nonetheless, there is evidence that individuals with low levels of trust towards the

general society or the public are more likely to rely on public or professional services and

government support for their necessities rather than their neighbors or the private sector. This

tendency has been observed over the last half century in American society (Putnam, 2000, p. 144-

145). In contrast, individuals with high levels of generalized trust tend to keep their eyes focused

on their communities and concern themselves only with each other, thus self-interests are served

within the community. Therefore, individuals having higher levels of general social trust would

tend to be less dependent on governmental social services (Putnam, 2000, p. 135).









H2.1I: Individuals having higher levels of general social trust are less likely to support

government activism than individuals having lower levels of general social trust, controlling for

individuals' demographic characteristics

Individuals who are more involved in broader social networks are more likely to be

exposed to public issues such as education, environment and health, and discuss those issues

either at the local or national levels. These individuals tend to care more, and voice stronger

opinions about governmental policies on those issues (Putnam, 2000, p.51-3)

H2. 2: Individuals involved in extensive social networks are more likely to support

government activism than individuals who have no, or limited social networks, controlling for

individuals' demographic characteristics.

Politically active individuals are more likely to support government actions although

political tendencies vary depending on different party identification and the scope of political

views. However, occupational/professional unions or networks focus on narrower self-interests;

hence, the members of those types of organizations are less concerned with general public issues

and reluctant to have governmental control over their professional spaces. Overall, members

belonging to any organization that has narrower and more specific interests or goals are less

likely to support governmental activism that ultimately targets the benefits of the general public

rather than specific interests (Cochran et al., 2006; Putnam, 2000, pp.80-91).

H2. 3: Individuals intensively involved in a limited range of social networks are less likely

to support government activism than individuals who are not intensively involved in any or in

multiple social networks, controlling for individuals' demographic characteristics.

On Morality Policies

Individuals trusting general society as a whole, and other members of a society tend to

dislike governmental intervention in their private lives. Some scholars argue that individuals









who trust people of the general public more rather their government and political leaders, tend

not to be confident about any type of government-initiated policy (Wood, Owen, and Durham,

2005). Those people believing not only in their sphere of acquaintances, but also in general

public, tend to avoid any political constraints and are more likely to be tolerant of minority

views. Thus, those people tend not to care about, or avoid governmental control on personal

morality issues such as abortion and gay rights (Cook, 2001, pp.307-20, Putnam, 2000, p.137).

H3.1I: Individuals having higher levels of general social trust are less likely to support

morality based tyipes of public policies than individuals having lower levels of general social

trust, controlling for individuals' demographic characteristics.

As discussed, individuals who are involved in extensive social networks are more likely

to be exposed to multiple points of view, and thus tend to be more understanding about different

perspectives (Cigler and Joslyn, 2002). For the same logical reason regarding network

extensiveness, the study assumes the negative correlation between multiple memberships and

supportive attitudes for morality government policies that somehow constrain individuals'

freedom to choose their life style. Morality issues require a great deal of tolerance toward

diversity (Putnam, 2000, p.341). Therefore, extensive memberships in multiple networks would

reduce the desire for governmental control on individual's lifestyle choices. However, we also

need to consider that exclusive membership in a single or limited network can be worse than no

membership in any network, in terms of social tolerance. Strong single in-group attachments

could lead to little tolerance for out-group differences (Putnam, 2000, p.355)

H3. 2: Individuals involved in extensive social networks are less likely to support morality

based tyipes of government regulations than individuals who have no or limited social networks,

controlling for individuals' demographic characteristics.









As discussed in the rationale for network intensiveness, people engaging intensively in

more than one social network tend to be more tolerant to differences and diversity, and are more

likely to respect the rights of others (Putnam, 2000, p. 80, 137, 335). However, social capital can

also create undesirable group attitudes and societal tendencies if the social networks are narrowly

structured. For instance, individuals in small towns are highly engaged in their community life,

but they are less tolerant of differences and diversities (Putnam, 2000, p.352). In addition,

politically or religiously conservative people with a limited range of social networks would not

be tolerant with societal differences (Schudson, 1998), thus dislike individuals' freedoms to

choose and preferring stricter governmental regulations on social morality issues (Putnam, 2000,

pp.357-8).

H3. 3: Individuals intensively involved in limited range of social networks are more likely

to support morality based government regulations than individuals who are not intensively

involved in any or in multiple social networks, controlling for individuals' demographic

characteristics.

In summary, based on previous research on social capital and various political

implications, my research presumes that general social trust would encourage positive attitudes

toward redistributive government policies that help socially disadvantaged people, but induce

negative attitudes for other types of government interventions in both public and private spheres.

The factor of how extensively, or broadly, people were involved in social networks would

positively influence redistributive and government activism policies that create social equity and

public goods, but negatively influence policy attitudes for government regulations on morality

policies. Lastly, however, people who engaged in single or limited social networks intensively

would be less likely to support both redistributive and government activism policies, but more










likely to support morality government policies that somehow constrain social diversities and


differences.

Table 3-1. Hypotheses Matrix
General Social

Trust


Extensive

Networks


Limited

Intensiveness


Redistributive

Policy
Government

Activi sm

Morality

Regulation










CHAPTER 4
METHOD

Data

To test the hypotheses, my study uses the 2004 General Social Survey (GSS) data gathered

by the National Opinion Research Center through national probability sampling. The GSS was

designed to survey various social issues and political attitudes at the individual level, and has

repeated many core questionnaire items and question wordings in order to facilitate time-series

studies.

The GSS 2004 data were gathered through Computer Assisted Personal Interview (CAPI)

using a national full probability sampling. The median length of the interview was about one and

a half hours. The participants were English-speaking persons 18 years of age or over within the

U.S. The sample size was 2,812 and weighted for the Black subpopulation to adjust overall

ethnicity proportion in the U.S.

The 2004 GSS asked more detailed questions about individuals' civic engagements and

their political attitudes. Beyond GSS general categories of demographics, media consumption

patterns, negative life events, religious transformations, daily religious practice, an experiment

on measuring immigration status, altruism, an experiment on measuring alcohol consumption,

attitudes towards guns, social networks and group memberships, sexual behavior and genetic

testing, the role of heredity, and stress and violence in the workplace, the 2004 GSS included the

"citizenship module", a new series of items collected in the 2004 data.

The 'citizenship module' included questions regarding civic and political participation,

social welfare policies, efficacy, misanthropy, international organizations, political parties,

SThe principal investigators of the 2004 General Social Survey were James A. Davis, Tom W. Smith and Peter V.
Marsden. These were made available to me by the Interuniversity Consortium for Political and Social Research
(ICPSR Study Number 4295). Neither the National Opinion Research Center, Professors (James A. Davis, Tom W.
Smith and Peter V. Marsden), nor the ICPSR are responsible for my analysis and interpretation of the data.










political corruption, and the working of democracy. The questions regarding these categories

sought the respondent's opinions on social and political topics such as the environment,

government, society in general, the economy, leisure activities, interpersonal relations, health

care, personal philosophy, and other moral controversies. As is evident, the GSS is well

incorporated with the perspectives of this study with reliable categories of different facets of

social capital in trust and social networks to explore patterns of various policy attitudes.

Perspectives of Categorization

Measuring Dimensions of Social Capital

Social capital is an amorphous concept and has multiple connotations. Some scholars

argue that social capital needs to be explored through qualitative methods (Coleman, 1990),

while others claim quantitative analysis is the only means of measuring social capital (Bourdieu,

1991). As we observed in the previous chapter, there are ongoing debates regarding the levels

and dimensions of social capital. Scholars identify different aspects (or "facets") of social

capital based on their own theoretical or empirical judgment. For instance, as Bastelaer and

Grootaert (2002) summarized, social capital can be approached using multiple dichotomous

categories of Structural vs. Cognitive, Horizontal vs. Vertical, Heterogeneous vs. Homogeneous,

or Formal vs. Informal dimensions. A social tie can be interpreted as any one of networks, roles,

rules, life patterns, norms, values, attitudes, or beliefs; thus researchers find diverse meanings of

social capital for different individuals and social systems. Thus, depending on the definition of

social capital used, researchers need to consider possible rationales, implications, and functions

of their ways of categorizations.

My research intends to examine social capital in a more comprehensive and exhaustive

way. I incorporate both theoretical understandings and quantitative methods in order to explore

the concept of social capital. For instance, in the categorization stage of social capital, I adopt









theoretical approaches of several scholars to determine the various implications of the multiple

concepts of social capital and to retest previous empirical evidence. Multiple dimensions of

social capital overlap in their social functionality and definition (Putnam, 2000). Utilizing

multiple concepts of social capital such as network extensiveness and intensiveness, reciprocity,

and trust that have been discussed in previous studies, my study measures multiple implications

of different dimensions of social capital in policy attitudes. In order to achieve comprehensive

but exclusive measurements of social capital, I sort out distinctive elements such as the

difference between social networks and trust, but merge similar elements of social capital per se,

under network intensiveness or extensiveness that has its own homogenous implications.

Previous studies showed that theoretically both social networks and trust are core parts of social

capital (Putnam, 2000), but each has its own functional effect on various political perspectives.

Therefore, my study keeps core elements of social capital that would maintain their exclusivity

enough to be distinguished from each other in concept and functionality, but the sum of each

category would cover all possible implications of social capital.

In terms of dimensions of social networks, previous scholars argued about the

intensiveness and extensiveness of social networks. In other words, depending on how broadly

individuals engage in and how intensively they participate in social networks, people have

different perspectives toward different policies. Therefore, the operational definition of network

extensiveness is somewhat consistent with Putnam's concept of 'bridging' that connects people

inclusively. In contrasts, the operational definition of network intensiveness is consistent with

Putnam's meaning of 'bonding' that connects members of a social group exclusively (Putnam,

2000, pp.22-3). Network intensiveness and extensiveness are consistent with the definition of

social capital, but clearly distinguished from one another in individuals' social life patterns. At









the same time, these two are interrelated indicators that have different impacts on individuals'

policy beliefs; thus, they should be treated as theoretically distinctive elements of social

networks (Granovetter, 1973, p.1361). Therefore, I also keep network extensiveness and

intensiveness as separate indicators for the range of social connectedness and levels of

intensiveness in social involvement, respectively, that can predict multiple possibilities of

impacts on policy attitudes.

In the measurement of general social trust, my study targets trust in participants' general

social lives. There are multi-dimensional conceptualizations of trust based on its relationships

with policy attitudes in political processes. Different research programs look at different aspects

of interpersonal trust. Social trusts toward ordinary people may need to be differentiated from

trust toward governments or political institutions. "Empirically, social and political trust may or

may not be correlated, but theoretically, they much kept distinct" (Putnam, 2000, p.137). In

addition, general trust toward the general public is also different from Cook' s concept of specific

types of trust toward a particular individual in a particular situation (2000) or Hardin' s trust

limited to personal relationships (2002).

Therefore, my study focuses on interpersonal beliefs toward the general public or

members of a given society, namely generalized social trust, primarily in order to test the tenets

of trust in the social dimension rather than trust in governments, specific institutions, or

particular individuals. In other words, trust in this study is interpreted as general trust toward

ordinary people in their daily social lives. Rather than defining trust as a specific or a broad

concept of interpersonal belief or as confidence in political leaders or government systems that

may be changeable based on individuals' given environment or resources, this study explores










general social trust toward ordinary people or society in order to measure only its social

components .

After considering multiple theoretical frameworks, I determine that social capital would be

explored through two categories of general social networks that physically connect members of a

society either in extensive or intensive ways and general social trust that creates common facets

of beliefs or norms. My study defines general social networks as public sphere interactions. For

instance, civic engagement in public affairs, organizational activities for socialization, voluntary

networks for general social improvement, and diversity of social engagements are the main

elements of this dimension of social connectedness. General social trust is composed of beliefs

toward the general public in the society. The belief that other members of the society are trusted,

fair, and helpful is among the many meanings of general social trust.

In order to achieve a high reliability and validity for each measurement and scale, I

adopted measures that have been used in previous studies, signaling them as reliable indicators.

In the measurement of social networks, I adopted Putnam' s measurement of participation level in

multiple social networks and Cigler and Joslyn' s numbers of networks. Network intensiveness

was measured by levels of how intensively individuals were involved in given social gatherings

such as volunteer work for common issues, political community meetings and others

professional associations, religious gatherings, and other social and leisure activities (See

Appendix A. 1.). Network extensiveness was measured using the total number of memberships

to which each individual belongs (See Appendix A.2.). In measuring general social trust, I

utilized three different questions asking individuals' levels of beliefs in general society that have

been used frequently in previous research, such as Putnam (2000) and Gibson (2001)' study on










social trust, and national panel data, such as National Election Studies (NES) and General Social

Studies (GSS) (See Appendix A.3.).

Using the 2004 GSS data, I first used participation levels in multiple types of political

parties, a trade union or professional association, a church or other religious organization, a

sports/ leisure/ cultural group, and another voluntary association to examine individuals' network

intensiveness in relation to various policy attitudes. The intensiveness of social networks was

measured in four different degrees of involvement: 1 'have never belonged to it', 2 'used to

belong but do not any more', 3 'belong but don't actively participate', and 4 'belong and actively

participate' (See Appendix A. 1.). Empirically, different types of networks were highly

correspondent to each other based on Cronbach's Alpha reliability Score2 (.922) with a single

dimension of factor component loading (>.854) (See Appendix A. 1.). Therefore, regardless of

the differences in various associations, individuals who were involved in any social network at

the degree of 4 'belong and actively participate' were coded as a group of individuals with high

network intensiveness; while individuals who were involved in any network at any degree of 1

'have never belonged to it', 2 'used to belong but do not any more', or 3 'belong but don't

actively participate' were coded as a group of individuals with low network intensiveness.

Furthermore, in order to observe attitudinal differences between individuals who were active in

only one type of social network and those who were active in multiple networks, I created



SCronbach's Alpha reliability score indicates a coefficient of consistency among different variables. High
Cronbach' s alpha reliability refers to how well various different items can be constructed into a single
unidimensional scale. A reliability coefficient of .70 or higher is considered "acceptable" in most social science
research (http://www.ats. ucla. edu/STAT/SP SS/faq/alpha.html).

3 Factor analysis is an interdependence test technique. Among multiple factor rotation methods, 'Oblique principle
components analysis' that computational strategies have been developed to rotate factors so as to best represent
"clusters" of variables, without the constraint of orthogonality of factors was adapted in order to calculate
interdependent relationships (http:.//en.wikipedia. org/wiki/Factor~analy sis,
hop11 w il i .statsoft.coml/textbook/stfacan.html).










dummy variables of counter-cases for single network intensiveness and multiple network

intensiveness.

In terms of network extensiveness, regarding sixteen different memberships in social,

cultural, religious, professional, or political associations, individuals were asked whether they

had any of those memberships. The memberships achieved a reliable level of Cronbach' s Alpha

score of .735 and a relatively homogenous factor loading (2.228) (See Appendix A.2) among

those different memberships. These categories proved to be equally important measurements in

terms of network variations, thus I used the total number of each individuals' social network

memberships as a form of network extension to see the influence of network expansiveness on

individuals' policy beliefs (See Appendix A.2). The number of memberships ranged from 0 to

16 out of total possible number of 16. These memberships exhaustively covered all possible

social, professional, cultural, and religious associations. The higher the score was, the more

extensive the individual was in their social networks. Again, for a comparison of attitudinal

differences between individuals who had single social membership and who had multiple

memberships in a regression, I created dummy variables of counter-cases for single membership

and multiple memberships.

In order to measure general social trust, I adopted three questions, 'whether people are

helpful or looking out for themselves', 'whether they are fair or try to take advantage of others',

and 'whether they can be trusted' that were asked frequently in previous research. They were

measured on an ordinal scale of 1,'not helpful', 'take advantage', or 'cannot trust', 2 'depends',

and 3 'helpful', 'fair', or 'trust' respectively. Individuals' answers to these three questions were

highly correlated each other based on Cronbach's Alpha of .66 resulting in one single dimension

of factor loading (>.735) (See Appendix A.3.). Therefore, I created a single indicator of 'general









social trust' by computing a mean score of three answers for each individual in a range of three

ordinal values, low, moderate, and high.

Measuring Public Policy Typology

My study was designed to investigate the relationships between social capital and its

effects on policy attitudes. In other words, the study investigated patterns of individuals' policy

attitudes from their social lives that have often been overlooked in previous research. Previous

scholarly works have theoretically categorized types of public policies based on their substantive

functional characteristics, targeting sectors, ideology (conservative vs. liberal), or approach

styles (good vs. bad or progressive vs. regressive). Based on policy expectations and processes,

Theodore Lowi (1964) categorized policies into distributive, redistributive, constituent, and

regulatory types. Peter Steinberger (1980) determined categories of public policy from possible

impacts: he categorized distributive, redistributive, and regulatory of policies based on

substantive impact, adaptive and control based on political impact, areal and segmental based on

scope of impact, public goods and private goods based on exhaustibility, and symbolic and

tangible based on tangibility (McCool, 1995, pp.183, 229).

Cristopher Wlezien (1995) categorized five policy areas of big cities, education,

environment, health, and welfare in measuring people's preferences for government spending

(p.985). A similar study done by William Jacoby (1994) also observed that public attitudes

toward certain types of policies such as welfare policies were qualitatively different from public

preferences toward other types of government spending. Jacoby categorized various policies

based on program-specific preference in welfare, environment, crime prevention, public schools,

science and technology, and defense (p.347). Moreover, due to some ambiguity of policy

categorizations, some scholars have used a methodological approach to categorize various policy










types using factor analyses (Letki, 2004). Each categorization seems to have its own logical

rationale to understanding dimension of public policy issues.

My study explained how individuals' social connectedness influenced their attitudes

toward various types of policies in particular. Therefore, based on attitude relevance of various

policies that are more likely to be activated by individuals' social lives, but different political

attributes that were discussed in previous policy typology studies, the study categorized various

types of policy attitudes into three areas of 'redistributive policies' that are related to the social

equality and benevolence for the have-nots, 'government activism' that are relevant to the

collective public reciprocity, and 'morality policies' that deal with attitudes toward government

regulations on socially controversial issues (See Appendix B).

In an empirical process of sorting multiple policy attitude indicators by each category of

public policies, my study conducted multiple scaling tests to create a reliable indicator for each

type of policy attitude beyond theoretical considerations. Before running any reliability tests, I

rescaled all possible policy attitude indicators on a seven point scale to make them more

consistent numerically. For redistributive policy attitude measurement, I ran reliability tests on

attitudes toward government responsibility on reducing income difference between the rich and

the poor, improving standard of living for the poor Americans, and helping paying for medical

care (See Appendix B. 1.). The three items achieved a relatively high Cronbach's Alpha score

(.674) and have higher factor loading components on a single dimension (>.740) (See Appendix

B. 1.). Therefore, I averaged the three items on a scale of 7 from 'Government should not/ people

should help themselves' to 'Government should help' and created a single index of redistributive

policy attitudes. The higher scores indicated more supportive attitudes toward redistributive

government policies.









For the government activism measurement, I also ran reliability tests on individual

attitudes toward governmental support on public good such as 'improving & protecting national

health', 'improving national education system', 'improving & protecting environment', and

'solving problems of big cities' (See Appendix B.2.). These items achieved a high Cronback' s

Alpha score of .731 and the factor components loaded as a single dimension (>.476) (See

Appendix B.2). Therefore, I again created a single index of governmentt activism' on range of 7

from 'too much spent on it/ no government activism needs to 'too little spent on it/ more

government activism needs' by averaging these four items. Higher scores indicated more

supportive attitudes for government activism.

Lastly, for the morality policy attitude measurement, I intentionally selected the most

representative and controversial morality policy issues of 'abortion' and 'gay issues'. As Jacoby

pointed out (1994, 2005), attitudes toward different policy issues are not unidimensional.

Morality policy issues are more problematic than other types of policies in Jacoby's perspectives

since they are interrelated with multiple social factors such as their ethnicity, religious beliefs,

previous life experience, and so on. Therefore, I kept morality policy attitudes toward the issues

of abortion and gay rights separate in my measurement. In order to achieve a more consistent

attitude measurement in each issue, I included multiple degrees of questions about legal

boundaries for abortion and gay rights. Attitudes toward abortion were asked in degrees of

different reasons for defects in babies, women's health, rape, poverty, an unwanted child, an

unwanted marriage, and any other reason. Attitudes toward gay rights were asked through

different aspects of questions, such as 'whether the individual would allow homosexual

relations', 'whether the individual would allow homosexuals to teach', 'whether the individual

would allow homosexual to speak', and 'whether the individual would allow books on









homosexuality in the library' (See Appendix B.3). When I ran tests on these items, abortion

items achieved a high Cronbach's Alpha score (.901) and relatively good factor loading on one

of component scale (2.584) (See Appendix B.3-1). Gay rights items also achieved a high

Cronbach's Alpha score (.793) and were loaded in one dimension (>.605) (See Appendix B.3-2).

Therefore, I was able to create two attitudinal scales on abortion and gay rights policy attitudes

on a seven point scale from 'no allowance/ government regulation' to 'allowance/ individual

choice' for morality policy. Higher scores meant more support for individual choices and lenient

government morality policies on abortion and gay rights.

Conditional Factors of Demographics

Demography is a crucial factor in individuals' shared experiences and their manner of

thinking and interpretation. Where you go and how you interact with other people often

determine who you are. Therefore, it is necessary to find a direct causation between the

following demographic factors. For instance, being a female, head of a single household, of

lower socioeconomic status, and social elements such as networks of people around the

individual, interacted in predicting a single mom's policy beliefs and preferences. Hero (2003)

presented ethnicity as the core demographic factor in relation to general social trust,

Hetherington (2001) discussed ethnicity and socioeconomic status as it related to policy

perceptions, and Jacoby (2005) had considered party identification as an important interacting

factor in attitudes toward government spending in multiple types of policies in his series of

related studies.

Classical demographic variables in political and social studies, such as party

identification, gender, education level, age, income, ethnicity, religiosity and geographical

locations were controlled or used as conditional factors in the main analyses. Party identification

was coded on a seven point scale from strong Democrats, weak Democrats, Independents near









Democrats, Independents, Independents near Republicans, weak Republicans, to strong

Republicans. Republicans recorded higher values in party identification. Ethnicity was

categorized into two categories, the majority (value 'O') and the minority (value '1'). White

people were coded as an ethnic maj ority and ethnic minorities were comprised of all Asians,

Blacks, Hispanics, Indians, and other mixed racial groups. Religiosity was categorized in an

ordinal manner of 'not religious', 'not very religious', 'somewhat religious', and 'strongly

religious'. Thus, higher values in religion indicated stronger religiosity. Income was coded in

ordinal values of 12 from income less than 1,000 (1) to more than 25,000 (12). The raw numbers

of years of education and age were used in numeric scales in predicting policy attitudes.

However, numeric variables of education, age, and income were recorded in ordinal scales for

descriptive analyses in order to see them conveniently in the preliminary stage of the analyses

(See the values in Tables 5-5, 5-7, & 5-13).

In terms of geopolitical categorizations, I used the rationales of political sociologists'

assumptions on regional variety within the large scale of the U.S. Regional characteristics have

been accumulated over time through all political, economic, and cultural experiences and assets.

Overall, New England and Mid Atlantic areas are areas with a high concentration of industries

and have higher levels of academic circumstance; the South has a slower pace of life but strong

southern identity under warmer weather and more retirees; the Midwest is a more diverse

cultural and political intersection; the Southwest is more likely to be dominated by Mexican

cultural heritage with less resources; and the West is culturally very diverse, thus tends to be

more tolerant (Clack, Targonski, and Morgan, 1997). My study assumed that these different

regional circumstances were reflected in individuals' policy attitudes.










The regions were categorized into nine different groups of 'New England', 'Middle

Atlantic', 'Eastern North Central', 'West North Central', 'South Atlantic', 'East South Central',

'West South Central', 'Mountain', and 'Pacific'. This categorization has been used continuously

in previous research such as NES or GSS time series panel data, thus I adopted it into my study.

There were obvious similarities among states within and differences between states that belonged

to different geographical categories. In order to control the regional variance of social capital in

predicting individuals' political attitudes, I assigned Putnam's social capital index4 to each state

and averaged states' scores within each region of New England, Middle Atlantic, East North

Central, West North Central, South Atlantic, East South Central, and West South Central,

Mountain, and Pacific Based on these scores, I created a dummy variable of regions with low

social capital in order to see a statistical difference between those regions and regions with high

social capital. Regions with high social capital included New England, North West Central and

Mountain, and the rest of regions were coded as a low social capital region. The dichotomous

region variable was incorporated into regression analyses as a control variable.





4 Using 14 different indicators of 1)Number of club meetings attended last year, 2)Number of community projects
worked on last year, 3) Number of times entertained in home last year, 4) Number of time volunteered last year, 5)
Mean response to "I spend a lot of time with friends, 6) Mean state response to "most people are honest", 7) Mean
percent that served on local committee in past year, 8) Mean percent that served as officer of club or organization, 9)
Mean percent that attended meeting on town or school affairs, 10) Mean number of nonprofits per capital, 11) Mean
number of group membership, 12) Mean response to "most people can be trusted", 13) civic and social organization
per 1000 people 1977-1992, 14) Mean presidential turnout 1988 and 1992, the index was created by the average of
the standardized scores. The scores are identical to the factor scores from a principal components analysis of the 14
component variables (Putnam, 2000, p.487)

5 New England is comprised of Maine, Vermont, New Hampshire, Massachusetts, Connecticut, and Rhode Island:
Middle Atlantic is comprised of New York, New Jersey, and Pennsylvania; East North Central is comprised of
Wisconsin, Illinois, Indiana, Michigan, and Ohio: West North Central is comprised of Minnesota, Iowa Missouri,
North Dakota, South Dakota, Nebraska, and Kansas: South Atlantic is comprised of Delaware, Maryland, West
Virginia, Virginia, North Carolina, South Carolina, Georgia, Florida, and District of Columbia; East South Central is
comprised of Kentucky, Tennessee, Alabama, and Mississippi: West South Central is comprised of Arkansas,
Oklahoma, Louisiana, Texas: Mountain is comprised of Montana, Idaho, Wyoming, Nevada, Utah, Colorado,
Arizona, and New Mexico; and Pacific is comprised of Washington, Oregon, California, Alaska, and Hawaii.









In addition, to observe the varying influences of regional social capital on policy attitudes,

I created another dichotomous variable of high and low social capital regions using only six

regions, and excluding the three other regions in the middle range of social capital, according to

Putnam's social capital index. Again, New England, West North Central, and Mountain were

categorized as a high social capital region; South Atlantic, East South Central, and West South

Central were coded as a low social capital region; and East North Central, Middle Atlantic, and

Pacific were excluded in order to observe the conditional effect of high and low regional social

capital more clearly.

Analyses

The study reported three sets of analyses. In a preliminary analyses, I measured the

correlation between demographic factors and social capital to see how those demographic

variables were related to individuals' social connectedness and then controlled them to see a

whether there were clear interactions between social capital and policy beliefs.

In the second set of analyses, the study considered how the dimensions of social capital

related with one another by summarizing general patterns of social capital and describing

interrelations among the patterns.

In the third set of analyses, the study measured the impacts of social capital on policy

attitudes at both the individual and under conditional regional levels of low and high social

capital. In this stage, I intended to construct solid patterns of different aspects of social capital in

predicting different policy attitudes. After identifying three different types of policy attitudes in

'government activism', 'redistributive policy', and 'morality policy', I examined patterns of

individuals' attitudes towards these three types of public policy attitudes using different aspects

of social network and general social trust, controlling for other demographic factors. Therefore,

the model equations can be written like these:









* Model 1: Y governmet activism I +Ptrust + P2Single extensiveness + P3multiple
extensiveness + P4Single intensiveness + Psmultiple intensiveness + P6partyid + p7female +
Psethinic minority + P901d + Bloeducation + plnincome + Pl2TeligiOsity + Pl3TegiOnal social
capital

* Model 2: Y redistributive policies 1 +ptrst + P2Single extensiveness + P3multiple
extensiveness + P4Single intensiveness + Psmultiple intensiveness + P6partyid + p7female +
Psethinic minority + P901d + Bloeducation + plnincome + Pl2TeligiOsity + Pl3TegiOnal social
capital

Model 3: Y morality: abortion= 1 trust + P2Single extensiveness + P3multiple extensiveness +
P4Single intensiveness + Psmultiple intensiveness + P6partyid + p7female + Psethinic
minority + P901d + Bloeducation + plnincome + Pl2TeligiOsity + Pl3TegiOnal social capital

* Model 4: Y morality: gay rights' a I Ptrust + P2Single extensiveness + P3multiple extensiveness
+ P4Single intensiveness + Psmultiple intensiveness + P6partyid + p7female + Psethinic
minority + P901d + Bloeducation + plnincome + Pl2TeligiOsity + Pl3TegiOnal social capital









CHAPTER 5
RESULTS

Demographics and Social Capital

Individuals have a wide range of predisposed characteristics. Demographics are

preliminary factors that determine individuals' levels of social capital or intervene in the

interaction between individuals' social capital and policy attitudes or preference, thus

demographics need to be taken into consideration and at least be controlled for in order to

understand the dynamics of social capital and policy attitudes. In my sample, the mean age is

45.96 year old, and average level of education is between high school and college. 34% are

Democrats, 36% are Independents, and 30% are Republicans. About 80% are the White people

and the remaining 20 % are a mixture of ethnic minorities such as Blacks, Asians, Hispanics,

Natives, and other minority groups. 46% of participants are males and 54% are females. The

sample was equally gathered across different geographical regions.

Overall, Republicans, older adults, more educated, more religious, ethnic majority

members (the White) and females have higher levels of social capital than Democrats and

Independents, younger adults under the age of 30, less educated, less religious, ethnic minorities,

and males respectively; although there are some variations across different elements of social

capital in network intensiveness and extensiveness, and general social networks.

Party Identification

Political identification, one of the most influential demographic factors in politics, has a

strong relationship with network intensiveness (F[6, 1456]=14.069 p<.001) and extensiveness

(F[6, 1458]=3.972 p<.001) and the level of general social trust (F[6, 862]=2.554, p<.019).

Republicans (M=1.64, SD=. 1.25) tend to engage more intensively in social networks than

Democrats (M=1.29, SD=1.30) and Independents (M=0.77, SD=0.98). Again, Republicans









(M=1.98. SD=1.89) and Democrats (M=1.84, SD=1.94) are more likely to be involved in

multiple social networks than Independents (M=1.25, SD=1.85). Those partisan groups of

Republicans (M=2.08, SD=0.51) and Democrats (M=2.02, SD=0.42) also tend to trust general

society and people more than Independents (M=1.94, SD=0.42). In addition, political

Independents have the highest proportions of individuals who had no activity in any network

(X2=77.003, p<.001) and no membership (X2=41.012, p<.001) among political partisans (See 5-1

& 5 -2).

In short, partisanship reflects social capital in two ways. Although social capital is a little

more prevalent among Republicans than Democrats, strength of partisanship was a stronger

influence in individuals' social capital than the direction of party identification. In other words,

individuals who have strong partisanship tend to be more intensively involved in multiple social

networks with higher levels of trust than people who have no or lower levels of partisanship

(Tables 5-1 & 5-2).

Gender

Although gender does not have any relevance with network extensiveness and

intensiveness, it influences levels of general social trust (F [1, 867]=5.083, p<.001). Females

(M=2.05, SD=0.45) are more likely to trust the general public than males (M=1.98, SD=0.47)

(Tables 5-3 & 5-4)

Age

In terms of age, overall older adults over 30 year old more intensively (F [1, 1461]

= 24. 148, p<.001) participate in various types of social memberships (F [1, 1463]=10. 106,

p<.002), and have higher levels of general social trust (F[1, 867]=24.990, p<.001) than young

adults. About 32% of older adults are more strongly engaged in multiple social networks while

only 19% of young adults are intensively involved in multiple social gatherings (X2=24.728,









p<.001). About 42% of old adults have multiple memberships, but only 32 % of young adults

have more than one membership (X2=8.551, p<.014) (Tables 5-5 & 5-6).

Education

More educated individuals tend to participate in social networks more intensively (F [4,

1458]=43.893, p<.001) and extensively (F [4, 1460]=51.546, p<.001), and have higher levels of

general social trust (F[4, 863]=6.432, p<.001) than people who have lower levels of education.

About 58% of graduate level individuals are intensively involved in multiple social networks

while only 1 1% of middle school graduates have similar levels of network intensiveness

(X2=180. 147, p<.001). In addition, more than 71% of individuals above the graduate level

belong to multiple social memberships, but only 16% of people who obtain middle school

education have more than one social membership (X2=166.608, p<.001) (Tables 5-7 & 5-8).

Ethnicity

Ethnic maj orities are more likely to have higher levels of general social trust (F[1,

867]=21.258 p<.001) compared to ethnic minorities that encompass Hispanics, Asians, Blacks,

and other original and mixed ethnic groups. Moreover, White people tend to participate more

intensively (F [1, 1461]=20.310, p<.001) and broadly (F [1, 1463]=3.500, p<.062) in social

networks than ethnic minorities (Tables 5-9 & 5-10).

Religiosity

Religious strength also shows a strong relationship with various social capital elements.

For instance, individuals who are very religious tend to be intensively involved in social

networks (F [3, 1459]=44.652, p<.001) in more extensive ways (F [3, 1461]=20.218, p<.001)

than less religious individuals. However, there is no difference in general social trust among

individuals with various degrees of religiosity (Tables 5-11 & 5-12).









Income

Income has also partial influence on social capital. Although it does not have any

statistical significance in network extensiveness and general social trust, higher income people

tend to engage more intensively in social networks than low income people (F [2, 891]=6.417,

p<.002). The proportion of individuals who are not active in any social network is the highest

among people who have a yearly income lower than $5,000 (X2=14.665, p<.005). The

proportions of people who intensively engages in multiple social network (34%) and multiple

social memberships (43%) are much higher for high income people than lower income people

(X"=10.670, p<.031) (Tables 5-13 & 5-14)

Region

Different geographical regions have different levels of social capital. For instance,

overall the mountain region, including such states as Nevada, Arizona, and New Mexico, has

more network intensiveness (F [8, 1462]=2.440, p<.013) and extensiveness (F [8, 1456]=1.896,

p<.057) and higher levels of general social trust (F [8, 860]=1.754, p<.083) than other

geopolitical regions, especially compared to the deep South states of Tennessee, Alabama, and

Mississippi (Tables 5-15 & 5-16). These regional variances in social connectedness are well

supported by previous research such as Clack, Targonski, and Morgan's argument on Southern

conservatives, Midwest liberalisms, and Western mellowness (1997).

Dimension of Social Capital

Overall, each individual has different levels of social capital. When analyzing network

intensiveness and extensiveness, survey participants were spread out across multiple levels of

networks. In network intensiveness, about 39% of people are never intensively involved in any

of social organizations, associations, or informal gathering. However, about 3 1% of people say

that they are intensively involved in a single social network and 30% of others report that they









are intensively involved in at least two different social groups. The mean of network

intensiveness for each individual is .908 (SD=.823). It infers that the average individual tends to

be socially active at least in one type of social networks although the extent of this activity seems

somewhat limited (Table 5-17).

In terms of network extensiveness, average people are members of at least one social group

(M=1.018, SD=.881) although there are some variations in types of social networks. About 38%

of participants have no social membership at all, 22% of people have a single membership, and

other 40% have at least two different memberships. Among various types of memberships, 3 1%

of valid participants belong to a church group, 17% of them belong to sports clubs, 15% belong

to professional society, 14% in school service, 11% in hobby clubs and art groups, and the rest of

the memberships, such as youth group (10.3%), service groups (10%), labor union (9.6%),

fraternal group (6.8%), veteran group (5.3%), political club (4.3%) are occupied by 5 10% of

participants. A very small portion of people belong to farm organizations (3%) or a nationality

group (2.7%). In sum, individuals seem to participate in different types of social gathering at

various levels (Table 5-17).

For the measurement of general social trust, when the survey asked participants how much

people could be trusted, helpful, and fair; most of them say that it depends (M=2.02, SD=.463).

Only 4% of the people have a mean score of 1.5 (between '1. not trust' and '2. depends'), people

who fall between the mean scores of 1.5 and 2.5 (near 'depends') are comprised of more than

71% of the sample, and people who are above the mean score of 2.5 (between '2. depends' and

'3. trust') are 25% of the sample. Therefore, we can infer that majority of individuals have at

least a moderate level of general social trust (Table 5-17).









Correlations between Different Dimensions of Social Capital

As expected, there are strong correlations among different tenets of social capital.

According to the Pearson correlation tests, individuals who are intensively involved in at least

one social network are more likely to have multiple social memberships (r-.717, p<.001). In

other words, network intensiveness and extensiveness are highly correlated. However, general

social trust is negatively correlated with being intensive (r- -.362, p<.001) in multiple types of

social networks (r- -.339, p<.001) (Table 5-18).

When explored more deeply, general social trust is more negatively related to multiple

memberships (r- -.325, p<.001) rather than to a single membership (r= -.232, p<.001). In other

words, individuals who distrust other members of a society tend to belong to loose multiple

social networks rather than a single social gathering. In addition, individuals who are intensively

involved in a single social network tend not to intensively engage in other social networks (r- -

.190, p<.001), but tend to have at least one (r=.289, p<.001) or more (r-. 165, p<.001) social

memberships. Moreover, individuals who have any type of single membership are less likely to

have other memberships (r= -186, p<.001). In other words, we can infer that as long as an

individual has a single membership, he or she is less likely to obtain another membership (Table

5-19).

Among the different memberships, individuals who have a religious membership (r=.476,

p<.001) are more likely to be intensively involved in multiple social networks, but people who

belong to veteran groups are more like to be intensive only within the group, compared to other

types of social memberships (r=. 118, p<.001).

Therefore, we can conclude that individuals who participate in any social network

intensively are more likely have any type of social membership. However, people who are

intensively involved in a single social network tend not to extend their social networks. In










addition, individuals who do not trust people of the general public are more likely to have

multiple social memberships and tend to be intensively involved in those social networks. This

can be interpreted in that people, who do not trust acquaintances, still have a secondary group of

people with whom to share certain hobbies and norms within organizations. This finding is

somewhat contradictory with Putnam's argument that "people who trust their fellow citizens

volunteer more often..., [and] participate more often in politics and community organizations"

(Putnam, 2000, p.136-37). However, as Putnam made points in his later discussion, the levels of

trust on general public that are caught by such question, 'whether people can be trusted' are 'thin

trust', thus the level of trust can be changeable and different from solid sense of community

(Putnam, 2000, p.137). Therefore, thin trust on general public could create more desire for

secondary networks that are loose but still face-to-face interaction and share certain disciplines

among members.

Social Capital and Policy Attitudes6

On Redistributive policy

Certain demographic factors, such as party identification, religiosity, education, and

ethnicity influence individuals' redistributive policy attitudes. As expected, conservative

Republicans are less likely to support redistributive types of government policies that primarily

help the poor and socially disadvantage people (t= -10.042, p1.001). However, although the


significance are relatively low, ethnic minorities (t=1.847, p1.065) and less educated people (t=



6 For multiple regressions, I checked multicollinearity between different elements of social capital using VIF
(Variation Inflation Factor). In the full model, VIF scores for single membership, multiple memberships, single
intensiveness, multiple intensiveness, and general social trust are between 1.032 and 2.261. The values above 1
indicate that there are multicollinearity effects. Therefore, I ran multiple regressions separately for each network
intensiveness, extensiveness, and social capital with demographic factors. However, the statistical significance for
each element of social capital is still identical with the full models. As a result, I still reports the full models.










-1.911, p1.056) who often get more benefits out of such policies are more likely to support


redistributive policies compared to ethnic majorities and highly educated individuals. A negative

coefficient on religiosity means that the more religious people are less likely to support

redistributive government policies (t= -2.504, p1.012). It can be interpreted that benevolent


religiosity relies on God's will, thus those individuals are less likely to rely on the government

for help with the disadvantaged. Overall, there is more support for government redistributive

policies among social minorities, such as ethnic minorities and less educated people, and socially

liberal Democrats, while gender, age, income, and regional variation have no independent

statistical effects (Table 5-20)

Controlling for demographic factors, such as party identification, religiosity, gender, age,

education, income, ethnicity, and regional differences, certain dimensions of social capital

influence individuals' redistributive policy attitudes. As this research predicted, individuals who

have higher levels of general social trust are more supportive of government redistributive

policies than people with lower levels of general social trust (t=5.103, p1.001). However,


network intensiveness (t= -.905, p1.366) and extensiveness (t= -.460, p1.646) do not determine


redistributive policy attitudes. In other words, the factor of how intensively and broadly

individuals participate in social networks has no effect on redistributive policy preferences

(Table 5-20).

Model 1: Y redistributive policy 4.687 +0. 164trust -0.074single extensiveness -0.03 multiple
extensiveness +0.035Ssingle intensiveness -0.081Imultipel intensiveness -0. 117partyid +
0.061female +0.110~ethinic minority 0.003old -0.016education + 0.005income -0.053religiosity
+ 0.080region









On Government Actions

Again, some demographic factors influence individuals' policy attitudes toward

government activism that intends to improve national health, education, environment, and big

city conditions. As expected, Republicans are least supportive of government activism (t= -

5.252, p1.001). However, individuals earning higher incomes who would have the financial


capability to partake in various types social responsibilities are more likely to support

government activism (t=2.393, p1.017), ceteris paribus (Table 5-21).


After controlling for demographic factors, general social trust (t= -.839, p1.402), network


extensiveness (t=. 103, p1.918), and network intensiveness (t= -. 173, p1.862) have no statistical


significance on government activism attitudes (Table 5-21). Insignificant results could be

caused by methodological errors or theoretical misunderstanding. When conducted

multicollinearity tests, although minor effect (above one in VIF) of multicollinearity is detected,

a model with a single indicator of social trust still does not have any statistical significance;

therefore, multicollinearity is not the cause of statistical insignificance. Theoretically, some

argue about the broad concept of government activism. The beneficiaries and the consequences

of such policies are often random and not specified. As a result, the connection between social

capital and the particular policy attitudes could be somewhat blurry and vague (McCool, 1995,

pp.210-17).

Model 2: Y govemment ativism= 4.924 -0.034trust +0. 102single extensiveness -0.011multiple
extensiveness -0.085single intensiveness -0.020multipel intensiveness -0.078partyid +
0.096female +0.058ethinic minority 0.003old -0.002education + 0.025income -0.005religiosity
+ 0.008region










On Morality Policy

As we discussed in the method chapter, morality issues vary in terms of concepts,

approaches, and solutions. Therefore, different types of morality issues, such as abortion and

gay rights, have different political implications. For instance, among various demographic

factors, party identification still has strong influences on abortion attitudes, but not on gay rights

issues. Conservative Republicans are supportive of stronger government regulations on abortion


(t=-.069, p1.010), but the tendency is faded way on gay rights issues (t = -.010, p 1.728). In


contrasts, older adults are more likely to be generous particularly on abortion issues (t=2.713, pi


.007), but not on gay rights (t=-.368, p 1.713). Overall, more educated (t=6.070, t=7.430, pi


.001) and higher income people (t=2.405, t=2.446, p1.015) are more likely to allow women's


freedom of decision on abortion and gay rights, and are thus supportive of minimum

governmental regulations on those issues. (Tables 5-22 & 5-23)

As predicted, after controlling for demographic factors, individuals who belong to a single

social association or organization (t= -7.695, t= -8.797, p1.001) have supportive attitudes for


government regulations on both abortion and gay rights. In addition, people who are intensively

involved in such a single social network (t= -6.976,t= -8.430, p1.001) tend to support


government regulations on both issues. Based on this result, we can infer that limited social

networks narrow peoples' views on difference and diversity, and thus tend to diminish social

tolerance.










However, unlikely my study predicted, individuals who belong to multiple social

memberships (t= -7.279, t= -8.426, p1.001) and who intensively participate in those social


networks (t= -5.657, t= -6.862, p1.001) are also more likely to support government regulations


on individual choices regarding morality issues such as abortion and gay relations. In other

words, as opposed to what was predicted, there are no statistical differences between single and

multiple network intensiveness and extensiveness. Individuals who have either a single or

multiple memberships, and participate with either limited intensiveness in a single social

network or broad intensiveness, all tend to agree with tougher government control on both

abortion and gay rights, placing greater importance on social order and morality over personal

freedom (Tables 5-22 & 5-23)7. This infers that as long as individuals engage in any type of

social gathering in any manner, they seem likely to support government supervision keeping

societal order and homogeneity on morality issues.

In addition, individuals at higher levels of general social trust are partially likely to support

strong government regulations, particularly on gay issues (t= -2.260, p1.024), but not on abortion


(t= -1.141, p1.254) (Tables 5-22 & 5-23). These results reflect that policy attitudes toward


different kinds of morality issues are influenced in a variety of ways by even the same kind of

individuals' social lives and the manner in which the individuals make personal connections

(White, 2003). Thus, although individuals with a higher level of general social trust tend to hold



SThe researcher was suspicious about the tenets of particular social group, such as religious gathering, for the reason
of politically conservative views on morality issues. Therefore, the researcher re-ran multiple regressions on those
two morality issues of abortion and gay rights after excluding religious groups from the measurements of social
networks. However, the statistical significance for each element of social capital is still identical with the full
models. As a result, the researcher still reports the full models.










higher moral values on life, faith in God, and respect of tradition, the levels of support for

government control on morality issues varied depending on the type of issues considered and

different perspectives.

Model 3: Ymorality: abortion- -0.538 0.083trust 1.228single extensiveness 1.146multiple
extensiveness 1.440single intensiveness 1.381multipel intensiveness 0.070partyid +
0.025female 0. 181ethinic minority + 0.01101d + 0. 120education + 0.044income -
0.077religiosity + 0.166region

Model 4: Y morality: gayrights- -0.523 -0. 178trust -1.591single extensiveness -1.495multiple
extensiveness -1.771single intensiveness -1.717multipel intensiveness -0.011partyid +
0.037female -0.263ethinic minority + 0.001old + 0.158education + 0.049income
+0.027religiosity + 0.159region


The Regional Context and Social Capital

Regional levels of social capital at the aggregate level of states or larger political units are

a useful way to explore dynamics of political attitudes and characteristics. Using a dichotomous

variable of region that was divided according to Putnam's social capital index (2000), I looked at

the conditional effects of two, low and high, regional social capital circumstances on various

aggregated policy attitudes. In general, rich social capital regions have a higher White

population (99%) than poor social capital regions (77%) (X2 = 42.58, p<.001). Other

demographic variables such as gender, age, and religiosity, and party identification, however, do

not have statistical variations across different levels of social capital regions.

Under both high social capital regions of New England, West North Central, and Mountain

(F[12, 286]=3.948, p<.001, F[12, 286]=2.382, p<.061) and low social capital regions of South

Atlantic, East South Central, and West South Central (F[12, 613]=6.554, p<.001, F[12,

613]=1.904, p<.03 1), network intensiveness (t=.3 84, p<.701, t=.580, p<.562) and extensiveness

(t= -.496, p<.620, t=.085, p<.932) have no statistical significance in redistributive policies and

government activism attitudes. However, both network intensiveness and extensiveness induce









supportive attitudes for government regulations on morality policies such as abortion and gay

rights in both regions with high social capital (F[12, 286]=9.673, p<.001, F[12, 286]=12.097,

p<.001)and low social capital (F[12, 613]=13.095, p<.001, F[12, 613]=17.099, p<.001) (Tables

5-24 & 5-25). Therefore, regional social capital conditions do not make any statistical difference

in relationships between social networks and policy attitudes on redistributive, government

activism, and morality policies.

However, general social trust behaves differently across different policy areas under

different regional social capital circumstances. Although general social trust encourages

supportive attitudes for redistributive policies in both high (t=2.590, p<.010) and low (t=4.059,

p<.001) levels of social capital regions, it has a significant influence on government regulations

on abortion (t= -2.226, p<.027) and gay rights (t= -3.769, p<.001) only in higher social capital

regions, but not in lower social capital regions (t=.360, p<.719, t=1.121, p<.263). In other words,

a group of people who are in social capital rich regions with higher general social trust support

government regulations on morality issues, while a group of people who have higher general

social trust but are in a region with low social capital do not have particular tendencies in

morality policy attitudes (Tables 5-24 & 5-25).

Individuals in regions with either higher or lower levels of social capital present identical

policy attitudes besides a little variation in the function of general social trust on morality policy

attitudes. Compared to general social trust at the individual level that partially influences

positive attitude for government regulation on one type of morality issue, gay rights, but not on

the issue of abortion, policy attitudes become more homogeneous under a given regional levels

of social capital. For instance, in higher social capital regions, general social trust always

induces individuals' positive attitudes for government regulations on morality issues regardless









the types of different issues. In contrasts, in lower social capital regions, it has no particular

influence on any type of morality policy attitude. This finding supports theoretical arguments on

discrepancies between individuals of micro and aggregates of macro political characteristics. As

they are aggregated, political attitudes at the macro level become more orderly and seemingly

uniform (Erikson and Tedin, 2007, p.93)

Nonetheless, overall findings under different regions are consistent with the tendency in

the micro level of individuals' policy attitudes. As found in the previous section, higher social

capital at the individual level induces conservative views toward abortion and gay rights, thus

people care more about government regulations; and regional social capital circumstances do not

change such tendencies of social capital on policy attitudes at the aggregate level. Therefore, the

individual tendency is persistent at the aggregate level. This strong linear consistency with

minimal variations between two different levels of approaches helps further development of

theoretical connections of social capital dynamics across different levels of individuals and states.










Table 5-1. Party Identification and Social Capital
Demographics Network Intensiveness Network Extensiveness General Social Trust
Party Affiliations Mean (SD) Mean (SD) Mean (SD)
Strong Democrat 1.29(1.30) 1.84(1.94) 2.02(0.42)
Not Strong Democrat 0.98(1.17) 1.55(1.94) 1.97(0.44)
Independent Democrat 0.92(1.05) 1.65(1.81) 1.94(0.47)
Independent 0.77(0.98) 1.25(1.85) 1.94(0.42)
Independent Republican 0.91(1.07) 1.50(1.82) 2.06(0.47)
Not Strong Republican 1.13(1.12) 1.54(1.76) 2.09(0.50)
Strong Republican 1.64(1.25) 1.98(1.89) 2.08(0.51)
F[6, 1456]=14.069 p<.001, F[6, 1458]=3.972 p<.001, F[6, 862]=2.554, p<.019,
N=1462 N=1464 N=868

Table 5-2. Party Identification and Networks Intensiveness and Extensiveness
No Single Multiple No Single Multiple


Demographics
Party Affiliations
Strong Democrat
Not Strong Democrat
Independent Democrat
Independent
Independent
Republican
Not Strong Republican
Strong Republican


Intensiveness Intensiveness Intensiveness
% % %


Membership


Membership


Memberships

45.82
35.55
45.80
29.14


33.86
44.31
45.38
50.18

45.24
35.71
18.69
X2=77.003, p<.001


31.08
30.59
29.23
30.32

30.95
33.33
34.58


35.06
25.10
25.38
19.49

23.81
30.95
46.73


33.07
41.02
35.88
49.28

37.60
37.62
26.64
X2=41.012, p<.001


21.12
23.44
18.32
21.58

28.00
21.90
23.83


34.40
40.48
49.53































1.29 (1.79)
1.68(1.90)
F [1, 1463]=10.106, p<.002,
N=1464


1.85(0.40)
2.05(0.47)
F[1, 867]=24.990, p<.001,
N=868


Demographics Network Intensiveness Network Extensiveness General Social Trust
Age Mean (SD) Mean (SD) Mean (SD)


Table 5-3. Gender and Social Capital
Demographics Network Intensiveness
Gender Mean (SD)


Male
Female


Network Extensiveness
Mean (SD)


General Social Trust
Mean (SD)


1.08 (1.19) 1.67 (1.92) 1.98 (0.47)
1.11 (1.17) 1.56 (1.85) 2.05 (0.45)
F [1,1461]=0.235, p<.628, N=1462 F [1, 1463]=1.067, p<.302, N=1464 F[1, 867]=5.083, p<.001, N=868


Table 5-4. Gender and Network Intensiveness and Extensiveness
No Single M/
Demographics Intensiveness Intensiveness In


% ;


multiple
Itensiveness

29.80
29.56


No
Membership

37.06
38.55
X"=.389, p<.823


Single
Membership


Multiple
Memberships

40.43
39.04


Gender
Male
Female


40.09
37.81
X2=1.226, p<.542


30.11
32.64


22.51
22.41


Table 5-5. Age and Social Capital


0.79(1.01)
1.17(1.20)
F [1, 1461]=24.148, p<.001,
N=1462


Less than 30 Years Old
More than 30 Years Old


00
O










Table 5-6. Age and Network Intensiveness and Extensiveness
No Single Multiple No Single Multiple
Demographics Intensiveness Intensiveness Intensiveness Membership Membership Memberships
Age % % % % % %
Less than 30 Years Old 50.18 30.82 19.00 43.53 24.46 32.01
More than 30 Years
Old 36.15 31.67 32.18 36.56 21.99 41.45
X =24.728, p<.001 X =8.551, p<.014

Table 5-7. Education and Social Capital
Demographics Network Intensiveness Network Extensiveness General Social Trust
Education Mean (SD) Mean (SD) Mean (SD)


Middle School
High School
Junior College
Bachelor
Graduate


0.53(0.88)
0.92(1.06)
1.28(1.14)
1.49(1.24)
1.87(1.34)
F[4, 1458]=43.893, p<.001,
N=1462


0.74(1.29)
1.27(1.61)
1.69(1.87)
2.36(2.14)
2.92(2.09)
F [4, 1460]=51.546, p<.001,
N=1464


1.94(0.44)
1.97(0.45)
1.98(0.47)
2.09(0.48)
2.21(0.47)
F[4, 863]=6.432, p<.001,
N=867


Table 5-8. Education and Network Intensiveness and Extensiveness


Single
Intensiveness


Multiple
Intensiveness

10.53
21.83
34.23
46.48
57.93


Single
Membership


Multiple
Memb ership s

16.93
32.83
41.96
55.44
71.03


No
Intensiveness


No
Membership


Demographics
Education
Middle School
High School
Junior College
Bachelor
Graduate


63.68
42.84
27.93
26.06
19.31
X2=180.147, p<.001


25.79
35.33
37.84
27.46
22.76


62.43
42.78
33.04
23.51
13.10
X"=166.608, p<.001


20.63
24.39
25.00
21.05
15.86













Minority 0.83 (1.06) 1.43 (2.00) 1.87(0.35)
Maj ority 1 .17 (1 .20) 1.66 (1.17) 2.05(0.48)
F [1, 1461]=20.310, p<.001, F[1, 1463]=3.500, p<.062, F[1, 867]=21.258 p<.001,
N=1462 N=1464 N=868

Table 5-10. Ethnicity and Network Intensiveness and Extensiveness
No Single Multiple No Single Multiple
Demographics Intensiveness Intensiveness Intensiveness Membership Membership Memberships
Ethnicity Status % % % % % %
Minority 46.77 35.48 17.74 43.87 23.55 32.58
Maj ority 36.69 30.44 32.87 36.28 22.16 41.56


Table 5-9. Ethnicity and Social Capital
Demographics Network Intensiveness
Ethnicity Status Mean (SD)


Network Extensiveness
Mean (SD)


General Social Trust
Mean (SD)


X2=8.896, p<.012


X2=27.224, p<.001


Table 5-11. Religiosity and Social Capital
Demographics Network Intensiveness
Religious Strength Mean (SD)
Not Religious 0.64 (0.94)
Not Very Religious 0.85 (1.09)
Somewhat Religious 11 11)
Strongly Religious 1.49 (1.21)
F [3, 1459]=44.652, p<.001,
N=1462


Network Extensiveness
Mean (SD)
1.14 (1.66)
1.37 (1.71)
1.40 (1.73)
2.07 (2.05)
F [3, 1461]=20.218, p<.001,
N=1464


General Social Trust
Mean (SD)
1.96 (0.41)
2.03 (0.48)
2.08 (0.44)
2.00 (0.47)
F [3, 865]=1.243, p<.293,
N=868










Table 5-12. Religiosity and Network Intensiveness and Extensiveness
No Single Multiple No Single Multiple
Demographics Intensiveness Intensiveness Intensiveness Membership Membership Memberships
Religious Strength % % % % % %
Not Religious 59.91 22.91 17.18 49.12 24.12 26.75
Not Very Religious 51.16 25.19 23.64 42.05 24.22 33.72
Somewhat Religious 31.54 39.60 28.86 44.97 16.78 38.26
Strongly Religious 21.19 38.53 40.28 27.80 21.68 50.52
X2=157.838, p<.001 X2=61.862, p<.001

Table 5-13. Income and Social Capital
Demographics Network Intensiveness Network Extensiveness General Social Trust
Income Mean (SD) Mean (SD) Mean (SD)
Less than 4,999 0.87 (1.10) 1.49 (1.91) 1.92 (0.43)
Between 5,000-9,999 0.76 (0.92) 1.24 (1.70) 1.93 (0.43)
More than 10,000 1.22 (1.22) 1.76 (1.95) 2.04 (0.47)
F [2, 891]=6.417, p<.002, F [2, 893]=2.503, p<.082, F[2, 514]=1.934, p<. 146,
N= 893 N= 895 N= 86 8


Table 5-14. Income and Network Intensiveness and Extensiveness
Single M
Demographics No Intensiveness Intensiveness I


multiplee
ntensiveness


No Single
Membership Membership
% %


Multiple
Memberships


Income
Less than 4,999
Between 5,000-9,999
More than 10,000


48.05
47.46
35.22
X" 14.665, p<.005


32.47
35.59
30.47


19.48
16.95
34.30


40.26
51.72
33.38
X -10.670, p<.031


27.27
17.24
23.65


32.47
31.03
42.97










al Capital
Network Intensiveness
Mean (SD)


Table 5-15. Region and Soci
Demographics
Region
New England
Middle Atlantic
East North Central
West North Central
South Atlantic
East South Central
West South Central
Mountain
Pacific


Network Extensiveness
Mean (SD)


General Social Trust
Mean (SD)
2.02 (0.52)
2.03 (0.49)
2.07 (0.46)
2.06 (0.46)
1.94 (0.43)
2.06 (0.48)
1.93 (0.43)
2.11 (0.48)
1.99 (0.47)
F[8, 860]=1.754, p<.083,
N=868


1.00 (1.00) 1.70 (1.98)
1.27 (1.23) 1.72 (1.91)
1.10 1.17)1.58 (1.78)
1.15 (1.25) 1.72 (1.82)
1.16 (1.20) 1.52 (1.86)
1.18 1.18)1.76 (1.97)
0.81 (1.02) 1.19 (1.98)
1.24 (1.24) 2.01 (1.85)
0.98 (1.14) 1.69 (1.86)
F=[8, 1456]=1.896, p<.057,
F[8, 1462]=2.440, p<.013, N=1462 N=1464


Table 5-16. Region and Network Intensiveness and Extensiveness


Single
Intensiveness

37.21
25.13
32.59
35.05
37.26
32.53
30.43
24.49
28.16


Multiple
Intensiveness

25.58
38.74
29.26
27.84
28.98
33.73
19.88
38.78
26.21


Single
Membership


Multiple
Memberships

44.19
43.46
42.01
41.84
35.35
43.37
25.47
46.94
43.75


No
Membership


Demographics
Region
New England
Middle Atlantic
East North Central
West North Central
South Atlantic
East South Central
West South Central
Mountain
Pacific


Intensiveness

37.21
36.13
38.15
37.11
33.76
33.73
49.69
36.73
45.63
X"=34.589, p<.005


39.53
34.03
39.78
32.65
38.54
34.94
54.66
24.49
34.62
X2=40.041, p<.001


16.28
22.51
18.22
25.51
26.11
21.69
19.88
28.57
21.63












Table 5-17. Descriptive Social Capital
Dimensions of Social Capital
Network Intensiveness
Not active in any network
Active in single network
Active in multiple networks
Network Extensiveness
No membership
Single membership
Multiple memberships
General Trust
Low trust
Moderate trust
High trust

Table 5-18. Correlations of Social Capital


Mean(SD)


Percentage (%)


0.908 (.823)


1463
568
461
434
1465
555
329
581
869
36
618
215


38.82
31.51
29.67

37.88
22.46
39.66

4.14
71.12
24.74


Network Intensiveness Network Extensiveness


General Social Trust


Network Intensiveness 1.000
Network Extensiveness 0.717***
General Social Trust -0.362***
***You need to define what your asterisks mean underneath each table


1.000
-0.339*** 1.000


1.018 (.881)



2.012 (.463)














SinglelIntensiveness 1.000
MultiplelIntensiveness -0.190*** 1.000
Single membership 0.289*** 0.049*** 1.000
Multiple memberships 0.165*** 0.592*** -0.186*** 1.000
General social trust -0.282*** -0.273*** -0.232*** -0.325*** 1.000

Table 5-20. Social Capital and Redistributive Policy Attitudes
Redistributive Policy
Coef. t sig.


Table 5-19. Correlations of Network Intensiveness, Extensiveness, and General Social Trust
Single Multiple Single


Multiple
Memberships


General Social
Trust


Intensiveness


Intensiveness


Membership


Constant
Party Identif ication
Ethnic Minority
Religiosity
Female
Age
Education
Income
Region High in Social Capital
Single Network Intensiveness
Multiple Network Intensiveness
Single Membership Extensiveness
Multiple Membership Extensiveness
General Social Trust
F [13 1669 =13.949, p.001, R2=0.098, N=1682, *** <.01, ** <.05,

4.687
-0.117
0.110
-0.053
0.061
-0.003
-0.016
0.005
0.080
0.035
0.081
-0.074
-0.038
0.164


29.071
-10.042
1.847
-2.504
1.303
-1.682
-1.911
0.554
1.334
0.459
0.905
-0.905
-0.460
5.103


0.000
0.000
0.065
0.012
0.193
0.093
0.056
0.579
0.182
0.646
0.366
0.365
0.646
0.000










Table 5-21. Social Capital and Government Activism Attitudes
Government Activism
Coef. t sig.
Constant 4.924 24.106 0.000
Party Identification -0.078 -5.252 0.000
Ethnic Minority 0.058 0.766 0.444
Religiosity -0.005 -0.193 0.847
Female 0.096 1.628 0.104
Age -0.003 -1.147 0.252
Education -0.002 -0.173 0.863
Income 0.025 2.393 0.017
Region High in Social Capital 0.008 0.110 0.913
Single Network Intensiveness -0.085 -0.876 0.381
Multiple Network Intensiveness -0.020 -0.173 0.862
Single Membership Extensiveness 0.102 0.988 0.323
Multiple Membership Extensiveness 0.011 0.103 0.918
00 General Social Trust -0.034 -0.839 0.402
F[13.1669]=3.606, p<.001, R2=0.027, N=1682, ***p<.01, **p<.05, p<.10










Table 5-22. Social Capital and Attitudes toward Abortion
Morality Policy: Abortion
Coef. t sig
Constant 0.048 0.130 0.897
Party Identification -0.069 -2.583 0.010
Ethnic Minority -0.167 -1.225 0.221
Religiosity -0.082 -1.696 0.090
Female 0.029 0.276 0.782
Age 0.011 2.713 0.007
Education 0.120 6.070 0.000
Income 0.046 2.405 0.016
Region High in Social Capital 0.295 2.142 0.032
Single Network Intensiveness -1.227 -6.976 0.000
Multiple Network Intensiveness -1.156 -5.657 0.000
Single Membership Extensiveness -1.434 -7.695 0.000
Multiple Membership Extensiveness -1.368 -7.279 0.000
00 General Social Trust -0.084 -1.141 0.254
00 F [13.1669 =37.427, p.001, R =0.226, N=1682, *** <.01, ** <.05, <.10










Table 5-23. Social Capital and Attitudes toward Gay Rights
Morality Policy: Gay Right
Coef. t sig
Constant 0.060 0.152 0.879
Party Identification -0.010 -0.348 0.728
Ethnic Minority -0.258 -1.761 0.078
Religiosity 0.023 0.444 0.657
Female 0.040 0.351 0.726
Age 0.002 0.368 0.713
Education 0.158 7.430 0.000
Income 0.050 2.446 0.015
Region High in Social Capital 0.218 1.472 0.141
Single Network Intensiveness -1.594 -8.430 0.000
Multiple Network Intensiveness -1.508 -6.862 0.000
Single Membership Extensiveness -1.763 -8.797 0.000
Multiple Membership Extensiveness -1.702 -8.426 0.000
00 General Social Trust -0.179 -2.260 0.024
iD FE13, 1669 =46.914, p.001, R =0.262, N=1682, *** <.01, ** <.05, <.10










Table 5-24. Regions with High Social Capital


Morality Policy:
Abortion
Coef. t
-0.279 -0.298
-0.111 -1.627
0.214 0.431
-0.004 -0.032
0.418 1.554
0.021 2.103
0.141 2.575
0.058 1.324


Morality Policy: Gay


High Social Capital

Constant
Party Identification
Ethnic Minority
Religiosity
Female
Age
Education
Income
Single Network
Intensiveness
Multiple Network
Intensiveness
io Single Membership
Extensiveness
Multiple Membership
Extensiveness
General Social Trust

*** <.01, ** <.05, *
p1.10


Redistributive Policy


Government Activism


Right
Coef.
0.062
-0.053
0.309
0.102
0.601
0.016
0.168
0.030


Coef.
4.967
-0.150
-0.006
0.027
0.174
-0.006
-0.033
0.007


sig.
0.00
0.000

0.977
0.596
0.116
0.131
0.144
0.713


Coef.
4.938
-0.098
0.532
-0.054
0.102
-0.002
0.007
0.020


sig.
0.000
0.004
0.030
0.382
0.440
0.729
0.783
0.361


sig
0.766
0.105
0.667
0.974
0.121
0.036
0.011
0.187


t sig
0.063 0.950
-0.746 0.456
0.600 0.549
0.780 0.436
2.152 0.032
1.577 0.116
2.953 0.003
0.665 0.507


t
12.891
-5.318
-0.028
0.531
1.578
-1.515
-1.467
0.369


t
10.702
-2.918
2.178
-0.876
0.774
-0.347
0.276
0.915


0.019 0.089 0.929 -0.131 -0.514 0.608 -1.514 -2.923 0.004 -1.932 -3.590 0.000

0.090 0.384 0.701 0.369 1.310 0.191 -1.499 -2.620 0.009 -1.831 -3.083 0.002

-0.051 -0.257 0.798 -0.061 -0.256 0.798 -2.057 -4.239 0.000 -2.562 -5.083 0.000

-0.110 -0.496 0.620 -0.389 -1.461 0.145 -1.693 -3.131 0.002 -2.103 -3.745 0.000
0.186 2.590 0.010 0.048 0.560 0.576 -0.390 -2.226 0.027 -0.685 -3.769 0.000


F[12,286]=3.948,
p1.001, R2=0.142
N=298


F[12.286]=2.382,
p1.006, R2=0.091
N=298


F[12, 286]=-9.673,
p1.001, R2=0.289
N=298


F[12, 286]=12.097,
<1.001, R2=0.262,
N=298










Table 5-25. Regions with Low Social Capital


Morality Policy:
Abortion


Morality Policy: Gay


Redistributive Policy


Government Activism


Right
Coef.
0.785
-0.012
-0.212
-0.174
0.068
-0.008
0.114
0.076


Coef.
4.970
-0.120
0.111
-0.069
0.019
-0.005
-0.021
-0.002


sig.
0.000
0.000
0.250
0.062
0.815
0.066
0.140
0.874


Coef.
4.487
-0.072
0.023
-0.017
0.138
-0.002
0.015
0.039


sig.
0.00
0.004

0.847
0.706
0.163
0.537
0.392
0.025


Coef.
0.637
-0.044
-0.078
-0.209
0.027
0.004
0.100
0.044


sig
0.273
0.309
0.709
0.010
0.876
0.520
0.001
0.146


sig
0.209
0.804
0.349
0.045
0.716
0.276
0.001
0.019


t
18.662
-6.030
1.151
-1.870
0.234
-1.845
-1.478
-0.158


t
13.603
-2.931
0.193
-0.377
1.395
-0.617
0.856
2.249


t
1.098
-1.019
-0.373
-2.591
0.156
0.644
3.198
1.456


Constant
Party Identification
Ethnic Minority
Religiosity
Female
Age
Education
Income
Single Network
Intensiveness
Multiple Network
Intensiveness
io Single Membership
Extensiveness
Multiple Membership
Extensiveness
General Social Trust

*** <.01, ** <.05, *
p1.10


1.258
-0.248
-0.937
-2.008
0.364
-1.090
3.378
2.357


0.023 0.177 0.860 -0.119 -0.730 0.466 -1.304 -4.540 0.000 -1.568 -5.072 0.000

0.095 0.580 0.562 -0.136 -0.673 0.501 -1.150 -3.229 0.001 -1.423 -3.712 0.000

-0.079 -0.543 0.588 0.266 1.470 0.142 -0.956 -3.007 0.003 -1.113 -3.252 0.001

0.013 0.085 0.932 0.276 1.465 0.144 -0.931 -2.809 0.005 -1.120 -3.138 0.002
0.227 4.059 0.000 -0.022 -0.324 0.746 0.044 0.360 0.719 0.147 1.121 0.263


F[12, 613]=6.554,
p1.001, R2=0. 114
N=625


F[12.613]=1.904,
<1.031, R2=0.036
N=625


F[12, 613]=-13.095,
p1.001, R2=0.204
N=625


F[12, 613]=17.099,
p1.001, R2=0.251,
N=625









CHAPTER 6
DISCUSSION

A single mother meets other single mothers in a day-care center. Those single mothers tend

to experience financial and emotional difficulties. The common experiences which they share

allows them to identify with one another and create more personal associations with each other

than the fact that they are all single mothers. As a result of their shared experiences and personal

interactions, they become alike in political beliefs and preferences.

Individuals' social lives are not predetermined elements and are not always translated

directly into feelings towards political agendas because people react to various parts of politics

using both explicit and implicit social interactions, such as cues in their political thinking

(Conover, 1988, pp.62, 65). Based on this logic, my study argued that different elements of

social capital would be activated or elevated by different types of political agendas and would

vary in their influence on certain types of policy attitudes.

Demographics

Overall, in preliminary analyses, my study found that there is a relevant association

between individuals' demographic factors and social capital. Individuals who have strong

partisanship, and are older, more educated, and part of the ethnic maj ority (the White) tend to be

more intensively involved in multiple social networks with higher levels of trust than people who

have no, or lower levels of partisanship, and are younger, less educated, and part of the ethnic

minority. However, gender has relevance only with general social trust; females are more likely

to believe that people are trustful, helpful, and fair than are males. People who are very religious

engage in social networks more intensively and extensively, but have similar levels of social

trust toward the general public, compared to less religious individuals. In addition, in spite of

some variations, different geographical regions have different levels of social capital. The









Mountain region, including states such as Nevada, Montana, and Wyoming has higher levels of

social capital compared to the West or South East regions, which includes states such as

Louisiana, Mississippi, and Alabama.

Stereotypically, liberals are more in favor of welfare programs and spending money, while

conservatives favor free enterprise. "Conservatives are seen as moralistic and religious; however

liberals are seen as having more flexible moral standards and not as religious." Reflectively,

Republicans have been seen as moralistic and Democrats as permissive in American politics

(Erikson and Tedin, 2007, p.75, 86). Several previous researchers observed that "the American

public is ideologically conservative but operationally liberal" (Free and Cantril 1967; Cantril and

Cantril, 1999). Therefore, the overall majority of Americans tend to support government

spending on various welfare policies (Erickson and Tedin, 2007, p.95).

More educated individuals tend to be more liberal in moral based types of public policies,

such as abortion and gay rights; but less educated individuals are more likely to support "social-

welfare spending issues, such as a guaranteed job and standard of living, national health

insurance, and increased government services" (Erikson and Tedin, 2007, pp. 64-5).

Among various demographic factors, religion is one of the most comprehensive social

networks in U.S. society. Individuals active in religious networks are more likely to "associate

with other forms of civic involvement, like voting, jury service, community proj ects, talking with

neighbors, and giving to charity". More importantly, religiosity has been a powerful indicator of

civic engagement, especially for voluntary and cultural networks (Putnam, 2000, pp.66-7).

Lastly, regarding research that shows that ethnic minorities such as Hispanics and Blacks

have suffered seriously from lack of health insurance (Cochran, et al., 2006, p.256), it is natural









that ethnic minorities tend to share less social capital, but are more supportive of liberal political

approaches such as social welfare policies.

Social Networks

In terms of dimensional relationships between multiple aspects social capital, according

to correlation tests, individuals who are intensively involved in a single social network tend not

to engage intensively in other types of networks. It seems reasonable to think that those that

already had a single membership are less likely to obtain other types of membership. This

finding indicates that social interactions do not unlimitedly occupy individuals' lives. People

who are already intensively involved in any social network they prefer, often have less time to

dedicate to other social networks. In addition, people who already have any type of social

membership do not have any motivation or desire to be a member of other social associations.

According to multiple regression tests in my study, network intensiveness and

extensiveness are related only to morality based policy attitudes, but are not relevant to

redistributive and government activism attitudes. In addition, unlike the study that expected

memberships in multiple group associations to increase political tolerance towards various social

issues (Cigler and Joslyn, 2002), individuals who are in multiple social networks still tend to put

greater values on societal order and morality over individuals' freedom to choose. According to

results of regressions excluding elements of religious networks, the statistical significance are

still identical with the model with regard to all types of social networks. Therefore, there are no

overwhelming effects of religious networks on participants' conservative policy attitudes.

Therefore, the result implies that having any type of social membership increases

individuals' morality values on social orders, thus the members are more supportive of stronger

governmental control on morality based social issues. This tendency is more dominant in people










who engage in one homogeneous social network that shares less attitudes of benevolence and

tolerance to differences (Putnam, 2000, p.341).

General Social Trust

General social trust has some contradictory characteristics of social capital against other

elements of social capital, such as network intensiveness and extensiveness. In addition, the

relationship between individuals' levels of trust toward the general public and various policy

attitudes is not always consistent. For instance, general social trust is highly related to positive

attitudes toward government redistributive policies and certain morality policies, such as gay

rights, but has no relevance to policy attitudes toward government activism and other types of

morality issues regarding abortion.

There could be several explanations about the dynamic implications of general social trust.

First of all, social trust itself contains attitude ambivalence, and the ambivalence becomes more

prevalent when it is directed toward different obj ects in different degrees of political situations

and social environments (Craig, Martinez, Kane, and Gainous, 2005). Second, the levels of trust

vary and are not linear: the maximum level of general social networks could be less positively

related to social tolerance compared to moderate level of social trust (Hardin, 2002). Social trust

is initially built up through interpersonal relations. Therefore, beyond certain interpersonal

connections or relevant boundaries, individuals tend to withdraw their social trust (Earle and

Cvetkovich, 1995, p. 10-11). Therefore, general social trust could be less prevalent among

individuals who belong to any social network boundaries than in people who were not in any

social network.

In addition, "people who trust others are all-round good citizens, and those more engaged

in community life are both more trusting and more trustworthy" (Putnam, 2000, p.137).

However, as Hero points out (2003), a greater level of social capital can isolate the minority and










ignore certain policies that are related to those people while benefiting the maj ority in the

society. "Racially homogeneous states do well on aggregate indicators of policy, but often have

very disparate relative examples of outcomes for racial ethnic minorities (p.402)." Therefore,

future research should further investigate more sophisticated social trust measurements and the

resulting implications.

Divergence of Policy Attitudes

In terms of redistributive policy attitudes, individuals who have higher levels of general

social trust are more likely to support government redistributive policies that would help the

'have-nots', however other elements of social capital, such as social networks, do not have any

significant influence on such policy attitudes. This result reflects the different functions of

social capital on even the same types of policy attitudes.

Moreover, multiple elements of social capital do not have any influence on policy attitudes

toward government activism that would often create public good. This finding could be the

result of particular tenets of government activism that are supposed to create and improve

general social good. For government activism, Americans have mixed preferences of wanting

both private choices/management and government intervention for subsidies (Erikson and Tedin,

2007, p.97). Regarding Putnam's arguments that social networks and associations help citizens

resolve collective problems easily, develop character traits that are good for the rest of society

(Putman, 2000, pp.288-90), facilitate communication, improve the flow of information, and

stabilize collaboration (Putnam, 1993, pp.173-74), a high level of social capital can even reduce

desire or the necessity of government actions. In addition, such different statistical significance

for redistributive and government activism are already suggested by previous scholars, such as

Lane (2000) and Wlezien (1995), who argued for contradictory and ambivalent policy attitudes









toward different areas of redistributive and government activism policies among general

American publics.

According to other findings in my research, individuals' social life patterns have the

strongest relevance with policy attitudes toward government morality policies on issues like

abortion and gay rights, among other types of government policies. As long as individuals

engage in any type of social network, they are more likely to support government regulations on

abortion and gay issues, placing greater value on social morality over individuals' freedom to

choose. General social trust, however, induces individuals' preferences on government

regulations on gay rights, but not on abortion.

These results reflect an incidence of social capital that not only makes people tolerant to

social diversity, but also creates undesirable group attitudes, group differences, and societal

isolations (White, 2003). For instance, individuals in small towns are highly engaged in their

community life, but they tend to be less tolerant of differences and diversities (Putnam, 2000,

p.352). Because social capital is often easily established by race, gender, and political

affiliations, individuals within such social networks are less likely to understand people from

other societal or political sectors. Small communities and highly committed neighborhoods are

less tolerant of homosexual teachers and interracial marriages for people within their own

communities (Putnam, 2000, p.352-53). Considering such a down-side of social capital, a strong

and narrow level of social capital can constrain an individual's freedom to choose and require

governmental regulations on societal orders (Schudson, 1998).

According to Feldman and Zaller (1992), people use diverse values, such as individualism,

humanitarianism, or personal attitudes against big government, in determining their attitudes

toward multiple policies. Therefore, there exist significant levels of attitude ambivalence in their









issue positions. The attitudinal ambivalence seems more predominant on governmental welfare

and morality policy types. Individuals' ideological innocence results in positive attitudes toward

benevolence to the have-nots and social morality. However, it creates problems by unaware

practical political tensions with inconsistent policy attitudes and preferences for welfare or social

policies (Feldman and Zaller, 1992, pp.268-69). All public policies have two sides, the effects

and counter-effects. These policies are fixing certain parts of the political problem and

benefiting certain groups of people, however they also constrain some other parts of society and

groups of people. Therefore, the conflict of ideological justifications and the practical operations

have been difficult for policy reformers, especially for welfare reformers (Feldman and

Zaller, 1992, pp.270-71), and perpetuates individuals' ambivalent policy attitudes (Craig,

Martinez, Kane, and Gainous, 2005).

Overall, although a large element of social capital, such as the levels of social trust,

become more indistinguishable across different regions (Hetherington, 2005, p.21), regional

differences on political and social culture have existed. Public opinion or attitudes at the macro

level of aggregation are far more orderly than single answers at the micro levels of the

individual. Although some individual tendencies can be cancelled out at the macro level, the

macro level of attitudes was seemingly uniform and appeared obvious (Erikson and Tedin, 2007,

p.93). Future research needs to address and explore the different effects of an element of social

capital at the individual level and the aggregated level of regions on political attitudes.

There are variations in different aspects of social capital in predicting political

consequences (Cigler and Joslyn, 2002). Individuals use different cues to determine their

political attitudes and their surroundings provide important cues. Based on how intensively and

broadly individuals engage in social networks, they view certain issues in more or less positive










ways (Stolle and Rochon, 2001). Therefore, it is reasonable to infer that different dimensions of

social networks are activated by different issues. Among various different types of policy

attitudes, government activism attitudes are less likely to relate to general social networks and

morality policy attitudes are more strongly related to all elements of social capital. As the study

predicted, various elements of social capital influence different policy attitudes in various ways.

Policy itself has multiple dimensions in purpose, process, and outcomes. Various political

structures and individuals' predispositions determined different policy preferences and induced

the government to end up with certain policy choices accordingly. For instance, homogeneous

communities adopt 'areal' policies, but heterogeneous communities will adapt 'segmental'

policies to satisfy diverse people (McCool, 1995, p.211).

Although the maj ority of individuals' political attitudes, especially policy preferences, are

highly related to their own interests, a great part of their preferences are determined by political

predispositions and socially shared values (Erikson and Tedin, 2007, p.65). Formal political

evidence and the connection with social capital are not yet clearly shown in the academic world

(Putnam, 2000, p.146).

Despite some limitation for clear causations between multiple dimensions of social capital

and various policy attitudes due to uncontrollable variations, this research is coherent and

parsimonious since policy attitudes and preferences tend to be more consistent and tractable than

any other political attitudes. In addition, policy attitudes can be easily summarized based on

attitudes towards specific public policies (Erikson and Tedin, 2007, pp. 9-18). Therefore, the

patterns between multi-dimensional social capital and specific policy attitudes are more likely to

be reliable.









In conclusion, it is important to understand the potential effect of social capital not only on

individuals' policy preferences at the level of individual, but also on direct policy efficiency at

the macro level of government on more specific policy issues such as education, poverty,

employment, housing, and other living environment (The National Economic and Social Forum,

2003). Further research needs to be done to construct more reliable and valid causations.









APPENDIX A
SOCIAL CAPITAL

Social Network Intensiveness
* Indicate whether you belong to a political party (Never belonged (1), used to belong (2),
belong but do not participate (3), belong and actively participate (4))

* Indicate whether you belong to a trade union or professional association (Never belonged
(1), used to belong (2), belong but do not participate (3), belong and actively participate
(4))

* Indicate whether you belong to a church or other religious organization (Never belonged
(1), used to belong (2), belong but do not participate (3), belong and actively participate
(4))

* Indicate whether you belong to a sports, leisure, or cultural groups (Never belonged (1),
used to belong (2), belong but do not participate (3), belong and actively participate (4))

* Indicate whether you belong to another voluntary association (Never belonged (1), used to
belong (2), belong but do not participate (3), belong and actively participate (4))

*Robert Putnam's social capital index (2000, pp.27, 291); Kwak, Shan, and Holbert (2004)'
categorization; Letki (2004)'s membership categorization

Table A-1. Factor Analysis on Social Network Intensiveness
Factor Component
belongs to a political party 0.871
belongs to a trade union or professional association 0.854
belongs to a church or other religious organization 0.886
belongs to a sports, leisure, or cultural group 0.889
belongs to another voluntary association 0.888


Social Network Extensiveness (Sum of memberships)
* Whether you have a membership in fraternal group (Q: We would like to know something
about the groups or organizations to which individuals belong. Here is a list of various
organizations. Could you tell me whether or not you are a member of fraternal group? no
(0), yes (1))

* Whether you have a membership in service group (Q: We would like to know something
about the groups or organizations to which individuals belong. Here is a list of various
organizations. Could you tell me whether or not you are a member of service group? no
(0), yes (1))

* Whether you have a membership in political club (Q: We would like to know something
about the groups or organizations to which individuals belong. Here is a list of various









organizations. Could you tell me whether or not you are a member of political club? no (0),
yes (1))

* Whether you have a membership in labor union (Q: We would like to know something
about the groups or organizations to which individuals belong. Here is a list of various
organizations. Could you tell me whether or not you are a member of labor union? no (0),
yes (1))

* Whether you have a membership in sports club (Q: We would like to know something
about the groups or organizations to which individuals belong. Here is a list of various
organizations. Could you tell me whether or not you are a member of sports club? no (0),
yes (1))

* Whether you have a membership in youth group (Q: We would like to know something
about the groups or organizations to which individuals belong. Here is a list of various
organizations. Could you tell me whether or not you are a member of youth group? no (0),
yes (1))

* Whether you have a membership in school service (Q: We would like to know something
about the groups or organizations to which individuals belong. Here is a list of various
organizations. Could you tell me whether or not you are a member of school service? no
(0), yes (1))

* Whether you have a membership in hobby club (Q: We would like to know something
about the groups or organizations to which individuals belong. Here is a list of various
organizations. Could you tell me whether or not you are a member of hobby club? no (0),
yes (1))

* Whether you have a membership in school fraternity (Q: We would like to know
something about the groups or organizations to which individuals belong. Here is a list of
various organizations. Could you tell me whether or not you are a member of school
fraternity? no (0), yes (1))

* Whether you have a membership in nationality group (Q: We would like to know
something about the groups or organizations to which individuals belong. Here is a list of
various organizations. Could you tell me whether or not you are a member of nationality
group? no (0), yes (1))

* Whether you have a membership in farm organization (Q: We would like to know
something about the groups or organizations to which individuals belong. Here is a list of
various organizations. Could you tell me whether or not you are a member of farm
organization? no (0), yes (1))

* Whether you have a membership in literary or art group (Q: We would like to know
something about the groups or organizations to which individuals belong. Here is a list of
various organizations. Could you tell me whether or not you are a member of art group? no
(0), yes (1))









* Whether you have a membership in church group (Q: We would like to know something
about the groups or organizations to which individuals belong. Here is a list of various
organizations. Could you tell me whether or not you are a member of church group? no
(0), yes (1))

* Whether you have a membership in veteran group (Q: We would like to know something
about the groups or organizations to which individuals belong. Here is a list of various
organizations. Could you tell me whether or not you are a member of veteran group? no
(0), yes (1))

* Whether you have a membership in professional society (Q: We would like to know
something about the groups or organizations to which individuals belong. Here is a list of
various organizations. Could you tell me whether or not you are a member of professional
society? no (0), yes (1))

* Whether you have a membership in any other (Q: We would like to know something about
the groups or organizations to which individuals belong. Here is a list of various
organizations. Could you tell me whether or not you are a member of any other? no (0),
yes (1))

*Allan Cigler and Mark Joslyn (2002)' s study, "The extensiveness of group membership and
social connectedness"

Table A-2. Factor Analysis on Social Network Extensiveness
Factor Component
membership in fraternal group 0.419
membership in service group 0.595
membership in veteran group 0.228
membership in political club 0.384
membership in labor union 0.249
membership in sports club 0.552
membership in youth group 0.558
membership in school service 0.560
membership in hobby club 0.439
membership in school fraternity 0.398
membership in nationality group 0.245
membership in farm organization 0.235
membership in literary or art group 0.521
membership in professional society 0.614
membership in church group 0.623
membership in any other 0.292










General Social Trust (Mean of three trust scale)


* Whether people helpful or looking out for themselves (Q: Would you say that most of the
time people try to be helpful, or that they are mostly just looking out for themselves? Not
helpful (1), Depends (2), Helpful (3))

* Whether people are fair or try to take advantage of others (Q: Do you think most people
would try to take advantage of you if they got a chance, or would they try to be fair? Take
advantage (1), Depends (2), Fair (3))

* Whether people can be trusted (Q: Generally speaking, would you say that most people can
be trusted or that you can't be too careful in life? Cannot trust (1), Depends (2), Trust (2))

*Putnam (2000); Letki (2004); James Gibson (2001)'s index

Table A-3. Factor Analysis on General Social Trust
Factor Component
Helpful 0.780
Trust 0.735
Fair 0.795









APPENDIX B
POLICY ATTITUDES

Redistributive Policy

* Whether government should reduce income differences (Q: Some people think that the
government in Washington ought to reduce the income differences between the rich and
the poor, perhaps by raising the taxes of wealthy families or by giving income assistance to
the poor. Others think that the government should not concern itself with reducing this
income difference between the rich and the poor. Here is a card with a scale from 1 to 7.
Think of a score of 7 as meaning that the government ought to reduce the income
differences between rich and poor, and a score of 1 meaning that the government should
not concern itself with reducing income differences. What score between 1 and 7 comes
closest to the way you feel? (Govemnment should not (1), Government should (7))

* Whether government should improve standard of living (Q: I'd like to talk with you about
issues some people tell us are important. Please look at CARD BC. Some people think that
the government in Washington should do everything possible to improve the standard of
living of all poor Americans; they are at Point 1 on this card. Other people think it is not
the government's responsibility, and that each person should take care of himself; they are
at Point 5. Where would you place yourself on this scale, or haven't you have up your mind
on this? (Rescaled to Govemnment should not (1), Govemnment should (7))

* Whether government should help pay for medical care (Q: In general, some people think
that it is the responsibility of the government in Washington to see to it that people have
help in paying for doctors and hospital bills. Others think that these matters are not the
responsibility of the federal government and that people should take care of these things
themselves. Where would you place yourself on this scale, or haven't you made up your
mind on this? (Government should not (1), Government should (7))

Table B-1. Factor Analysis on Redistributive Policies
Factor Component
improve standard of living 0.816
reduce income should government reduce income differences 0.784
help pay for medical care 0.740

Government Activism

* Whether government needs to do more to improve & protect national health (Q: We are
faced with many problems in this country, none of which can be solved easily or
inexpensively. I'm going to name some of these problems, and for each one I'd like you to
tell me whether you think we're spending too much money on it, too little money, or about
the right amount. Are we spending too much, too little, or about the right amount on
improving & protecting nations health? Too much done (1), About Right (4), Too little
done (7))









* Whether government needs to do more to improve nations education system (Q: We are
faced with many problems in this country, none of which can be solved easily or
inexpensively. I'm going to name some of these problems, and for each one I'd like you to
tell me whether you think we're spending too much money on it, too little money, or about
the right amount. Are we spending too much, too little, or about the right amount on
improving national education system? Too much done (1), About Right (4), Too little done
(7))

* Whether government needs to do more to improve & protect environment (Q: We are
faced with many problems in this country, none of which can be solved easily or
inexpensively. I'm going to name some of these problems, and for each one I'd like you to
tell me whether you think we're spending too much money on it, too little money, or about
the right amount. Are we spending too much, too little, or about the right amount on
improving and protecting the environment? Too much done (1), About Right (4), Too little
done (7))

* Whether government needs to do more to solve problems of big cities (Q: We are faced
with many problems in this country, none of which can be solved easily or inexpensively.
I'm going to name some of these problems, and for each one I'd like you to tell me whether
you think we're spending too much money on it, too little money, or about the right
amount. Are we spending too much, too little, or about the right amount on solving
problems of big cities? Too much done (1), About Right (4), Too little done (7))

Table B-2. Factor Analysis on Government Activism
Factor Component
improving & protecting nations health 0.829
improving nations education system 0.823
improving & protecting environment 0.782
solving problems of big cities 0.576

Morality policy

On Abortion

* Whether allow abortion: Defect in the baby (Q: Please tell me whether or not you think it
should be possible for a pregnant woman to obtain a legal abortion, if there is a strong
chance of serious defect in the baby? No (1), Yes (7))

* Whether allow abortion: No more children (Q: Please tell me whether or not you think it
should be possible for a pregnant woman to obtain a legal abortion If she is married and
does not want any more children? No (1), Yes (7)

* Whether allow abortion: Endangered by the pregnancy (Q: Please tell me whether or not
you think it should be possible for a pregnant woman to obtain a legal abortion, if the
woman's own health is seriously endangered by the pregnancy? No (1), Yes (7))









* Whether allow abortion: Poverty (Q: Please tell me whether or not you think it should be
possible for a pregnant woman to obtain a legal abortion, if the family has a very low
income and cannot afford any more children? No (1), Yes (7))

* Whether allow abortion: Rape (Q: Please tell me whether or not you think it should be
possible for a pregnant woman to obtain a legal abortion, if she became pregnant as a result
of rape? No (1), Yes (7))

* Whether allow abortion: Unwanted marriage (Q: Please tell me whether or not you think it
should be possible for a pregnant woman to obtain a legal abortion, if she is not married
and does not want to marry the man? No (1), Yes (7))

* Whether allow abortion: Any reason (Q: Please tell me whether or not you think it should
be possible for a pregnant woman to obtain a legal abortion, if the woman wants it for any
reason? No (1), Yes (7))

Table B-3. Factor Analysis on Abortion
Factor Component
not married 0.889
wants no more children 0.872
cant afford more children 0.871
any reason 0.866
serious defect 0.717
rape 0.693
health seriously endangered 0.584


On Gay Rights

* Whether allow homosexual sex relations (Q: What about sexual relations between two
adults of the same s ex d o you think it is always wrong, almost always wrong, wrong only
sometimes, or not wrong at all? Always wrong (1), Almost always wrong (3), Depends (4),
Sometimes wrong (5), Not wrong at all (7))

* Whether allow homosexual to speak (Q: Should a men who admits that he is a homosexual
be allowed to speak and make a speech in your community, or not? Not allow(1),
Allow(7))

* Whether allow homosexuals to teach (Q: Should a men who admits that he is a
homosexual be allowed to teach in a collage or university, or not? Not allow(1), Allow(7))

* Whether allow homosexuality books(Q: If some people in your community suggested that
a book he wrote in favor of homosexuality should be taken out of your public library,
would you favor removing this book, or not? Remove(1), Not Remove(7))










Table B-4. Factor analysis on gay rights
Factor
homosexual to teach
homosexual to speak
homosexuals book in library
homosexual sex relations


Component
0.826
0.810
0.769
0.605









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BIOGRAPHICAL SKETCH

Hyun Jung Yun grew up in South Korea and completed her undergraduate work maj oring

in Political Science at Aj ou University. Starting with her undergraduate senior year as an

exchange student, she continued her master' s degree studying in political science and doctorate

in the fields of 'political science' and 'j ournalism and communications' at the University of

Florida in the United States of America

Her research interests are in political perception, the political communication process,

policy attitudes, persuasion, and geopolitics across different levels of the individual, small group,

and aggregate group. More specifically, her research in the Hield of political communication

explores the relationship between political information process and individuals' political

attitudes in different geopolitical circumstance. In the same line of interdisciplinary research, her

research in political science investigates how individuals' beliefs about various policies are

influenced by varying levels of multi-dimensional social capital and communication networks.

Her research in journal publications demonstrates how individuals' political perceptions

and attitudes are influenced by political predispositions within a group and by political resources

within a given political and media system at the aggregate level. In addition, she had coauthored

several book chapters examining news coverage of policy issues and political candidates across

different political regions to observe the relationship between different political characteristics

and political information effects. She is currently working on analyzing the dual spirals of

silence in policy opinion formation between issue minority and issue maj ority, effects of

relationship between media and politics on voter perceptions, as well as political cynicism and

information efficacy in young voters.

She also has participated in grant-supported research proj ects including the Florida

Department of Health' s 2004 Proj ect in Media Terrorism Preparation under Dr. Mary Ann










Ferguson and Dr. Lynda Lee Kaid, Uvote inter-university research on U.S. elections under Dr.

Lynda Lee Kaid, and United States Election Assistance Commission' s proj ect establishing

election law database under Dr. Lynda Lee Kaid and Dr. Cliff Jones The former proj ect dealt

with media advocacy, government public information, and issue management on terrorism. The

Uvote research has focused on political advocacy and political information effects. The

development of electronic database of U. S. election laws intended to provide U. S. citizens easy

internet search function for comprehensive U.S. election law. She has worked for these proj ects

as a data analyst and proj ect manager.

She also worked as data archiving assistant for ICPSR (Inter-university Consortium for

Political and Social Research) for a part of graduate assistantship duty. She was trained in

advanced methodology through ICPSR as well as by the departments of statistics, political

science, and journalism and mass communications. Her methodological training across different

fields includes managements of data through various applications and various levels of statistics

such as linear regression, categorical analysis, multivariate analysis, maximum likelihood

analysis, game theory, content analysis, scaling, and measurement.

Her next proj ect is to collect linearly coherent multi-level data that links individual

perceptions, attitudes, and preferences with the aggregate level of media and political

predispositions in different political regions, election turnouts, policy efficiency, and other

media-politics routines in order to conduct research with theoretically reliable connections across

different levels of dynamics.

Hyun Jung Yun who has two doctorate degrees, one in political science and the other in

journalism and communications, will work as an assistant professor at Texas State University

starting from August 2007.





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1 THE DIFFERENT TIERS OF SOCIAL LIVES IN POLICIES: POLICY BELIEFS AND DIFFERENT ASPECTS OF SOCIAL CAPITAL By HYUN JUNG YUN A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2007

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2 2007 Hyun Jung Yun

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3 To all who nurtured my intellectual curiosity, academic interests, and sense of scholarship throughout my lifetime, maki ng this milestone possible

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4 ACKNOWLEDGMENTS Completing two doctoral programs has been a fabulous life journey for me. I have gone through exciting, enjoyable, su rprising, blissful, but sometim es stressful, depressing, and heartbreaking moments. I beli eve that I am very lucky since I have been surrounded by amazing people for the last seven years of this journey. I would like to express my gratitude to all of the people who gave me endless support, encourag ement, and love from the beginning of my graduate program through to the point of comple tion of my two disserta tions, one in Political Science and the other in Jour nalism and Mass Communications. First of all, I want to thank my life time advisers and chairs, Dr. David Hedge and Dr. Lynda Lee Kaid. Dr. Hedge has guided me and co rrected me whenever I need any direction to go and added his sweetness to my journey with in credible encouragement and compliments. Dr. Kaid has always stimulated me with resear ch ideas through a week ly research meeting throughout my doctoral program and taught me i nvaluable lesson of how the research is supposed to be processed. I also deeply appr eciate that Dr. Michae l Martinez, Dr. Renee Johnson, and Dr. Mary Ann Ferguson who have been always there for me and given me precious advice at the right moments. Dr. Spiro Kiousis and Dr Lynn Levertys endless support for my academic projects has accelerated my academic progr ess. My interdisciplinary research was able to be completed due to all of my committee members special academic expertise and emotional support and dedication. I would also likely to express my special th anks to my mentors, Dr. Goran Hyden, Dr. Seung Ik Yoo, Dr. Mi Kyung Jin, Dr. Chul Whan Kim, Dr. Sun Joo Yoon, Dr. Sung Hwa Yoon, Dr. Jun Han Kim, Dr. Soo Bok Lee, and Dr. Kyung Ho Lee since my undergraduate program in Korea. Their priceless lessons and guidance fuel ed my academic eagerness in the early years of my university education. Moreover, Korean f aculty members at the University of Florida, Dr.

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5 Won-Ho Park, Dr. Chang-Hoan Cho, Dr. YooJin C hoi, and Dr. Hyojin Kim, have always offered to lend their hands to me. I al so would like to give my special thanks to Dr. Joo Myung Song, Dr. Dou Kyung Ahn, and Dr. Yoo Hy ang Kim who have shared thei r hearts even giving me luck money for my job interviews. In addi tion, Dr. Richard Scher a nd Dr. Badredine Arfis compliments and support on my teaching experience have built me up with positive confidence, thus make me be able to overcome all unnecessary self-consciousness as an international student My great colleagues and best friends, David Conklin, Dr. Mo nica Postelnicu, Dr. Jun Soo Lim, Dr. Seung Eun Lee, Dr. Eyun Jung Ki, Soo Yeon Km, Dr. Nadia Ramutar, Sarah Urriste, Dae Hyun Kim, Min Gil Kim, and Shari Kwon, deserv e to have my whole he art. I was able to stay human due to their sense of humor, faith, love and trust. In addition, I would like to thank to Mrs. Jody Hedge, Mrs. Debbie Wallen, and Mr s. Sue Lawless-Yanchisin who have been my personal life advisers beyond academia by giving me important information and sharing our stories. They always shared their great smiles an d open-minds with me. Th ey are the core people for the programs of Journalism & Mass Communicati ons and Political science. They made all this process easier, smoother, a nd enjoyable. My special than ks also goes to Gordon Tapper, who has a wonderful heart and cultural insight s. Sharing my cultural background, he has observed my pattern of English speaking to guide me in how a foreign speaker at the advanced level can reach to the level of native English sp eaker, even dedicating his free Friday for me. Lastly, I would like to express my special than ks to my parents. My daddy, who is very protective and would do anything he can do for me, thus it was not easy for him in the beginning to let me go away even for an academic program, has been an important reason for me to be a good person. My mom has dedicated every single breath to me and has been the best supporter for my choice for academic life. I was able to grow up in a happy environment due to my

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6 wonderful parents. My final appreciation goes to my soul mate who has shared every single moment with me for the last eleven years. I always felt their affection and belief in me It has given me my endless energy for my academic progress. Due to them, I have never th ought about giving up in any single step of my academic progress. I know how lucky I am having such wonderful people around me. I deeply appreciate all of them and promise that I will try to be one who can make them happy.

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7 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................4 LIST OF TABLES................................................................................................................. ..........9 ABSTRACT....................................................................................................................... ............11 CHAPTER 1 INTRODUCTION..................................................................................................................12 2 LITERATURE REVIEW.......................................................................................................20 Dimensions of Social Capital.................................................................................................20 Definitions of social capital.............................................................................................20 Different Dimensions of Social Capital..........................................................................21 Social networks: theo retical understandings & empirical evidence.........................22 General social trust: Theoretical understandings & empirical evidence..................28 Functions of Social Capital.................................................................................................... .33 The Positive Consequences of Social Capital.................................................................33 The Negative Consequences of Social Capital................................................................37 3 HYPOTHESES AND THE PERSPECTIVES.......................................................................42 On Redistributive Policies..................................................................................................... .43 On Government Activism.......................................................................................................45 On Morality Policies........................................................................................................... ....46 4 METHOD....................................................................................................................... ........50 Data........................................................................................................................... ..............50 Perspectives of Categorization...............................................................................................51 Measuring Dimensions of Social Capital........................................................................51 Measuring Public Policy Typology.................................................................................57 Conditional Factors of Demographics.............................................................................60 Analyses....................................................................................................................... ...........63 5 RESULTS...................................................................................................................... .........65 Demographics and Social Capital...........................................................................................65 Party Identification..........................................................................................................65 Gender......................................................................................................................... ....66 Age............................................................................................................................ ......66 Education...................................................................................................................... ...67 Ethnicity...................................................................................................................... ....67

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8 Religiosity.................................................................................................................... ....67 Income......................................................................................................................... ....68 Region......................................................................................................................... .....68 Dimension of Social Capital...................................................................................................68 Correlations between Different Di mensions of Social Capital...............................................70 Social Capital and Policy Attitudes........................................................................................71 On Redistributive policy..................................................................................................71 On Government Actions..................................................................................................73 On Morality Policy..........................................................................................................74 The Regional Context and Social Capital...............................................................................76 6 DISCUSSION................................................................................................................... ......92 Demographics..................................................................................................................92 Social Networks...............................................................................................................94 General Social Trust........................................................................................................95 Divergence of Policy Attitudes.......................................................................................96 APPENDIX....................................................................................................................... ...........101 A. SOCIAL CAPITAL..............................................................................................................101 Social Network Intensiveness...............................................................................................101 Social Network Extensivene ss (Sum of memberships)........................................................101 General Social Trust (Mean of three trust scale)..................................................................104 B POLICY ATTITUDES.........................................................................................................105 Redistributive Policy.......................................................................................................... ..105 Government Activism...........................................................................................................105 Morality policy................................................................................................................ .....106 On Abortion...................................................................................................................106 On Gay Rights...............................................................................................................107 LIST OF REFERENCES.............................................................................................................109 BIOGRAPHICAL SKETCH.......................................................................................................119

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9 LIST OF TABLES Table page 3-1 Hypotheses Matrix.......................................................................................................... ...49 5-1 Party Identification and Social Capital..............................................................................79 5-2 Party Identification and Networks Intensiveness and Extensiveness................................79 5-3 Gender and Social Capital.................................................................................................80 5-4 Gender and Network Intens iveness and Extensiveness.....................................................80 5-5 Age and Social Capital..................................................................................................... ..80 5-6 Age and Network Intensiveness and Extensiveness..........................................................81 5-7 Education and Social Capital.............................................................................................81 5-8 Education and Network Inte nsiveness and Extensiveness.................................................81 5-9 Ethnicity and Social Capital...............................................................................................82 5-10 Ethnicity and Network Intensiveness and Extensiveness..................................................82 5-11 Religiosity and Social Capital............................................................................................82 5-12 Religiosity and Network Inte nsiveness and Extensiveness...............................................83 5-13 Income and Social Capital.................................................................................................83 5-14 Income and Network Intensiveness and Extensiveness.....................................................83 5-15 Region and Social Capital................................................................................................. .84 5-16 Region and Network Intens iveness and Extensiveness.....................................................84 5-17 Descriptive Social Capital................................................................................................ ..85 5-18 Correlations of Social Capital............................................................................................85 5-19 Correlations of Network In tensiveness, Extensiveness, and General Social Trust...........86 5-20 Social Capital and Redist ributive Policy Attitudes............................................................86 5-21 Social Capital and Government Activism Attitudes..........................................................87 5-22 Social Capital and Attitudes toward Abortion...................................................................88

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10 5-23 Social Capital and Att itudes toward Gay Rights...............................................................89 5-24 Regions with High Social Capital......................................................................................90 5-25 Regions with Low Social Capital......................................................................................91 A-1 Factor Analysis on Social Network Intensiveness...........................................................101 A-2 Factor Analysis on Social Network Extensiveness..........................................................103 A-3 Factor Analysis on General Social Trust.........................................................................104 B-1 Factor Analysis on Redistributive Policies......................................................................105 B-2 Factor Analysis on Government Activism.......................................................................106 B-3 Factor Analysis on Abortion............................................................................................107 B-4 Factor analysis on gay rights............................................................................................108

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11 Abstract of Dissertation Pres ented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy THE DIFFERENT TIERS OF SOCIAL LIVES IN POLICIES: POLICY BELIEFS AND DIFFERENT ASPECTS OF SOCIAL CAPITAL By Hyun Jung Yun August 2007 Chair: David Hedge Major: Political Science This study showed how specific policy beliefs are influen ced by individuals various levels of general social trust and multi-dimensional social networks such as intensiveness and extensiveness. By analyzing the 2004 General So cial Survey, the study f ound that general social trust and network intensiveness and extensivenes s conditionally influence policy beliefs based on various policy types. General social trust reinforces positive attitudes toward redistributive policies for the poor and morality policies on gay rights. Network intensiveness and extensiveness influence supportive tendencies fo r government regulations on morality policies, but do not do so for other types of policies. In addition, there are no statistical differences between single and multiple network intensivene ss and extensiveness on policy beliefs as long as an individual is involved in any type of social network. Although there was a mixture of evidence, the study proved that various elements of social capital influence different policy attitudes.

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12 CHAPTER 1 INTRODUCTION There is renewed interest in political scie nce regarding the infl uence of individuals social lives on politics. For in stance, prominent scholars in the study of social capital, such as Robert Putnam and Margaret Levi, have successfu lly incorporated a discussion on the effects of social lives within the political sphere. In his depiction of the lonely American isolated from society due to thinning social c onnections, Putnam (2000) pulled indi viduals social lives into the academic arena by examining the impact of so cial capital, or social networks, and the corresponding norms of trust and reciprocity on the quality of co mmunity and political life. Similarly, Valerie Braithwaite and Margaret Levi (1998), Karen C ook (2001), and others developed the concepts of comm unal trust and norms as explanations for social cooperation and efficient government operation. Pamela C onover and Stanley Feldman (1984), and David Boninger, Jon Krosnick, and Matthew Berent (1995) also contributed by uncovering the importance of social groups to an individuals political beliefs. These scholars used different approaches to in troduce the various political implications of individuals social lives. Putn am (2000) argued that social networks, trust, and group norms allow the American society to accomplish collect ive actions and establish efficient information flow, thus enabling society to overcome selfish social problem s. Putnams long-term study comparing similar political regimes demonstrat ed that good governments were established by a strong tradition of social networks and a higher level of trust among citizens, rather than by the quality of the government system, party politics, ideology, social stabil ity, political harmony, or population movements (Putnam, 1993). Karen Cook, Russell Hardin, Margaret Levi, a nd others have specifi cally explored the concept of trust and emphasize its importance in a wide variety of social contexts across different

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13 disciplines including philosophy, political scie nce, sociology, hist ory, economics, and psychology. They defined trust as an alternat ive, informal means of sustaining social cooperation and establishing a be tter society. Combining normative and empirical studies supported their original hypothese s on the normative role of trus t in a society (Russell Sage Foundation). Henri Tajfel and John Turners (19 79) original works on social group attachments and scholars recent applications of social ties in macro-level studies of soci ety and politics suggested that individuals psychol ogical attachments to social groups affected their political attitudes toward candidates, forms of government, and behaviors such as voting. However, there are some critical issues that these scholars have overlooked. First, scholarly works have not yet clarified definitions, ranges, or meanings of social capital. No consensus or agreement exists on the different as pects of social capital despite the fact that theoretical and empirical agreement is necessary to further applications of social capital studies. Many scholars have either narrowed their focus to specific types of social capital or broadened their understanding of social capital void of concrete definitions (Cook, 2001, p.23). Therefore, no concise meaning or consistent measurement of social capital exists in the field. Secondly, previous studies too of ten failed to look at the multiple dimensions of social capital. Social capital studies are in the prelim inary stages of identifying how various elements of social capital differ from and relate to one anot her. The majority of scholarly works have not differentiated specific trust from general trus t, types of social networks from network extensiveness, reciprocity from trust, and connectedness at the mi cro-level of the individuals from identity at the macro-level of groups, regions, or states. For instance, mainstream scholars in the study of trust, such as Cook, Hardin, and Levi, argued the importance of only a specific type of trust in certain contexts, overlooking the

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14 different levels of social conn ectedness in individuals lives. Therefore, their studies simply focused on a contextual understandi ng of social capital. Although so me other scholars started to analyze trust as a distinctive con cept by looking at situati onal or contextual trust differently from general social connectedness and even defined se veral types of trust fo r ordinary individualspublic incumbents, general public organizations, and political institutio ns (Chanley, Rudolph, and Rahn, 2000)they did not provide any theoretic al reasons or empirical evidence to support how these categories were related to one anothe r or how different leve ls of trust and other aspects of social norms could be used to predict social and polit ical consequences. Therefore, their works failed to provide a complete explan ation of how specific forms of trust at the individual-level are influenced by broader so cial trust within the political sphere. In addition, general networks, r eciprocity, and trust were trea ted partially or broadly as representatives of social capit al according to the different purposes of each study. Previous scholars did not exhaustively deal with multiple dimensions of social capital and explore how these ideal concepts work together and are inte rrelated in societal contexts. For instance, scholars in the social capital fiel d view social networks through an even narrower perspective of interpersonal attachment. Such scholars have used different types of social ties in various social and political situations, resulting in studies that are too divergent to predict a coherent pattern of political outcomes using such different perspectives of social capital. In other words, they have not confirmed the overall the patter n linking the various aspects of social capital to a specific political result. There are theoretical and empiri cal discrepancies that lead to difficulties in explaining what social capital m eans, how each different element of social capital interacts in the political contexts, and how they are de veloped into political consequences.

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15 Social networks and trust are two different di mensions of social lives, each of which can be interpreted in many different ways in politic al processes. Thus, the differing impacts of individuals social prope rties on their political beliefs need to be theoretically differentiated. Without defining the concrete dimensions of such concepts, the research w ill lose the capacity to deliver more accurate predictions (Braithwaite and Levi, 1998, p.69). Despite a number of great scholarly works on social capital, the outli ned limitations in understating its multiple implications make the process of defining a fi rm theoretical approach to the subject more difficult. The third limitation is that the majority of scholarly research has focused only on the positive or normative side of social capital, although a few insightful scholars, such as Putnam (2000) and Hero (2003) argued the po ssibility of the negative impacts. Social capital indeed has both positive and negative effects. One side of so cial ties is individuals positive attachments to certain groups, while the other side of excessi ve social group attachment, such as extreme ethnocentrism or chauvinism, could isolate in dividuals from society. Individuals who discriminate against out-group people in order to protect their own in-group against new information could cause social conflicts and hinder social cooperation (Chong, 2000, pp.88-90). Such bridging and bonding are typical political soci al scenes (Putnam, 2000). Even Putnams discussions on social networ ks and trustworthiness (1993 and 2000) overlooked all specific social and political functions by overemphasizi ng overall optimistic consequences of social capital (Franklin, 2003, p.352). Many well-known studies have overlooked the conflicting values within social networks by failing to consid er or define the multiple connotations of social ties.

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16 The final problem of previous research is a structural disconnect between individual levels of social capital and macro levels of aggregate political consequences. There are theoretical confusions between th e two different levels of social capital at the individual and aggregate state, and two different levels of individual political characteristics or aggregate political outcomes. These connections have been vaguely explored without any specification. The majority of previous research in the field dealt with aggregate social capital to predict overall political tendencies and policy choices, ignoring micro leve l of dynamics. Thus, these studies have struggled in finding a concrete conne ction between social capit al that are initially oriented from the micro-level of the individual and the macro-leve l of specific polit ical attitudes or choices. More interestingly, none of the previous research ha s looked at the impact of micro levels of individual social capit al on specific policy attitudes syst emically as an intermediate process before determining a final policy choice and other political outcomes. For example, some previous empirical studies, such as Margit Tavitss work on social capital and government performance, measured th e links between micro levels of social capital and governmental levels of political dynamics, such as policy activism and administrative efficiency (Tavits, 2006). However, such studi es omitted an important connection between the diverse factors of social capital among individual s and the steps leading to policy outcomes. In other words, the reasons of how individual levels of social capita l turn out as a consequence at the macro-level were not explained. The discrete measurement of two different micro-levels of social lives and the macro-level of their polit ical outcomes with a single indicator from each level is problematic in answering the c ontinuum level of research question. In addition, although some studies, such as Oorschots resear ch on the social connectedness of European welfare states, differe ntiated various types of social connectedness,

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17 they still retained the separa tion of microand macro-sphe res by neglecting individuals intentions or motivations in state policies and se parately analyzing national levels of aggregate public sector outcomes. Putnams perspe ctives on social ca pital in his books Bowling Alone (2000) and Making Democracy Work (1993) looked at civi c engagements or social networks as the core of the individual social elements needed for a successful political system, and considered trustworthiness a part of social networks. However, hi s research still did not clearly answer the process of how individual levels of so cial capital could be de veloped as governmental levels of political outcomes. To deal with these limitations, my study intends to make an apparent connection between the different aspects of individuals social capit al by attempting to show how these elements of social capital are related to one another while rectifying the discrepancies between various conceptualizations of social capital adopted by scho lars in previous resear ch. I also explore the interrelation of various aspects of social capita l to create a more reliable pattern and a more consistent understanding of the multidim ensional elements of social capital. In the next step, my study intends to expl ore the intermediate connection between the micro level of individual social capital and various policy attitudes accordingly. Moreover, instead of regarding social capital as a single conceptual dimension and measuring a onedimensional relationship between the level of soci al capital and possible political outcomes, this study presumes differences in indivi dual levels of trust and the vari ous facets of social networks as multi-dimensional components of individuals so cial lives that lead to particular political characteristics (Oorschot and Arts, 2005). In ot her words, it examines the ability of multiple aspects of social capital at the individual level to predict partic ular policy attitudes rather than

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18 simply connecting individuals and the aggregate political possibility or looking at the effect of a single aspect of social capital on general political outcomes. Finally, I create a pattern of the relationship between the multiple dimensions of social capital and various policy attitude s by testing how individuals sing le or collective social capital elements influence their various political attitude s towards different types of public policy issues. The specific policy attitudes and beliefs are expl ained through multidimensional social capital at the micro level of the individual. Individuals develop particul ar attitudes and make various political decisions about different political issues based on the cues they can easily take from the views, preferences, evaluations, a nd actions of people who are part of their social lives and such a tendency is reflected on larger aggregated poli tical pictures. My study investigates the multiple relationships between social connectedness within individuals lives and multiple policy beliefs and attitudes as an aggregate factor before policy outcomes. Using the 2004 General Social Survey, the study determines whethe r different levels and various as pects of social capital shape individuals various policy beliefs and attitudes about di fferent types of policies. My study found that different elements of soci al capital, such as network intensiveness and extensiveness, and levels of general social trust, contribute to different policy attitudes in various ways. Although common elements of social capital occu r by inducing positive expectations toward government policies among indi viduals who are intensiv ely involved in and have extensive social networks or interactions, there are divergent elements of social networks that are contradictory or even negatively influencing different types of policy attitudes. The study confirmed that individuals who are intensively involved in a limited boundary of social networks are less likely to be inte nsive in other types of social networks and less likely to trust other people beyond their social networks; how ever, people who engage in multiple social

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19 networks are more likely to engage intensively in any of those social networks, but again, less likely to trust other members of the society. In terms of redistributive polic y attitudes, individuals who ha ve higher levels of general social trust are more likely to support government redistributive policies that would help the have-nots, however, social networks did not have a significant in fluence on such policy attitudes. Moreover, multiple elements of social capital do not have any influence on policy attitudes toward government activ ism that would often create pub lic good. However, individual social life patterns have a strong influence on policy attitudes toward government morality policies on issues like abortion a nd gay rights. As long as indivi duals engage in any type of social network, they tend to support government regulations on abortion and gay issues, placing greater values on social morality over an individu als freedom to choose. General social trust, however, induces individuals pref erences on government regulati ons on gay rights, but not on abortion. These tendencies are still consistent when th e relationships between social capital at the individual level and policy attit udes are explored sepa rately under different regional levels of social capital. Multiple dimensi ons of social capital at the individual level in regions with either higher or lower levels of social capital identically influence i ndividuals policy attitudes overall besides the function of general soci al trust on morality policy attitude s. There is a stable positive relationship between general social trust and supportive attitudes for different types of morality policies in rich social capita l regions, but the tendency beco mes insignificant in low social capital regions. Such tendencies are more stable at the regional level than at the individual level where there are more fluctuating policy at titudes across different morality issues.

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20 CHAPTER 2 LITERATURE REVIEW This chapter discusses the definition and multidimensional elements of social capital. Different elements of social capital, such as network intensiveness (bonding), network extensiveness (bridging), and generalized social trust, have different political implications and functions, and have both positive and negative features of general political and policy effects. Therefore, I explore the components of social cap ital and their political implications on multiple policies more closely using pr evious scholarly research. Dimensions of Social Capital Definitions of social capital Scholars have looked at how individuals interact and what those interactions mean within communities, demographic groups, or other politic al boundaries. Originally, Lyda Hanifan used the notion of social capital for individuals communal interactions. For Hanifan, social connectedness interactions are ta ngible substances [that] count for most in the daily lives of people, particularly concerned w ith the cultivation of good will, fellowship, sympathy, and social intercourse (Hanifan, 1961, p.130). Several decades later, Robert Putnam (2000) introduced the concept of reciprocal social relations to politi cal research with greater concerns for declining social networks in American society. Accord ing to Putnam, social capital is defined as connections among individualssocial netw orks and the norms of reciprocity and trustworthiness that arise from them (Putnam, 2000, p.19). Both the specific and generalized reciprocity and trust that lubricate social and political proce sses are considered social capital, which has externalities that affect the wi der community beyond certain boundaries of social networks or specific levels of trust (Putnam, 2000, pp.19-21)

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21 James Coleman (1988) views social capital as a variety of different entities, with two elements in common: they all consist of some as pect of social structur e, and they facilitate certain actions of actors (p.598) Political scholars have used the concept of social capital extensively, associating it with interpersonal social interaction, conn ectedness, or sense of community to predict desirable political conseq uences such as positive policy outcomes, active political participation, and economic growth. Based on the characteristics of social capital that schol ars have adopted, previous research can theoretically be categorized into tw o broad areas: trust and social networks. For researchers in the field of trust, trust is a kind of social connectedness used as a good or commodity that helps members of societ y accomplish various purposes (Cook, 2001, p.21). General social networks can also be interpre ted in different ways such as the genre of associations, extensiveness, or level of attach ments. However, there is a blurred understanding of social capital and non e of its related concepts are fully defined. Based on the political consequences scholars are looking at, their resear ch has introduced various levels of trust, different aspects of social netw orks, and some combinations of those two tenets of social connectedness into the study of politics and policies. In general, social capital is a glue that holds society together (Serageldin, 1996, p.196), but we need to understand what it does and how it works within a given field of research through a reliable pattern of predictions. Different Dimensions of Social Capital Multiple facets of social capital can stimul ate and create different political outputs. Although different elements of social capital ar e reinforced by each other for reciprocity and collective actions, each of them plays a unique role in a society (Serageldin and Grootaert, 2000, p.40). A number of scholars argue that social capital can be approached through dichotomous dimensional tools: the elements of social capital can be structural vs. c ognitive (Krishna, 2000),

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22 horizontal vs. vertical (Putnam, 2000; Berman, 1997), heterogeneous vs. homogeneous (Portney and Berry, 1997; Stolle, 1998), and formal vs. info rmal (Minkoff, 1997). Some also argue that social capital is determined by the size and volume of social networks (Ihlen, 2005, p494). In addition, social capital can be an alyzed not only at the level of the individual, but also at the macro level of groups, societies, or nations. Scholars in the field of social capital have their own ways of viewing or measuring social capital. For Putnam social capital is more likel y to be based on horizon tally organized formal social networks, but for Newt on (1997, p.582), social capital is more likely to be based on informal social group networks. For Krishna (2 000), cognitive elements of mutual collectivism are different from the systemic structures that he lp such mutual actions (Bastelaer and Grootaert, 2002, p.19-22). There is no theoretical agreemen t among scholars on the meaning of social capital, but an increasing the numbe r of studies on social capital m eans that the theories will get more sophisticated and specific. All possible macro-level political consequen ces depend on the dynamics of various social capital issues on the micro-level of individuals. The field of social capital can be split broadly into two schools based on the level of approach (whether research focuses on individuals or groups) and the direction of a pproach (whether research fo cuses network intensiveness, extensiveness, trust, or other substantive elements). Social networks: theoretical unde rstandings & empirical evidence At the micro level of the individuals connectedness: Just as the definiti on and dimensions of social capital are controversial, the theme of same level social networks has been explored through different theoretical perspect ives. Social networks at the in dividual level have been seen through the effects of psychologi cal group attachment or indivi dual social inte raction with people who interact with each other in their daily lives. According to Conover (1988) and

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23 Chong (2000), the degree to which social networks matter in political thinking differs based on how much each individual likes or dislikes certain groups and how much each individual identifies himor herself with certain gr oups (Conover, 1988, p.54). Some scholars, like Huckfeldt and Sprague (1993), however, defined cont extual concepts of social networks through individual physical interacti on rather than cogniti ve attachment and examined the personal political choices according to the situational contacts. Huckfeldt and Sprague argued that individual political preference is not a simple function of individual characteri stics alone, but rather the comp lex product of an individuals own characteristics and predispos itions of other surrounding indi viduals (p.366). Individuals political lives extend far beyond self-evaluated partisanship. People place themselves in neighborhoods, churches, workplaces, clubs, and a ssociations, they make these situational choices for good reasons on rational grounds [a nd these] multidimensional social structures and exposures carry a political implication (Huckfeldt and Sprague, 1993, pp.374, 380). This approach emphasized the effect of soci al networks on individual level choices. Conover was talking about peoples attachments to groups at large, for instance; Blacks, women, and Catholics, rather than groups that pe ople actually see and talk with, which is what Huckfeldt and Sprague referred to. Members of va rious groups are often likely to pay attention to different things in the same political context. Individuals tend to evaluate others according to different criteria, and they will adopt differe nt perspectives when making judgments and decisions on policy matters. Group identifi cation [fundamentally] sh ape[s] how people look at politics [because] group identifiers differ in thei r viewpoints, it is expe cted that they will evaluate public policies differen tly and subsequently assume distinct positions on issues (Conover, 1984, pp. 763-4, 770). Conover argued that an emotional closene ss to certain social

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24 groups initiate political thi nking on issues where the group cues are explicit and salient (1988, p.61). Social attachments to groups or communitie s serve to form political thought and behavior. Individuals cultural norms, values, and group identification wi thin a given society accumulate in the political process over time. Conovers theoretical model (1988) demonstrated successive information-filtering processes in long -term political attitude formation through social networks. According to this model, issue pr eference is established in the following order: accumulated social, biological, and cultural f actors influence individual perceivers characteristics; these particular characteristics influence perc eptions of outgroup, ingroup, self, and/or policy related informati on; these perceptions influence evaluation of the issue through identity associations; and the evaluations determine their issue preference (p.59). As another example of individuals psychol ogical social attachments, Chong showed political conflicts caused by resistant social connectedness against rational choice through residents of a Texas community who needed to decide whether to compromise their long-term emotional attachment to a political culture in exchange for business development that would create jobs and fuel the local economy (Chong, 2000) His study proved that the strongly tied, long-term group networks among the people of the community constrained their rationa l political choices and shaped the pattern of thei r regional economic development. Individuals micro levels of social construction define their boundaries of political information and perceptions on political issues (Huckfeldt, et al., 1995). Several studies have illustrated different processes of policy perception and decision making using ranges of particular social mobilization at the individual level, be they ideological bonds, socio-economic ties, or just physical closeness within a give n political boundary (Baker 1990; Erikson, McIver,

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25 and Wright, 1987). Individuals who share relevant ideas within a group share similarities in their political issues, and thereby provide guidan ce for policy makers by expressing homogeneous desirability (Schneider and J acoby, 2005, p.377). Therefore, levels of network intensiveness, such as how actively, strongly, or intensively an individual engages in social networks, determine various policy attitude s accordingly. Such community or individual level-focused government approaches can be an efficient wa y to deal with public issues (Coppola, 2000). At the macro level of group associations: Although there are a significant number of studies looking at social networks at th e individual level of differences in predicting poli tical attitudes and behaviors, there are more no ticeable studies on social networ ks at the aggregate level of group and political entities. In predicting po litical outputs, these macro-level theoretical approaches to social networks look at the phen omena through a cultural, societal, or political group rather than through the individual. These theoretical approaches portray social influence as the product and residue of close and intim ate ties, and thus it becomes a precondition for political influence (Huckfeldt, Beck, Dalton, and Levine, J., 1995, pp.1025-27). Several studies have found that different gr oup memberships initiate different levels of political attitudes and different forms of political involvement. For instance, members of unions, farm associations, Greek associatio ns, and church groups are less likel y to be tolerant to a variety of policies than non-members. And union member ships influence individual members political attitude more strongly than general commun ity-type organizations (Cigler and Joslyn, 2002, p.15). Kwak, Shan, and Holbert (2004) also observed th at association with religious attendance, public attendance, or informal socializing resu lts in different degrees of influence on civic engagements. Among those three types of asso ciations, public attendance is the strongest

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26 indicator for active civic participa tion. Letki (2004) looked at th e three distinct dimensions of social organizations, professional/lifestyle organizations, and labor organizations during democratization in East-Central Europe. He fo und that community associations are the most significant indicator among the thre e dimensions of social intera ctions for active democratic activities. Additionally, group-level political tendencies were explored through various group-based applications. A previous exit poll survey pred icted political candidate popularity by assuming group voting. Individuals w ithin a group, who share norms a nd beliefs based on ethnicity, gender, or religion, invariably have a tendency to like or dis like a political candidate (Conover and Feldman, 1984). For example, religious attach ment is an important predictor for electoral political activities and political protest activities. Strong religious tradit ionalists are against liberal political movements such as gay rights an d pro-choice legislation, so people in this group tend to hesitate to vote for liberal Democratic Party candidates. Furthermore, while there are some regional variations, White Americans are more likely to be religious and less likely to engage in high-level political activity or protests, and they are more conservative than ethnic minority groups on social and morality public issues (DeLeon and Naff, 2004, pp.703 and 712). Different types of so cial networks and their standards for belonging relate to each other in different ways of political tende ncy and preferences (Stolle and Rochon, 2001). Socio-economic categories representative of in dividual economic and social status also create homogenous policy attitudes. Accordi ng to Thomas Nelson and Donald Kinders study, welfare beneficiaries as a group te nded to interpret government s upport in terms of morality, and have highly positive attitudes toward government assistance. General Americans attitudes on

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27 poverty policy, federal spe nding on AIDS and affirmative action in employment and educational settings reflect the degree of their importance to different social groups and the broadness of social engagements. Group sentimen t is a primary ingredient in public opinion (Nelson and Kinder, 1996, p.1071). Political ar guments about group images that spotlight certain social groups often activate peoples ster eotypes and prejudices towards the spotlighted group. Such group sentiments then become the ma in clue for people to evaluate group-relevant public policy in terms of the co st and effectiveness of the propos ed policy or the principles the policy might advance (Nelson and Kinder, 1996, p.1071-1074). Different cities choose particul ar types of social services or civic inter-group programs based on race, religion, or socioeconomic status. Depending on the particular groups and social networks that exist within a pol itical boundary, policy makers need to devise different tools to reflect what the public wants. Such a community composition is crucial for political processes and the aspect is adopted in several studies on government in which the research proves that community-friendly approaches are a cost-effici ent means for public development (Walsh, 2006). Moreover, James Gibson (2001) emphasized the roles of heterogeneous weak social ties, which are relationships beyond family boundaries, durin g democratic transitions in Russia, Spain, and Hungary. He found that the larger the heterogeneous social networks are, the more easily they benefit the social and po litical movements at the nationa l level (p.59). In addition, the extensive social location of groups in issue networks affects the information available to them about potential partners and the de sirability of particular alliances Groups of people in ranges of social networks have aggregate policy desirabili ty and a better level of policy efficacy than people outside of certain networ ks. Interest groups especially, are formed through previous

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28 interpersonal networks, and the ne tworks become the basis of alli ances to build a route of access to the government (Heaney, 2004). Casey (2002) found a moderate correlation betw een social capital and states economic performance. Putnam (2000) also added empiri cal evidence to the literature by proving that broad social networks are positiv ely correlated to the macro level of state outcome in low crime rate, high economic prosperity, and a better chil d welfare system. Hetherington and Globetti (2002) argued that general reciprocity through multip le social networks is a significant indicator of state government performance by establishi ng greater accountability and efficiency for government (p.272). Margit Tavits (2006) measured the link between extensive social networks and government performance by comparing Germany a nd the U.S. Her approach targeted the national levels of social capital and the governments levels of policy activism and administrative efficiency. The study found that fo r both countries the level of trust, volunteerism, membership, and informal socializing were pos itive indicators for policy activism although they did not matter for administrative efficiency. Overall, the factor of how broa dly or extensively an individua l engages in types of social networks determines homogeneous political at titudes among members of a group, or groups, and influences the macro-level of government policy outcomes. These approaches provide important tools for the present study to observe social cap ital across different levels of single or multiple group networks at an aggregate level by creating theore tical connections at multiple levels of social and political interactions. General social trust: Theoretical understandings & empirical evidence At the micro level of individual confidence on general members of society: Unlike general social networks, trust is a socially oriented emotional tie that creates a collective identity

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29 (Braithwaite and Levi, 1998, p.378). It is a posit ive expectation on others in doing particular things based on belief or knowledge rather than as a category of action and behavior (Cook, 2001, pp. 7, 10). More importantly, trust is a c ognitive process of moral commitments and expectations (Coleman, 1990; Putnam, 2000). In so cial life, trust sources include familiarity, reliable information, and generalizations based on experience with similar actors, on-going interactions, and confidence in the constraints provided by institutions (Braithwaite and Levi, 1998, p.376). This multi-functional trust is dealt with as another component of social capital in political applications in many studies. There have been some disagreements about leve ls of trust, however. Recent scholars tend to narrow down concepts of trust for their own purpose of study. For instance, Uslaner conceptualized trust as in st ranger, not as in people we already know (Uslaner, 2004, p.502). Other scholars defined trust contextually by saying that A trusts B to do X (Braithwaite and Levi, 1998, p.78). For the former scholar, trust is a general and broad concept of cognitive reliance, but for the latter scholar, it is a very specif ic psychological status in a particular context. Generally, people with a higher social status and who belong to the ethnic majority tend to have a higher level of social trust than hav e-nots and ethnic minorities. In addition, people from big cities are less likely to trust other people than people from small towns. These tendencies are not inherent char acteristics but accumulated from mistrustful experiences with crimes and lies among people who are in a disadvantaged stage in a large, anonymous group. Such a low level of social trust easily generate s vicious spirals at th e aggregate level of the society (Putnam, 2000, p.138). At the macro level of general social trust: There are also scholarly approaches at the aggregate level of trust. In terms of theoretical approaches, trust is proven as a core concept in normative

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30 social and political practices and it is suggested as an alterna tive solution for problems in those practices (Cook, 2001, pp.307-20). Trust also often se rves as an interesting element for smallersector politics at the local or community level. One study inve stigated neighbor hood effects in Texas using trust as a mediator in welf are policy efficacy. The study found that the neighborhood associated with lower trust had lowe r collective efficacy in health and education policies and higher degrees of fear of crime and racism. Trust was a key factor for the community to be betteror worse-off as a resu lt of the social progra ms. Therefore, this neighboring effect directly influe nces a states particular policy direction (Franzini, et al., 2005). Some argue that trust in govern ment and political systems be nefits democratic political processes. Others argue that i ndividual trust towards people with whom they have only little or no direct interaction contributes to collective action. Theo retically, social trust is different from trust in institutions and political authorities. Social and political trust may empirically relate to each other, but theoretically should be kept di stinct (Putnam, 2000, p.137). Some scholars argue that with population groups and greater struct ural differentiation, a great number of social relationships are based on cognitive or general trust rather than on emotional or specific trust (Lewis and Weigert, 1985, p.973). There are various ways to conceptualize trus t based on where trust activates, the persons who are the targets of trust, and how fluctuating th e trustful environment is. To explore trust in its multiple levels of political attitudes and citizenships, we may need to adopt general social trust or generalized expectancy as the core conc ept; to understand personal interactions we may need to take specific emotional or institutional tr ust into account. Regardless of whether trust is based on emotional ties among primary groups or cognitive rationality among more extensive

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31 secondary groups, the level of tr ust contributes to optimistic views towards social systems and allows cooperation to be more easily recogni zed and proceeded (Putnam, 2000; Scholz, 1998). Levels of general trust fluc tuate throughout political events Schmierbach, Boyle, and McLeod (2005) observed that increased levels of general trust among Americans after the terrorist attack of September 11th encouraged peoples political participa tion and strengthened conservative policy preferences and ideology among American citizens, meaning that American citizens were more likely to support President Bu shs conservative policie s and religious values (pp.333, 341). The trust level among a general group in an emergent national situation determines or creates different political environments for the po litical actors. During the peak of a trust mood, people were more likely to coopera te with national-level decisions and evaluate the outcomes of government policies in a positive way. Such a su rge in social connectedness creates active and cooperative political attitudes among citizens, at l east for a short time (Schmierbach, Boyle, and McLeod, 2005). Another study on 31 non-metropolitan Michig an residential units found that the differential ability of political sectors to realize mutual trust and solidarity was a major source for measuring residential units variations in determin ing their political needs. Therefore, several policy recommendations were endorsed based on re sources of social connectedness, especially trust, which could help to facilitate collectiv e efficacy for improving c itizens life quality in specific political sections (Cancino, 2005). The macro level of general social trust w ithin political boundaries is highly related to social equality and active government actions fo r the citizens. John Scholz and Mark Lubell (1998) found that both types of trust in governme nt and other citizens provided conditions for a

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32 collective solution, thus we re more likely to lead to a better outcome such as tax compliance. According to Bo Rothstein and Eric Uslaner (2005) countries with a high level of social trust have higher levels of economic equality and more opportunities for i ndividuals within the political boundary, and their governments are more active in thei r social policies, such as education and health. Overall, there are specific tene ts of social networks and tr ust, and they not only share some commonality and reinforce each others soci al and political functio ns, but also lessen the function of other tenets. Acco rding to Gibson (2001), members of social networks are more likely to trust others and think that others trust them. Political cooperation is not likely to take place among perfect strangers. In addition, general social networks help convert strangers to friends (p.61). Social trust and civic engagement are strongly correlated; the greater the density of associational membership in a society, the mo re trusting its citizens. Trust and engagement are two facets of the same underlying factor social cap ital (Putnam, 1995, p.73). Yet as Hero (2003) argues, a hi gh level of social capital, esp ecially trust from particular groups, can also reduce the positive political outco me for the minority groups. Different social networks are activated by different issues and situations (Shore, 1993). Especially, particular social groups that individuals ar e more attached to or more deeply controlled by, determine their political preference. Policy at titudes are usually determined by personal orientations (Saris and Sniderman, 2004, p.95). Therefore, specific catego rizations and different consequences of various levels of trust and different aspects of general networks need to be considered in order to conduct more consistent research.

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33 Functions of Social Capital The Positive Consequences of Social Capital The majority of scholars present the positive impacts of social capital, assuming that individuals collective engagement in public sectors is cr itical for effective economic and societal management and political development, and that interpersonal networks are necessary for satisfactory personal lives in both moralistic and practical benefits. Social capital is particularly more helpful for general social policies over other political or economic policies (Frank, 2003, pp.3-6). However, there are two opposite spill-over effects of so cial capital, which can be meaningful in varying degrees along a positive-negative continuum (Hazleton and Kennan, 2000, p.84), though it is theoretically and em pirically more likely to veer toward the positive side. Lets discuss the optimistic understanding of social capital first. At the micro level of social capital: Social capital makes more knowledge and information available for individuals in a ne twork web, and thus helps individua ls to be more efficient to cooperate with and behave among other members of a society. Thus, those with high social capital are more likely to be hired, housed, heal thy, and happy than others who have no social connections, thus have more possibilities to relive from welfare program (Woolcock, 2001, p.68) One study found that locally-ori ented businesses, civic orga nizations, and churches can have positive effects on individu als personal satisfactions (Tol bert, 2005). The study also illustrated how a communitys ability to satisfy re sidents in terms of school systems, sanitary issues, or safety is highly related to civic involvement and active community networks (Keele, 2003). For instance, social capita l within a company helps indivi duals develop speed training, improve employee morale, and enhance loyalty to the company (Putnam, 2000, p.320). In

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34 addition, general interacti on helps individuals phys ical and mental health and wellbeing within a given community (Putnam, 2000, pp.288-89) Ethnic networks often work as employme nt networks and business connections, especially within immigrant groups. For instan ce, Chinese immigrants often dominate certain services or industries through highl y developed internal networks in big cities. Likewise, Korean business owners tend to initiate their careers through family connec tions or support. Thus, social ties within certain groups help individuals economic wellbeing (Putnam, 2000, p.320). Beyond ethnic group boundaries, i ndividuals in a society tend to obtain jobs through the people around them. In fact, church groups and neighborhoods are th e very foundation for individuals social and economic activit ies (Putnam, 2000, p.321). Highly committed neighborhoods stabilize family lives by reduc ing incidents of misbehavior among family members. If parents know other parents with ch ildren attending the same school as their children, kids are more likely to be actively engaged in class. Furthermore, caring neighborhoods reduce drug use and teenage vandalism (Putnam, 2000, 314-15) Allan Cigler and Mark Joslyn discovered that the extent of group affiliations is positively correlated with political toleran ce towards social policies. Indi viduals who are more involved in voluntary associations tend to unde rstand different viewpoints with greater ease. Although some variances according to group-t ype exist, memberships in mu ltiple group associations also increase political tolerance towards various social issues (Cigler and Joslyn, 2002). In sum, at the micro-level, social networ ks and trust enable community members to contribute to society as a whole. More im portantly, social capital provides non-economic solutions to any social issues (Portes, 1998)

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35 At the macro-level of social capital: At the macro-level, intertwined networks and aggregate trust create healthy communities in terms of soci al and political improvement. Social capital does not work by one direction flow. Rather, it is achieved through links and relationships of two way flow between top and bottom (Glaes er, 2001, pp.39-40). Putnam argues that social networks among citizens act as a ci vic virtue in civil society and contain a set of predetermined connotations of economic efficien cy and political benefits at the macro-level of state and national politics. The ag gregate level of a communitys abilit y to conduct collective activities is positively related to the successful ness of all governmental-level of social, political, economic programs (Putnam, 2000). In Putnams comparative study of Italian re gional governments, he found that successful regional political entities had stronger civic engagements, inte grity, and more active community organizations compared to the failed other local governments. Such civic involvements, social solidity, and networks are accumulated as economic and political assets, and thus can help political systems be more successful and economic development more efficient (Putnam, 1993). Social networks and associations help citi zens resolve collective problems easily, allow communities to advance smoothly, develop character traits that are good for the rest of society (Putman, 2000, pp.288-90), foster robust norms of reciprocity, facilitate communication, improve the flow of information, and stabi lize collaboration (Putnam, 1993, pp.173-74). In addition, levels of social networks among citizens bring minorities into society, and as a result, help ensure a more inclusive and flourish ing democracy (Wolbrecht and Hero, 2005). More specifically, studies show that social networks are re levant to several types of public policy, such as education a nd health programs. In particular, information sharing, lower transition costs, low turnover rate s, and greater coherence of ac tion are optimal situations for

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36 maintaining social progress with minimal effo rt and governmental co sts (Cohen and Prusak, 2001, p.10). The existing social networks save a lot of cost for the government to build new routes or frameworks to allo cate resources to the societ y (Productivity Commission, 2003, p.56). Social capital itself produces collective well-being, enhances confidence in political institutions, naturally reduces crime rates, and accelerates government pe rformance (Brehm and Rahn, 1997, p.1000; Coleman, 1988; Fukuyama, 1995; Knack, 2002). Furthermore, extensive civic engagement from citizens provides free spaces for political discussions and the sharing personal id eals that would direc tly influence decisionmaking processes (Barakso, 2005). As an exampl e, the city of Omaha, Nebraska actually provided a civic engagement program that enco urages neighborhood associations to register formal documents and get involved in several c ity projects in order to deal with community issues more effectively. All city issues, su ch as natural disaster emergency management, landscaping projects, clean water, and energy problems, have been handled with a great efficiency in a shorter time period compared to other cities local government management processes without such devices (Fahey and Landow, 2005). Another facet of social capita l, interpersonal and societal trust, also enhances the democratic process (Almond and Verba, 1963). Demo cracy is an institution that allows citizens to make judgments not only about po litical platforms but also about the trustworthine ss of people. Trust in democracy allows people to believe in each other and is ther efore necessary for an effective political environment (Braithwaite and Levi, 1998, p.69). Some argue that social assurance and confidence between individuals and institutions is an essential element to building a civil society, creating invisibl e ties between general public and social institutions (Inglehart

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37 1997; Mishler and Rose, 1997), as well as a shared set of values, virtues, and expectations among members of a society (Beem, 1999, p.20). Robert Axelrod (1984) showed how repeated trust among actors benefit given political structures and maximize resource s through empirical game exercise s. Trust reduces the social and economic complexity caused by rational predictions of individuals interactions. Rather than calculating rational outcomes, trus t creates a simple and confiden ce basis (Lewis and Weigert, 1985, p.969). Social trust contributes to social equality and encourages government actions on education, health care, labor-mar ket opportunities, and gender equal ity (Rothstein and Uslaner, 2005). The Negative Consequences of Social Capital There are a significant numbers of scholars who remain suspicious about the potentials of social capital. Depending on th e different properties of social networks and trust, whether relationship boundaries are exclusive or inclusive, or the structure of a relationship is hierarchical or horizontal, there are possi bilities of negative effects of social capital (Dasqupta and Serageldin, 2000, p.47). In addition, po litical conservatism within elements of social capital can also be a negative impact on liberal policy applications (Portes, 1998). At the micro level of individual complexity: Social capital can disturb stable interpersonal activities and does not always benefit every si ngle member of a soci ety. How strongly and broadly an individual interacts with other peop le in a society determines the degree of the personal level of social capital. Personal ranges of so cial interrelationships also vary, leading to variations in emotional expecta tions and physical behavior boundari es. Some individuals tend to take advantage of the high level of social cap ital around them, but others often face disappointing outcomes from interpersonal relationships because of unwritten rules about reciprocal exchange and different levels of social capital between individuals.

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38 Due to the various levels of social capital in different individuals and groups, it is hard to predict expected outcomes of group activities. Individuals in a society in which there is a high level of social capital can easily violate expected reciprocity afte r they receive benefits. Trust often creates demanding attitudes towards coworkers when completing given tasks, and unlocks responsibility, thereby causing unnecessary conflicts in collaborative works. Unspecified obligations and unpredictable outcomes with a hi gh level of expectation can problematize task completion and make it hard to achieve social stability (Hazleton and Kennan, 2000, p.85). Moreover, individuals with an extremely high level of social capital could be even more seriously disappointed and hurt af ter experiencing betrayal, a nd individuals who have higher levels of trust tend to expect more from others When subjective emotional trust has failed, the emotional outrage can be more disastrous a nd the functional parts of the society become uncontrollable. Therefore, futu re uncertainty about others ac tions and the violation of particular expectations after experiencing betrayals lead indi viduals to become much more distrustful of others than during their initial stage of the intera ction with no trust (Lewis and Weigert, 1985, p.971). Social capital can also create undesirable group attitudes and so cietal tendencies. Individuals in small towns are hi ghly engaged in their community life, but they are less tolerant of differences and diversities (Putnam, 2000, p.352) Because social capital is often easily established by race, gender, and political affiliations individuals within such social networks are less likely to understand people from other societal or political sectors. For instance, small communities and highly committed neighborhoods ar e less tolerant of homosexual teachers and interracial marriages for people of their own communities (Putnam, 2000, p.352-53). A strong

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39 and narrow level of social capit al can constrain an individual s freedom to choose (Schudson, 1998). At the macro-level of political, so cietal and economic shortcomings: Discussing the NIMBY (not in my backyard) movement and the Ku Klux Klan activism of racial discrimination, Putnam admitted that networks and the associ ated norms of reciproc ity are generally good for the inside of the network, but the external e ffects of social capita l are by no means always positive (Putnam, 2000, pp.21-22). Intensively conn ected social networks or interest groups distort governmental decision making and trigger political polariz ation and cynicism (Putnam, 2000, p.340). The density of social networks and bondi ng determines the capacity of specific reciprocity and solidarity. Putman argues that inclusive networks generate broader identities and reciprocity thus allowing for the diffusion of information and economic efficiency, but tightly bonded networks reinf orce exclusive identities and homogeneous groups undergirding specific reciprocity thus creating not only st rong in-group loyalty bu t also strong out-group antagonism (Putnam, 2000, pp22-23). Kraign Beyerlein and Jone Hipp (2005) found that strong bonding networks among Evangelical Protestants led to a greater percentage of crime rates, while weak-bridging bonds between Protestants and Catholics reduced crime rates affiliated with those religious social networks across nearly all U.S. counties. In dividuals ability to build social support is constrained by their social bondi ng (Sachser, in press). Rodney Hero (2003) is one of the scholars w ho challenge fully optimis tic views of social capital on specific political sectors of public policy. He argues that the level of social capital can magnify inequality among society members. At st ate-level politics, Hero saw that rich social

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40 capital benefits the racial majority but isolates th e racial minority. States with high levels of trust also tend to yield worse policy outcomes that dir ectly address racial equality for minorities, such as low-income black populations within a given political sector (Hero, 2003). Although current public po licies utilizing social capital, such as encouraging informal relationship and engaging in soci al activities, have a great deal of benefits, the uncertainty of social capital, the requirement of multiple rein forcements from multiple actors, and flexibility based on localism make such policies much more difficult to apply to multiple situations in an uniformed way, preserve possible effects, and meas ure the potential problems. Therefore, there needs to be careful adjustment and design for soci al-capital oriented publi c policies (Productivity Commission, 2003, pp. 58-60). In addition, policie s which strive towards social order and cohesion have the potential to lose individual freedom and au tonomy along the way (Franklin, 2003, p.352). Previous scholarly research tells us that so cial capital can have a number of different meanings and serves as multiple causes and result s in the political arena. More specifically, social networks and general social trust have different elements of social capital; and the level and range of social engagements are different dime nsions of social networ ks. Social capital has various ways of influencing policy attitudes and po litical tendencies, and the effects can be both positive and negative. Considering the variet y of policy types, my study assumes that individuals attitudes towards va rious types of policies may be influenced by different social surroundings or connectedness of diffe rent degrees. Various levels of social trust and social involvement filter individuals particular asp ects of political information differently and determine levels of assessment to political info rmation. Utilizing previous scholarly research and arguments stating that differe nt aspects of social capital af fect different policy preference

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41 and further induce policy choices, I explore the relationship between specific elements of social capital and particular policy atti tudes. I also attempt to deve lop reliable patterns of policy tendency using multiple dimensions of social capital.

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42 CHAPTER 3 HYPOTHESES AND THE PERSPECTIVES As seen in the previous chapter, there are significant interactions between individuals policy perception/preferences and th eir daily interactions with othe r members of a society. This study examines individuals policy beliefs that woul d be triggered by social elements within their interpersonal lives rather than pragmatic policy pr ocesses or policy outcomes. Previous research found significant but varied correlations between social capital and specific types of public policy consequences. For example, Putnam (2000) showed that states with intensive social networks tended to have bette r welfare achievement, especial ly for the poor, weak, or disadvantaged people (pp. 297-306, 317) People living where there are higher trust levels and reciprocal community moods tend to have posit ive political expectati ons about governments decisions and policies (Schmierbach, Boyle, a nd McLeod, 2005), feel less of a necessity for government actions (Wood, Owen, and Durham, 2005), and tend to be more tolerant and understanding of differences a nd diversities (Cook, 2001, pp212-31). Based on some common elements of individuals beliefs toward certain policy type that are activated mainly by different aspects of social cap ital, this study categorizes multiple dimensions of social capital into social ne tworks (intensiveness and extensiv eness) and generalized social trust and also sorts various polic ies into three different policy at titudinal groups. Theoretically, network intensiveness is meant to measure how intensively and exclusiv ely an individual is involved in social networks. Thus, this concept is related to Putnams understanding of bonding. In contrasts, netw ork extensiveness measures how broadly and inclusively an individual engages in social networ ks, thus it is consis tent with Putnams concept of bridging. Lastly, general social trust is meant to measure levels of general belief in people and society. Therefore, general social trust is different from Hardins (200 2) trust built on physical personal

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43 interaction basis or Cooks (2001) specific social trus t on particular target s. Rather, general social trust has a non-specific range of positive perception on people in general. In terms of policy categorization related to social capital, the first category is redistributive types of policy that exclusively helps or enco urages the have-nots (Levy, 1986) (See Appendix B.1). The second type is government activism policies that help overall societal development for the collective public (Rudolph and Evans, 2005) (S ee Appendix B.2). The last type is morality policies that deal with mora lly controversial issues (Mcfarlane and Meier, 2000) (See Appendix B.3). Retrievi ng previous research and logica l rationales, I posited these hypotheses. On Redistributive Policies Previous research has argued that different types of trust have di fferent political and social potentials. Unfortunately, there is no clear answer for the function of generalized social trust on various types of public policies. Individu al levels of generalized social trust can have multiple meanings, and the degrees of trust matter differently (Putnam, 2000, p.136-39). Although there are theoretical a nd empirical discrepancies, some research argues that high levels of generalized trus t facilitate the provision of pub lic goods and provides social spinoffs in the forms of welfare dependence, lower health care expenditures and so on (Productivity Commission, 2003, p. 57). Assuming that the traits of redistributive pu blic policies are consistent with the tendency of trust in terms of benevolen ce, charity, and belief, my study hypothesizes a positive relationship between genera l social trust and supportive attitudes toward redistributive types of public policies. H1.1: Individuals having higher leve ls of general social trust are more likely to support redistributive types of pu blic policies than individ uals having lower levels of general social trust, controlling for individuals de mographic characteristics.

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44 In pragmatic perspectives, social capital in particular, tends to c ontribute to a better outcome with respect to welfare policies. Th rough multiple social networks, people who are well connected are more likely to get greater be nefits from the society, and thus have more chances to be independent from government subsidies (Woolcock, 2001, p.68). In normative perspectives, multiple heterogeneous social memberships widen and enlighten alternative viewpoints about various social and polit ical issues, while limited homogenous group memberships could create isolated or narrow mi nded perspectives (Putnam, 2000, p.341). Based on the broad nature of networks, and its releva nce with supportive attitudes toward helping the poor, I assume the positive relationship between ne twork extensiveness and redistributive policy attitudes. H1.2: Individuals involved in extensive social networks are more likely to support redistributive types of public policies than individual s who have no, or limited social networks, controlling for individuals de mographic characteristics. As Gibson (2001) argues, broade r social connectedness is more important for macro-level political changes or movements than a strong single primary group attachment that often discouraged balanced democratic movements. Indi viduals intensively involved in broader social networks, such as voluntary or religious groups, are more likely to be co ncerned and expressive about overall social equality and well-being. Ho wever, people intensively involved in a limited range of networks with limited perspectives, such as occupational/pro fessional unions, tend to care more about their direct self-interests (B oninger, Krosnick, and Be rent, 1995). In addition, the interpersonal relationship within an intens ive single social networ k such as professional organizations or associations is often tempor ary, formal, weak, and lim ited in the range of socializations possible within the network rath er than being a meani ngful and close personal

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45 interaction (Putnam, 2000, p.87-90) Therefore, my study assumes a negative relationship between a single intensive networ k and redistributive policy attit udes that require the sense of community for the general public rath er than specific interests. H1.3: Individuals intensively in volved in a limited range of social networks are less likely to support redistributive types of public polic ies than individuals who are not intensively involved in any or in multiple social netw orks, controlling for individuals demographic characteristics. On Government Activism As mentioned, social trust is considered dive rse in terms of target objects, degrees, and the effects. For instance, t hin trust is more adequate for expanding individuals personal networks through loose connections and encourages individuals s upportive attitude s towards the various social and political issues of others; more so than does the thick trust of dense and tight emotional attachments and social exchange s (Putnam, 2000, p.136). Thus, the ambiguity suggests many different possibilities for the effect of general social trust on various policy attitudes. Nonetheless, there is evidence that individuals with low levels of trust towards the general society or the public are more likely to rely on public or prof essional services and government support for their necessities rather than their neighbors or the private sector. This tendency has been observed over the last half century in American society (Putnam, 2000, p.144145). In contrast, individuals with high levels of generalized trust tend to keep their eyes focused on their communities and concern themselves only with each other, thus self-interests are served within the community. Therefore, individuals ha ving higher levels of general social trust would tend to be less dependent on governmental social services (P utnam, 2000, p. 135).

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46 H2.1: Individuals having higher levels of gene ral social trust are less likely to support government activism than individuals having lower le vels of general social trust, controlling for individuals demographi c characteristics Individuals who are more invol ved in broader social networks are more likely to be exposed to public issues such as education, en vironment and health, a nd discuss those issues either at the local or national levels. These individuals tend to care more, and voice stronger opinions about governmental policies on those issues (Putnam, 2000, p.51-3) H2.2: Individuals involved in extensive social networks are more likely to support government activism than individuals who have no, or limited social networks, controlling for individuals demographi c characteristics. Politically active individuals are more likely to support government actions although political tendencies vary depe nding on different party identificat ion and the scope of political views. However, occupational/professional unions or networks focus on narrower self-interests; hence, the members of those type s of organizations are less concer ned with general public issues and reluctant to have governmental control over their professional spaces. Overall, members belonging to any organization that has narrower and more specifi c interests or goals are less likely to support governmental activ ism that ultimately targets the benefits of the general public rather than specific interests (Cochran et al., 2006; Putnam, 2000, pp.80-91). H2.3: Individuals intensively involved in a limit ed range of social networks are less likely to support government activism than individuals who are not intensively involved in any or in multiple social networks, controlling for individuals demographic characteristics. On Morality Policies Individuals trusting general so ciety as a whole, and other members of a society tend to dislike governmental intervention in their private lives. Some scholars argue that individuals

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47 who trust people of the general public more rath er their government and political leaders, tend not to be confident about any type of gove rnment-initiated policy (Wood, Owen, and Durham, 2005). Those people believing not only in their sphere of acquaintances but also in general public, tend to avoid any political constraints and are more likel y to be tolerant of minority views. Thus, those people tend not to care a bout, or avoid governmen tal control on personal morality issues such as abortion and gay rights (Cook, 2001, pp.307-20, Putnam, 2000, p.137). H3.1: Individuals having higher levels of gene ral social trust are less likely to support morality based types of public policies than individuals having lower levels of general social trust, controlling for individuals demographic characteristics. As discussed, individuals who are involved in extensive soci al networks are more likely to be exposed to multiple points of view, and t hus tend to be more understanding about different perspectives (Cigler and Josl yn, 2002). For the same logical reason regarding network extensiveness, the study assumes the negative correlation between multiple memberships and supportive attitudes for morality government po licies that somehow constrain individuals freedom to choose their life style. Morality i ssues require a great deal of tolerance toward diversity (Putnam, 2000, p.341). Therefore, exte nsive memberships in multiple networks would reduce the desire for governmental control on individuals lifestyle choices. However, we also need to consider that exclusive membership in a single or limited network can be worse than no membership in any network, in terms of social tolerance. Strong si ngle in-group attachments could lead to little tolerance for out -group differences (Putnam, 2000, p.355) H3.2: Individuals involved in extensive social networks ar e less likely to support morality based types of government regulations than indi viduals who have no or limited social networks, controlling for individuals de mographic characteristics.

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48 As discussed in the rationale for network in tensiveness, people engaging intensively in more than one social network tend to be more to lerant to differences a nd diversity, and are more likely to respect the rights of others (Putnam, 2000, p. 80, 137, 335). Howeve r, social capital can also create undesirable group attitudes and societal tendencies if the social networks are narrowly structured. For instance, indivi duals in small towns are highly engaged in their community life, but they are less tolerant of differences and diversities (Putnam, 2000, p.352). In addition, politically or religiously conser vative people with a limited range of social networks would not be tolerant with societal differences (Sc hudson, 1998), thus dislike in dividuals freedoms to choose and preferring stricter gove rnmental regulations on social morality issues (Putnam, 2000, pp.357-8). H3.3: Individuals intensively involved in limited range of social networks are more likely to support morality based government regulatio ns than individuals who are not intensively involved in any or in multiple social netw orks, controlling for individuals demographic characteristics. In summary, based on previous research on social capital and various political implications, my research presumes that genera l social trust would enc ourage positive attitudes toward redistributive government policies that help socially disadvantaged people, but induce negative attitudes for other types of government interventions in both public and private spheres. The factor of how extensively, or broadly, pe ople were involved in so cial networks would positively influence redistributive and government act ivism policies that create social equity and public goods, but negatively influence policy att itudes for government regulations on morality policies. Lastly, however, people who engaged in single or limited social networks intensively would be less likely to support both redistribu tive and government activism policies, but more

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49 likely to support morality government policies th at somehow constrain social diversities and differences. Table 3-1. Hypotheses Matrix General Social Trust Extensive Networks Limited Intensiveness Redistributive Policy + + Government Activism + Morality Regulation +

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50 CHAPTER 4 METHOD Data To test the hypotheses, my study uses the 2004 General Social Survey (GSS) data gathered by the National Opinion Research Center through national probability sampling.1 The GSS was designed to survey various social issues and political attitudes at the individual level, and has repeated many core questionnaire items and question wordings in order to facilitate time-series studies. The GSS 2004 data were gathered through Co mputer Assisted Personal Interview (CAPI) using a national full probability sampling. The medi an length of the inte rview was about one and a half hours. The participants were English-sp eaking persons 18 years of age or over within the U.S. The sample size was 2,812 and weighted for the Black subpopulation to adjust overall ethnicity proportion in the U.S. The 2004 GSS asked more detailed questions about individuals civic engagements and their political attitudes. Beyond GSS general ca tegories of demographics, media consumption patterns, negative life events, religious transforma tions, daily religious practice, an experiment on measuring immigration status, altruism, an experiment on measuring alcohol consumption, attitudes towards guns, social ne tworks and group memberships, sexual behavior and genetic testing, the role of heredity, and stress and vi olence in the workplace, the 2004 GSS included the citizenship module, a new series of items collected in the 2004 data. The citizenship module included questions regarding civic and pol itical participation, social welfare policies, efficac y, misanthropy, international orga nizations, political parties, 1 The principal investigators of the 2004 General Social Su rvey were James A. Davis, Tom W. Smith and Peter V. Marsden. These were made available to me by the Interuniversity Consortium for Political and Social Research (ICPSR Study Number 4295). Neither the National Opinion Re search Center, Professors (James A. Davis, Tom W. Smith and Peter V. Marsden), nor the ICPSR are responsi ble for my analysis and interpretation of the data.

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51 political corruption, and the working of democr acy. The questions regarding these categories sought the respondent's opinions on social and political topics such as the environment, government, society in general, the economy, leisur e activities, interperso nal relations, health care, personal philosophy, and ot her moral controversies. As is evident, the GSS is well incorporated with the perspectiv es of this study with reliable ca tegories of different facets of social capital in trust and soci al networks to explore patterns of various policy attitudes. Perspectives of Categorization Measuring Dimensions of Social Capital Social capital is an amorphous concept and has multiple connotations. Some scholars argue that social capital need s to be explored through quali tative methods (Coleman, 1990), while others claim quantitative analysis is the on ly means of measuring social capital (Bourdieu, 1991). As we observed in the previous chapter, there are ongoing debates regarding the levels and dimensions of social capital. Scholars id entify different aspects (or facets) of social capital based on their own theoretical or empiri cal judgment. For instance, as Bastelaer and Grootaert (2002) summarized, social capital can be approached using multiple dichotomous categories of Structural vs. Cognitive, Horizont al vs. Vertical, Heterogeneous vs. Homogeneous, or Formal vs. Informal dimensions. A social tie can be interpreted as any one of networks, roles, rules, life patterns, norms, values, attitudes, or be liefs; thus researchers find diverse meanings of social capital for different indi viduals and social systems. Th us, depending on the definition of social capital used, researchers need to consider possible rationales, imp lications, and functions of their ways of categorizations. My research intends to examine social capita l in a more comprehensive and exhaustive way. I incorporate both theoreti cal understandings a nd quantitative methods in order to explore the concept of social capital. For instance, in the categorization stage of social capital, I adopt

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52 theoretical approaches of several scholars to determine the various implications of the multiple concepts of social capital and to retest previous em pirical evidence. Multiple dimensions of social capital overlap in their social functionality and defini tion (Putnam, 2000). Utilizing multiple concepts of social capital such as netw ork extensiveness and intensiveness, reciprocity, and trust that have been discussed in previous studies, my study measures multiple implications of different dimensions of social capital in polic y attitudes. In order to achieve comprehensive but exclusive measurements of social capital, I sort out distinctive elements such as the difference between social networks and trust, but merge similar elem ents of social capital per se, under network intensiveness or extensiveness that has its own homogenous implications. Previous studies showed that theoretically both so cial networks and trust ar e core parts of social capital (Putnam, 2000), but each has its own functi onal effect on various political perspectives. Therefore, my study keeps core elements of social capital that would main tain their exclusivity enough to be distinguished from each other in co ncept and functionality, but the sum of each category would cover all possible imp lications of social capital. In terms of dimensions of social netw orks, previous scholars argued about the intensiveness and extensiveness of social netw orks. In other words, depending on how broadly individuals engage in and how intensively they participate in social networks, people have different perspectives toward different policies. Therefore, the operationa l definition of network extensiveness is somewhat consis tent with Putnams concept of bridging that connects people inclusively. In contrasts, the operational definiti on of network intensivene ss is consistent with Putnams meaning of bonding th at connects members of a soci al group exclusively (Putnam, 2000, pp.22-3). Network intensiveness and extensiven ess are consistent with the definition of social capital, but clearly distinguished from one another in individuals so cial life patterns. At

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53 the same time, these two are interrelated indica tors that have different impacts on individuals policy beliefs; thus, they should be treated as theoretically distinctive elements of social networks (Granovetter, 1973, p.1361). Therefore, I also keep network extensiveness and intensiveness as separate indicators for the range of social connectedness and levels of intensiveness in social involvement, respectiv ely, that can predict multiple possibilities of impacts on policy attitudes. In the measurement of general social trust, my study targets trust in participants general social lives. There are multi-dimensional conceptualizations of trust based on its relationships with policy attitudes in political processes. Different research programs look at different aspects of interpersonal trust. Social trusts toward ordinary people may need to be differentiated from trust toward governments or politi cal institutions. Empirically, so cial and political trust may or may not be correlated, but theore tically, they much kept dist inct (Putnam, 2000, p.137). In addition, general trust toward the general public is also different from Cooks concept of specific types of trust toward a particular individual in a particular situation ( 2000) or Hardins trust limited to personal relationships (2002). Therefore, my study focuses on interpersonal beliefs toward the general public or members of a given society, namely generalized social trust, primarily in order to test the tenets of trust in the social dimension rather than trust in governments, spec ific institutions, or particular individuals. In other words, trust in this study is inte rpreted as general trust toward ordinary people in their daily social lives. Ra ther than defining trust as a specific or a broad concept of interpersonal belief or as confidence in political leaders or government systems that may be changeable based on individuals given environment or resources, this study explores

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54 general social trust toward ordinary people or society in order to measure only its social components. After considering multiple theoretical frameworks I determine that soci al capital would be explored through two categories of general social networks that physically connect members of a society either in extensive or intensive ways a nd general social trust th at creates common facets of beliefs or norms. My study defi nes general social networks as public sphere interactions. For instance, civic engagement in public affairs, or ganizational activi ties for socialization, voluntary networks for general social improvement, and di versity of social engagements are the main elements of this dimension of social connectedness. General social trust is composed of beliefs toward the general public in the society. The beli ef that other members of the society are trusted, fair, and helpful is among the many m eanings of general social trust. In order to achieve a high reliability a nd validity for each measurement and scale, I adopted measures that have been used in previous studies, signaling them as reliable indicators. In the measurement of social networks, I adopted Putnams measurement of participation level in multiple social networks and Cigler and Joslyn s numbers of networks. Network intensiveness was measured by levels of how in tensively individuals were involve d in given social gatherings such as volunteer work for common issues, political community meetings and others professional associations, religi ous gatherings, and other social and leisure activities (See Appendix A.1.). Network extensiveness was meas ured using the total number of memberships to which each individual belongs (See Appendix A.2.). In measuring general social trust, I utilized three different questions asking individuals levels of belie fs in general society that have been used frequently in previous research, such as Putnam (2000) and Gibson (2001) study on

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55 social trust, and national panel data, such as National Election Studies (NES) and General Social Studies (GSS) (See Appendix A.3.). Using the 2004 GSS data, I first used partic ipation levels in multip le types of political parties, a trade union or profe ssional association, a church or other religiou s organization, a sports/ leisure/ cultural group, a nd another voluntary association to examine individuals network intensiveness in relation to various policy attitu des. The intensiveness of social networks was measured in four different degrees of involveme nt: 1 have never belonged to it, 2 used to belong but do not any more, 3 belong but dont actively participate, an d 4 belong and actively participate (See Appendix A.1.) Empirically, different type s of networks were highly correspondent to each other based on Cronbachs Alpha reliability Score2 (.922) with a single dimension of factor component loading3 ( .854) (See Appendix A.1.). Th erefore, regardless of the differences in various associations, individu als who were involved in any social network at the degree of 4 belong and activel y participate were coded as a group of individuals with high network intensiveness; while i ndividuals who were involved in any network at any degree of 1 have never belonged to it, 2 used to belong but do not any more, or 3 belong but dont actively participate were code d as a group of individuals with low network intensiveness. Furthermore, in order to observe attitudinal differences between individuals who were active in only one type of social network and those who were active in multiple networks, I created 2 Cronbachs Alpha reliability score indicates a coeffici ent of consistency among different variables. High Cronbachs alpha reliability refers to how well variou s different items can be constructed into a single unidimensional scale. A reliability coefficient of .70 or higher is considered "acce ptable" in most social science research (http://www.ats.ucla. edu/STAT/SPSS/faq/alpha.html). 3 Factor analysis is an interdependence test technique. Among multiple factor rotation methods, Oblique principle components analysis that computational strategies have been developed to rotate factors so as to best represent "clusters" of variables, without the constraint of or thogonality of factors was adapted in order to calculate interdependent relationships (http://en.wikipedia.org/wiki/Factor_analysis; http://www.statsoft.com/te xtbook/stfacan.html).

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56 dummy variables of counter-cases for single network intensiveness and multiple network intensiveness. In terms of network extensiveness, regardi ng sixteen different memberships in social, cultural, religious, professional, or political associations, indivi duals were asked whether they had any of those memberships. The membership s achieved a reliable level of Cronbachs Alpha score of .735 and a relatively homogenous factor loading ( .228) (See Appendix A.2) among those different memberships. These categories pr oved to be equally important measurements in terms of network variations, thus I used the to tal number of each individuals social network memberships as a form of network extension to see the influence of network expansiveness on individuals policy beliefs (See Appendix A.2). The number of memberships ranged from 0 to 16 out of total possible number of 16. Thes e memberships exhaustivel y covered all possible social, professional, cultural, a nd religious associations. The higher the score was, the more extensive the individual was in their social ne tworks. Again, for a comparison of attitudinal differences between individuals who had singl e social membership and who had multiple memberships in a regression, I created dummy vari ables of counter-cases for single membership and multiple memberships. In order to measure general social trust, I adopted three questions whether people are helpful or looking out for themselves, whether they are fair or try to take advantage of others, and whether they can be trusted that were asked frequently in previous research. They were measured on an ordinal scale of 1,not helpful, t ake advantage, or cannot trust, 2 depends, and 3 helpful, fair, or trust respectively. Individuals answers to th ese three questions were highly correlated each other based on Cronbachs Alpha of .66 resulting in one single dimension of factor loading ( .735) (See Appendix A.3.). Therefore, I cr eated a single indicator of general

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57 social trust by computing a mean score of three answers for each individual in a range of three ordinal values, low, moderate, and high. Measuring Public Policy Typology My study was designed to investigate the rela tionships between social capital and its effects on policy attitudes. In other words, th e study investigated pattern s of individuals policy attitudes from their social lives that have often been overlooked in previous research. Previous scholarly works have theoretically categorized t ypes of public policies based on their substantive functional characteristics, targ eting sectors, ideol ogy (conservative vs. liberal), or approach styles (good vs. bad or pr ogressive vs. regressive). Based on policy expectations and processes, Theodore Lowi (1964) categorized policies into di stributive, redistributive, constituent, and regulatory types. Peter Steinbe rger (1980) determined categorie s of public policy from possible impacts: he categorized distributive, redistri butive, and regulatory of policies based on substantive impact, adaptive and control based on political impact, areal and segmental based on scope of impact, public goods and private goods based on exhaustibility, and symbolic and tangible based on tangibility (McCool, 1995, pp.183, 229). Cristopher Wlezien (1995) categorized five policy areas of big cities, education, environment, health, and welfare in measuri ng peoples preferences for government spending (p.985). A similar study done by William Jacoby (1994) also observed that public attitudes toward certain types of policies such as welfare policies were qualitatively different from public preferences toward other types of government spending. Jacoby categorized various policies based on program-specific preference in welfare, environment, crime prevention, public schools, science and technology, and defe nse (p.347). Moreover, due to some ambiguity of policy categorizations, some scholars have used a met hodological approach to ca tegorize various policy

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58 types using factor analyses (Let ki, 2004). Each categorization seems to have its own logical rationale to understanding dimens ion of public policy issues. My study explained how individuals social connectedness influen ced their attitudes toward various types of policies in particular. Therefore, based on attitude relevance of various policies that are more likely to be activated by individuals social lives, but different political attributes that were discussed in previous policy typology studies, the study categorized various types of policy attitudes into three areas of redist ributive policies that are related to the social equality and benevolence for the have-nots, government activism that are relevant to the collective public reciprocity, and morality policies that deal w ith attitudes toward government regulations on socially controvers ial issues (See Appendix B). In an empirical process of sorting multiple policy attitude indicators by each category of public policies, my study conducted multiple scaling tests to create a reliable indicator for each type of policy attitude beyond theo retical considerations. Before running any reliability tests, I rescaled all possible policy at titude indicators on a seven poi nt scale to make them more consistent numerically. For redi stributive policy attitude measurem ent, I ran reliability tests on attitudes toward government res ponsibility on reducing income di fference between the rich and the poor, improving standard of living for the poor Americans, and helping paying for medical care (See Appendix B.1.). The three items achie ved a relatively high Cronbachs Alpha score (.674) and have higher factor loadin g components on a single dimension ( .740) (See Appendix B.1.). Therefore, I averaged the three items on a scale of 7 from Government should not/ people should help themselves to Government should he lp and created a single index of redistributive policy attitudes. The higher sc ores indicated more supportive at titudes toward redistributive government policies.

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59 For the government activism measurement, I also ran reliability tests on individual attitudes toward governmental support on public good such as improving & protecting national health, improving national education system improving & protecting environment, and solving problems of big cities (See Appendix B.2.). These items achieved a high Cronbacks Alpha score of .731 and the factor compone nts loaded as a single dimension ( .476) (See Appendix B.2). Therefore, I agai n created a single index of gove rnment activism on range of 7 from too much spent on it/ no government activism needs to too little spent on it/ more government activism needs by averaging these f our items. Higher scores indicated more supportive attitudes for government activism. Lastly, for the morality policy attitude measurement, I intentionally selected the most representative and controve rsial morality policy issues of abor tion and gay issues. As Jacoby pointed out (1994, 2005), attitudes toward different policy issues are not unidimensional. Morality policy issues are more problematic than other types of policies in Jacobys perspectives since they are interrelated with multiple social fa ctors such as their ethnicity, religious beliefs, previous life experience, and so on. Therefore, I kept morality policy attitudes toward the issues of abortion and gay rights separate in my measurement. In order to achieve a more consistent attitude measurement in each issue, I included multiple degrees of questions about legal boundaries for abortion and gay rights. Attitudes toward abortion were asked in degrees of different reasons for defects in babies, womens health, rape poverty, an unwanted child, an unwanted marriage, and any othe r reason. Attitudes toward ga y rights were asked through different aspects of questions, such as w hether the individual would allow homosexual relations, whether the individual would allow homosexuals to teach, whether the individual would allow homosexual to speak, and whe ther the individual would allow books on

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60 homosexuality in the library (S ee Appendix B.3). When I ran tests on these items, abortion items achieved a high Cronbachs Alpha score (. 901) and relatively good factor loading on one of component scale ( .584) (See Appendix B.3-1). Gay ri ghts items also achieved a high Cronbachs Alpha score (.793) and we re loaded in one dimension ( .605) (See Appendix B.3-2). Therefore, I was able to create two attitudinal scales on abortion and gay rights policy attitudes on a seven point scale from no allowance/ govern ment regulation to allowance/ individual choice for morality policy. Higher scores mean t more support for individual choices and lenient government morality policies on abortion and gay rights. Conditional Factors of Demographics Demography is a crucial factor in individua ls shared experiences and their manner of thinking and interpretation. Where you go and how you interact with other people often determine who you are. Therefore, it is neces sary to find a direct causation between the following demographic factors. For instance, being a female, head of a single household, of lower socioeconomic status, and social elem ents such as networks of people around the individual, interacted in predic ting a single moms policy beliefs and preferences. Hero (2003) presented ethnicity as the core demographic fa ctor in relation to general social trust, Hetherington (2001) discussed et hnicity and socioeconomic stat us as it related to policy perceptions, and Jacoby (2005) had considered party iden tification as an important interacting factor in attitudes toward government spending in multiple types of policies in his series of related studies. Classical demographic variables in politic al and social studies, such as party identification, gender, education level, age, income, ethnicity, religi osity and geographical locations were controlled or used as conditional fa ctors in the main analyses. Party identification was coded on a seven point scale from strong Demo crats, weak Democrats, Independents near

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61 Democrats, Independents, Inde pendents near Republicans, w eak Republicans, to strong Republicans. Republicans recorded higher valu es in party identific ation. Ethnicity was categorized into two categories, the majority (v alue ) and the minority (value ). White people were coded as an ethnic majority and ethnic minorities were comprised of all Asians, Blacks, Hispanics, Indians, and other mixed raci al groups. Religiosity was categorized in an ordinal manner of not religi ous, not very religious, s omewhat religious, and strongly religious. Thus, higher values in religion indicated stronger relig iosity. Income was coded in ordinal values of 12 from income less than 1,000 (1) to more than 25,000 (12). The raw numbers of years of education and age were used in num eric scales in predicting policy attitudes. However, numeric variables of education, age, a nd income were recoded in ordinal scales for descriptive analyses in order to see them conveniently in the pr eliminary stage of the analyses (See the values in Tables 5-5, 5-7, & 5-13). In terms of geopolitical categorizations, I us ed the rationales of political sociologists assumptions on regional variety with in the large scale of the U.S. Regional characteristics have been accumulated over time through all political, economic, and cultural experiences and assets. Overall, New England and Mid Atlantic areas ar e areas with a high conc entration of industries and have higher levels of academic circumstance; the South has a slower pace of life but strong southern identity under warmer weather and mo re retirees; the Midwest is a more diverse cultural and political intersecti on; the Southwest is more likely to be dominated by Mexican cultural heritage with less resources; and the West is culturally very diverse, thus tends to be more tolerant (Clack, Targonski, and Morgan, 19 97). My study assumed that these different regional circumstances were reflected in individu als policy attitudes.

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62 The regions were categorized into nine di fferent groups of New England, Middle Atlantic, Eastern North Central, West North Central, South Atlantic, East South Central, West South Central, Mountain, and Pacific. This categorizati on has been used continuously in previous research such as NES or GSS time se ries panel data, thus I ad opted it into my study. There were obvious similarities among states within and differences between states that belonged to different geographical categories. In order to control the regi onal variance of social capital in predicting individuals political attitudes, I assigned Putnams social capital index4 to each state and averaged states scores w ithin each region of New Engla nd, Middle Atlantic, East North Central, West North Central, South Atlantic, East South Central, and West South Central, Mountain, and Pacific5. Based on these scores, I created a dummy variable of regions with low social capital in order to see a statistical diffe rence between those region s and regions with high social capital. Regions with high social capital in cluded New England, North West Central and Mountain, and the rest of regions were coded as a low social cap ital region. The dichotomous region variable was incorporated into regr ession analyses as a control variable. 4 Using 14 different indicators of 1)Number of club meetings attended last year, 2)Number of community projects worked on last year, 3) Number of tim es entertained in home last year, 4) Nu mber of time volunteered last year, 5) Mean response to "I spend a lot of time with friends, 6) Mean state response to "most people are honest", 7) Mean percent that served on local committee in past year, 8) Mean percent that served as officer of club or organization, 9) Mean percent that attended meeting on town or school a ffairs, 10) Mean number of nonprofits per capita, 11) Mean number of group membership, 12) Mean response to "most people can be trusted", 13) civic and social organization per 1000 people 1977-1992, 14) Mean presidential turnout 1988 and 1992, the index was created by the average of the standardized scores. The scores are identical to the factor scores from a principal components analysis of the 14 component variables (Putnam, 2000, p.487) 5 New England is comprised of Maine, Vermont, New Hampshire, Massachusetts, Connecticut, and Rhode Island; Middle Atlantic is comprised of New York, New Jersey, an d Pennsylvania; East North Central is comprised of Wisconsin, Illinois, Indiana, Michigan, and Ohio; West North Central is comprised of Minnesota, Iowa Missouri, North Dakota, South Dakota, Nebraska, and Kansas; South Atlantic is comprised of Delaware, Maryland, West Virginia, Virginia, North Carolina, South Carolina, Georgia, Florida, and District of Columbia; East South Central is comprised of Kentucky, Tennessee, Alabama, and Mississippi; West South Central is comprised of Arkansas, Oklahoma, Louisiana, Texas; Mountain is comprised of Montana, Idaho, Wyoming, Nevada, Utah, Colorado, Arizona, and New Mexico; and Pacific is comprised of Washington, Oregon, California, Alaska, and Hawaii.

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63 In addition, to observe the varying influences of regional social capit al on policy attitudes, I created another dichotomous variable of high and low social capital regions using only six regions, and excluding the three other regions in th e middle range of social capital, according to Putnams social capital index. Again, New Engl and, West North Central, and Mountain were categorized as a high social capit al region; South Atlantic, East South Central, and West South Central were coded as a low social capital regi on; and East North Centra l, Middle Atlantic, and Pacific were excluded in order to observe the conditional effect of high and low regional social capital more clearly. Analyses The study reported three sets of analyses. In a preliminary analyses, I measured the correlation between demographic factors and so cial capital to see how those demographic variables were related to indivi duals social connect edness and then controlled them to see a whether there were clear inter actions between social capital and policy beliefs. In the second set of analyses, the study cons idered how the dimensi ons of social capital related with one another by su mmarizing general patterns of so cial capital and describing interrelations among the patterns. In the third set of analyses, the study meas ured the impacts of social capital on policy attitudes at both the individua l and under conditional regional le vels of low and high social capital. In this stage, I intended to construct solid patterns of diffe rent aspects of social capital in predicting different policy attitudes. After identifying three differe nt types of policy attitudes in government activism, redistributive policy, and morality policy, I examined patterns of individuals attitudes towards th ese three types of public policy at titudes using different aspects of social network and general social trust, contro lling for other demographic factors. Therefore, the model equations can be written like these:

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64 Model 1: Y government activism = + 1trust + 2single extensiveness + 3multiple extensiveness + 4single intensiveness + 5multiple intensiveness + 6partyid + 7female + 8ethinic minority + 9old + 10education + 11income + 12religiosity + 13regional social capital Model 2: Y redistributive policies = + 1trust + 2single extensiveness + 3multiple extensiveness + 4single intensiveness + 5multiple intensiveness + 6partyid + 7female + 8ethinic minority + 9old + 10education + 11income + 12religiosity + 13regional social capital Model 3: Y morality: abortion= + 1trust + 2single extensiveness + 3multiple extensiveness + 4single intensiveness + 5multiple intensiveness + 6partyid + 7female + 8ethinic minority + 9old + 10education + 11income + 12religiosity + 13regional social capital Model 4: Y morality: gay rights= + 1trust + 2single extensiveness + 3multiple extensiveness + 4single intensiveness + 5multiple intensiveness + 6partyid + 7female + 8ethinic minority + 9old + 10education + 11income + 12religiosity + 13regional social capital

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65 CHAPTER 5 RESULTS Demographics and Social Capital Individuals have a wide range of predisposed characteri stics. Demographics are preliminary factors that determine individuals le vels of social capital or intervene in the interaction between individuals social capita l and policy attitudes or preference, thus demographics need to be taken into considerat ion and at least be controlled for in order to understand the dynamics of social ca pital and policy attitudes. In my sample, the mean age is 45.96 year old, and average level of education is between high school and college. 34% are Democrats, 36% are Independents, and 30% are Republicans. A bout 80% are the White people and the remaining 20 % are a mixture of ethnic minorities such as Blacks, Asians, Hispanics, Natives, and other minority groups. 46% of partic ipants are males and 54% are females. The sample was equally gathered across different geographical regions. Overall, Republicans, older adults, more educated, more religious, ethnic majority members (the White) and females have higher le vels of social capital than Democrats and Independents, younger adults under the age of 30, le ss educated, less religious, ethnic minorities, and males respectively; although there are some va riations across different elements of social capital in network intensiveness and exte nsiveness, and general social networks. Party Identification Political identification, one of the most influe ntial demographic factor s in politics, has a strong relationship with network intensiveness (F[6, 1456]=14.069 p .001) and extensiveness (F[6, 1458]=3.972 p .001) and the level of general social trust (F[6, 862]=2.554, p .019). Republicans (M=1.64, SD=.1.25) tend to engage mo re intensively in social networks than Democrats (M=1.29, SD=1.30) and Independe nts (M=0.77, SD=0.98). Again, Republicans

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66 (M=1.98. SD=1.89) and Democrats (M=1.84, SD=1.94) are more likely to be involved in multiple social networks than Independents (M=1.25, SD=1.85). Those partisan groups of Republicans (M=2.08, SD=0.51) and Democrats (M =2.02, SD=0.42) also tend to trust general society and people more than Independent s (M=1.94, SD=0.42). In addition, political Independents have the highest proportions of individuals who had no act ivity in any network ( 2=77.003, p .001) and no membership ( 2=41.012, p .001) among political partisans (See 5-1 & 5-2). In short, partisanship reflects social capital in two ways. Although soci al capital is a little more prevalent among Republicans than Democrats, strength of partisanships was a stronger influence in individuals social capital than the direction of party identification. In other words, individuals who have strong partis anship tend to be more intensiv ely involved in multiple social networks with higher levels of trust than peopl e who have no or lower levels of partisanship (Tables 5-1 & 5-2). Gender Although gender does not have any releva nce with network extensiveness and intensiveness, it influences levels of general social trust (F [1, 867]=5.083, p .001). Females (M=2.05, SD=0.45) are more likely to trust th e general public than males (M=1.98, SD=0.47) (Tables 5-3 & 5-4) Age In terms of age, overall older adults over 30 year old more intensively (F [1, 1461] = 24.148, p .001) participate in various types of social memberships (F [1, 1463]=10.106, p .002), and have higher levels of gene ral social trust (F[1, 867]=24.990, p .001) than young adults. About 32% of older adults are more st rongly engaged in multiple social networks while only 19% of young adults are intensively invo lved in multiple social gatherings ( 2=24.728,

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67 p .001). About 42% of old adults have multiple memberships, but only 32 % of young adults have more than one membership ( 2=8.551, p .014) (Tables 5-5 & 5-6). Education More educated individuals tend to participate in social networks more intensively (F[4, 1458]=43.893, p .001) and extensivel y (F [4, 1460]=51.546, p .001), and have higher levels of general social trust (F[4, 863]=6.432, p .001) than people who have lower levels of education. About 58% of graduate level individuals are inte nsively involved in mu ltiple social networks while only 11% of middle school graduates have similar levels of network intensiveness ( 2=180.147, p .001). In addition, more than 71% of individuals above the graduate level belong to multiple social memberships, but only 16% of people who obtain middle school education have more than one social membership ( 2=166.608, p .001) (Tables 5-7 & 5-8). Ethnicity Ethnic majorities are more likely to have higher levels of general social trust (F[1, 867]=21.258 p .001) compared to ethnic minorities that encompass Hispanics, Asians, Blacks, and other original and mixed ethnic groups. More over, White people tend to participate more intensively (F [1, 1461]=20.310, p .001) and broadly (F [1, 1463]=3.500, p .062) in social networks than ethnic minorit ies (Tables 5-9 & 5-10). Religiosity Religious strength also shows a strong relati onship with various social capital elements. For instance, individuals who are very religious tend to be intensively involved in social networks (F [3, 1459]=44.652, p .001) in more extensive ways (F [3, 1461]=20.218, p .001) than less religious individuals. However, there is no differen ce in general social trust among individuals with various degrees of religiosity (Tables 5-11 & 5-12).

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68 Income Income has also partial influence on so cial capital. Although it does not have any statistical significance in network extensiveness and general social trus t, higher income people tend to engage more intensively in social ne tworks than low income people (F [2, 891]=6.417, p .002). The proportion of individuals who are not active in any social network is the highest among people who have a yearly income lower than $5,000 ( 2=14.665, p .005). The proportions of people who intens ively engages in multiple soci al network (34%) and multiple social memberships (43%) are much higher for high income people than lower income people ( 2=10.670, p .031) (Tables 5-13 & 5-14) Region Different geographical regions have different levels of so cial capital. For instance, overall the mountain region, including such stat es as Nevada, Arizona, and New Mexico, has more network intensiv eness (F [8, 1462]=2.440, p .013) and extensiveness (F [8, 1456]=1.896, p .057) and higher levels of genera l social trust (F [8, 860]=1.754, p .083) than other geopolitical regions, especially compared to the deep South states of Tennessee, Alabama, and Mississippi (Tables 5-15 & 5-16). These regiona l variances in social connectedness are well supported by previous research such as Clac k, Targonski, and Morgans argument on Southern conservatives, Midwest liberalisms, a nd Western mellowness (1997). Dimension of Social Capital Overall, each individual has di fferent levels of social capit al. When analyzing network intensiveness and extensiveness, survey particip ants were spread out across multiple levels of networks. In network intensiveness, about 39% of people are never inte nsively involved in any of social organizations, associa tions, or informal gathering. Ho wever, about 31% of people say that they are intensively involve d in a single social network and 30% of others report that they

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69 are intensively involved in at least two different social groups. The mean of network intensiveness for each individual is .908 (SD=.823). It infers that the average individual tends to be socially active at least in one type of social networks although th e extent of this activity seems somewhat limited (Table 5-17). In terms of network extensiveness, average pe ople are members of at least one social group (M=1.018, SD=.881) although there are some variations in types of social networks. About 38% of participants have no social membership at all, 22% of people have a single membership, and other 40% have at least two di fferent memberships. Among vari ous types of memberships, 31% of valid participants belong to a church group, 17% of them belong to sports clubs, 15% belong to professional society, 14% in school service, 11% in hobby clubs and art groups, and the rest of the memberships, such as youth group (10.3%), service groups (10%), labor union (9.6%), fraternal group (6.8%), veteran group (5.3%), political club (4.3%) are occupied by 5 10% of participants. A very small porti on of people belong to farm orga nizations (3%) or a nationality group (2.7%). In sum, individuals seem to partic ipate in different types of social gathering at various levels (Table 5-17). For the measurement of general social trust, when the survey asked participants how much people could be trusted, helpful, and fair; most of them say that it depends (M=2.02, SD=.463). Only 4% of the people have a mean score of 1.5 (b etween not trust an d depends), people who fall between the mean scores of 1.5 and 2.5 (near depends) are comprised of more than 71% of the sample, and people who are above th e mean score of 2.5 (between depends and trust) are 25% of the sample. Therefore, we can infer that majority of individuals have at least a moderate level of gene ral social trust (Table 5-17).

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70 Correlations between Different Dime nsions of Social Capital As expected, there are strong correlations among different tenets of social capital. According to the Pearson correlati on tests, individuals who are in tensively involved in at least one social network are more likely to have multiple social memberships (r=.717, p .001). In other words, network intensivenes s and extensiveness are highly correlated. However, general social trust is negatively correla ted with being intensive (r= -.362, p .001) in multiple types of social networks (r= -.339, p .001) (Table 5-18). When explored more deeply, general social trust is more negatively related to multiple memberships (r= -.325, p .001) rather than to a si ngle membership (r= -.232, p .001). In other words, individuals who distrust other members of a society tend to belong to loose multiple social networks rather than a si ngle social gathering. In additi on, individuals who are intensively involved in a single social networ k tend not to intensivel y engage in other social networks (r= .190, p .001), but tend to have at least one (r=.289, p .001) or more (r=.165, p .001) social memberships. Moreover, individuals who have a ny type of single membership are less likely to have other memberships (r= -186, p .001). In other words, we can infer that as long as an individual has a single membershi p, he or she is less likely to obtain another membership (Table 5-19). Among the different memberships, individuals who have a religious membership (r=.476, p .001) are more likely to be intensively involved in multiple social networks, but people who belong to veteran groups are more like to be intensive only within the group, compared to other types of social memberships (r=.118, p .001). Therefore, we can conclude that individua ls who participate in any social network intensively are more likely have any type of social membership. However, people who are intensively involved in a single social network tend not to exte nd their social networks. In

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71 addition, individuals who do not trust people of th e general public are more likely to have multiple social memberships and tend to be intens ively involved in those social networks. This can be interpreted in that people, who do not tr ust acquaintances, still ha ve a secondary group of people with whom to share certain hobbies and norms within organizations. This finding is somewhat contradictory with Putnams argument that people who trust their fellow citizens volunteer more often, [and] participate more of ten in politics and community organizations (Putnam, 2000, p.136-37). However, as Putnam made points in his later discussion, the levels of trust on general public that are caught by such ques tion, whether people can be trusted are thin trust, thus the level of trust can be changeab le and different from solid sense of community (Putnam, 2000, p.137). Therefore, thin trust on general public could create more desire for secondary networks that are loose but still face -to-face interaction and share certain disciplines among members. Social Capital and Policy Attitudes6 On Redistributive policy Certain demographic factors, such as party identificati on, religiosity, education, and ethnicity influence individuals redistributive policy attitudes. As expected, conservative Republicans are less likely to s upport redistributive types of govern ment policies that primarily help the poor and socially disadvantage people (t= -10.042, p .001). However, although the significances are relatively low, ethnic minorities (t=1.847, p .065) and less educated people (t= 6 For multiple regressions, I checked multicollinearity be tween different elements of social capital using VIF (Variation Inflation Factor). In the full model, VIF sc ores for single membership, multiple memberships, single intensiveness, multiple intensiveness, and general social trust are between 1.032 and 2.261. The values above 1 indicate that there are multicollinearity e ffects. Therefore, I ran multiple regr essions separately for each network intensiveness, extensiveness, and social capital with demographic factors. However, the statistical significance for each element of social capital is still identical with the full models. As a result, I still reports the full models.

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72 -1.911, p .056) who often get more benefits out of such policies are more likely to support redistributive policies compared to ethnic majoriti es and highly educated individuals. A negative coefficient on religiosity means that the mo re religious people are less likely to support redistributive government policies (t= -2.504, p .012). It can be interpreted that benevolent religiosity relies on Gods will, thus those indi viduals are less likely to rely on the government for help with the disadvantaged. Overall, ther e is more support for government redistributive policies among social minorities, such as ethnic minorities and less educated people, and socially liberal Democrats, while gender, age, income and regional variation have no independent statistical effects (Table 5-20) Controlling for demographic fact ors, such as party identification, religiosity, gender, age, education, income, ethnicity, and regional differe nces, certain dimensions of social capital influence individuals redi stributive policy attitudes. As this research predicted, individuals who have higher levels of general social trust are more supportiv e of government redistributive policies than people with lower levels of gene ral social trust (t=5.103, p .001). However, network intensiveness (t= -.905, p .366) and extensiveness (t= -.460, p .646) do not determine redistributive policy attitudes. In other word s, the factor of how intensively and broadly individuals participate in soci al networks has no effect on redistributive policy preferences (Table 5-20). Model 1: Y redistributive policy = 4.687 +0.164trust -0.074single extensiveness -0.038multiple extensiveness +0.035single intensiveness -0.081multipel intensiveness -0.117partyid + 0.061female +0.110ethinic minority 0.003old -0. 016education + 0.005incom e -0.053religiosity + 0.080region

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73 On Government Actions Again, some demographic factors influe nce individuals polic y attitudes toward government activism that intends to improve na tional health, education, environment, and big city conditions. As expected, Republicans ar e least supportive of government activism (t= 5.252, p .001). However, individuals earning higher incomes who would have the financial capability to partake in various types social responsibilities are more likely to support government activism (t=2.393, p .017), ceteris paribus (Table 5-21). After controlling for demographic factor s, general social trust (t= -.839, p .402), network extensiveness (t=.103, p .918), and network inte nsiveness (t= -.173, p .862) have no statistical significances on government activism attitudes (Table 5-21). Insignificant results could be caused by methodological errors or theore tical misunderstanding. When conducted multicollinearity tests, although minor effect (above one in VIF) of multicollinearity is detected, a model with a single indicator of social trust still does not have any statistical significance; therefore, multicollinearity is not the cause of statistical insi gnificance. Theoretically, some argue about the broad concept of government activism. The beneficiaries and the consequences of such policies are often random and not specifie d. As a result, the connection between social capital and the particular polic y attitudes could be somewhat blurry and vague (McCool, 1995, pp.210-17). Model 2: Y government activism= 4.924 -0.034trust +0.102single extensiveness -0.011multiple extensiveness -0.085single intensiveness -0.020multipel intensiveness -0.078partyid + 0.096female +0.058ethinic minority 0.003old -0. 002education + 0.025incom e -0.005religiosity + 0.008region

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74 On Morality Policy As we discussed in the method chapter, mo rality issues vary in terms of concepts, approaches, and solutions. Therefore, different types of morality issues, such as abortion and gay rights, have different political implica tions. For instance, among various demographic factors, party identification still has strong influences on abortion a ttitudes, but not on gay rights issues. Conservative Republicans are supportive of stronger government regulations on abortion (t=-.069, p .010), but the tendency is faded way on gay rights issues (t = -.010, p .728). In contrasts, older adults are more likely to be generous particularly on abortion issues (t=2.713, p .007), but not on gay rights (t =.368, p .713). Overall, more educated (t=6.070, t=7.430, p .001) and higher income people (t=2.405, t=2.446, p .015) are more likely to allow womens freedom of decision on abortion and gay ri ghts, and are thus supportive of minimum governmental regulations on those issues. (Tables 5-22 & 5-23) As predicted, after controlling for demographi c factors, individuals who belong to a single social association or orga nization (t= -7.695, t= -8.797, p .001) have supportive attitudes for government regulations on both abortion and gay right s. In addition, people who are intensively involved in such a single soci al network (t= -6.976,t= -8.430, p .001) tend to support government regulations on both issu es. Based on this result, we can infer that limited social networks narrow peoples views on difference and di versity, and thus tend to diminish social tolerance.

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75 However, unlikely my study predicted, individuals who belong to multiple social memberships (t= -7.279, t= -8.426, p .001) and who intensively par ticipate in those social networks (t= -5.657, t= -6.862, p .001) are also more likely to support government regulations on individual choices regarding morality issues such as abortion and gay relations. In other words, as opposed to what was predicted, there are no statistical differences between single and multiple network intensiveness and extensiveness. Individuals who have either a single or multiple memberships, and participate with ei ther limited intensiveness in a single social network or broad intensiveness, all tend to agree with tougher government control on both abortion and gay rights, placing greater importance on social or der and morality over personal freedom (Tables 5-22 & 5-23)7. This infers that as long as in dividuals engage in any type of social gathering in any manner, they seem lik ely to support government supervision keeping societal order and homogeneity on morality issues. In addition, individuals at higher levels of general social trus t are partially likely to support strong government regulations, partic ularly on gay issues (t= -2.260, p .024), but not on abortion (t= -1.141, p .254) (Tables 5-22 & 5-23). These result s reflect that policy attitudes toward different kinds of morality issues are influenced in a variety of ways by even the same kind of individuals social liv es and the manner in which the indi viduals make personal connections (White, 2003). Thus, although individuals with a hi gher level of general so cial trust tend to hold 7 The researcher was suspicious about the tenets of particular social group, such as religious gathering, for the reason of politically conservative views on morality issues. Theref ore, the researcher re-ran multiple regressions on those two morality issues of abortion and gay rights after excluding religious groups from the measurements of social networks. However, the statistical si gnificance for each element of social capital is still identical with the full models. As a result, the researcher still reports the full models.

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76 higher moral values on life, faith in God, and re spect of tradition, the levels of support for government control on morality issues varied de pending on the type of issues considered and different perspectives. Model 3: Y morality: abortion= -0.538 0.083trust 1.228single extensiveness 1.146multiple extensiveness 1.440single intensiveness 1.381multipel intensiveness 0.070partyid + 0.025female 0.181ethinic minority + 0.011old + 0.120education + 0.044income 0.077religiosity + 0.166region Model 4: Y morality: gay rights= -0.523 -0.178trust -1.591single extensiveness -1.495multiple extensiveness -1.771single intensiveness -1.717multipel intensiveness -0.011partyid + 0.037female -0.263ethinic minority + 0.001old + 0.158education + 0.049income +0.027religiosity + 0.159region The Regional Context and Social Capital Regional levels of social capital at the aggregate level of states or larger pol itical units are a useful way to explore dynamics of political at titudes and characteristic s. Using a dichotomous variable of region that was divi ded according to Putnams social capital index ( 2000), I looked at the conditional effects of two, low and high, regi onal social capital circumstances on various aggregated policy attitudes. In general, ri ch social capital regions have a higher White population (99%) than poor soci al capital regions (77%) ( 2 = 42.58, p .001). Other demographic variables such as gender, age, and religiosity, and party identification, however, do not have statistical variati ons across different levels of social capital regions. Under both high social capital regions of New England, West North Central, and Mountain (F[12, 286]=3.948, p .001, F[12, 286]=2.382, p .061) and low social capital regions of South Atlantic, East South Central, and West South Central (F[12, 613]=6.554, p .001, F[12, 613]=1.904, p .031), network intensiveness (t=.384, p .701, t=.580, p .562) and extensiveness (t= -.496, p .620, t=.085, p .932) have no statistical significances in redi stributive policies and government activism attitudes. However, both network intensiveness and extensiveness induce

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77 supportive attitudes for government regulations on morality policies such as abortion and gay rights in both regions with high social capital (F[12, 286]=9.673, p .001, F[12, 286]=12.097, p .001)and low social capital (F[12, 613]=13.095, p .001, F[12, 613]=17.099, p .001) (Tables 5-24 & 5-25). Therefore, regiona l social capital conditions do not make any statistical difference in relationships between social networks a nd policy attitudes on redi stributive, government activism, and morality policies. However, general social trust behaves di fferently across different policy areas under different regional social capit al circumstances. Although gene ral social trust encourages supportive attitudes for redistribu tive policies in both high (t=2.590, p .010) and low (t=4.059, p .001) levels of social capital regions, it has a significant influence on government regulations on abortion (t= -2.226, p .027) and gay rights (t= -3.769, p .001) only in higher social capital regions, but not in lower so cial capital regions (t=.360, p .719, t=1.121, p .263). In other words, a group of people who are in social capital rich regions with higher general social trust support government regulations on morality issues, whil e a group of people who have higher general social trust but are in a region with low social capital do not have particular tendencies in morality policy attitudes (Tables 5-24 & 5-25). Individuals in regions with eith er higher or lower levels of social capital present identical policy attitudes besides a little variation in the function of general social trust on morality policy attitudes. Compared to general social trust at the individual level that partially influences positive attitude for government regulation on one t ype of morality issue, gay rights, but not on the issue of abortion, policy atti tudes become more homogeneous under a given regional levels of social capital. For instance, in higher so cial capital regions, genera l social trust always induces individuals positive attitudes for governme nt regulations on morality issues regardless

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78 the types of different issues. In contrasts, in lower social capital regions, it has no particular influence on any type of morality policy attitude This finding supports theoretical arguments on discrepancies between individuals of micro and aggr egates of macro political characteristics. As they are aggregated, political at titudes at the macro level beco me more orderly and seemingly uniform (Erikson and Tedin, 2007, p.93) Nonetheless, overall findings under different regions are cons istent with the tendency in the micro level of individuals po licy attitudes. As found in the previous section, higher social capital at the individual level induces conserva tive views toward aborti on and gay rights, thus people care more about government regulations; and regi onal social capital circumstances do not change such tendencies of social capital on policy attitudes at the aggregate level. Therefore, the individual tendency is persistent at the aggregate level. This strong linear consistency with minimal variations between two different levels of approaches helps further development of theoretical connections of social capital dynamics across different leve ls of individuals and states.

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79Table 5-1. Party Identifica tion and Social Capital Demographics Network Intensiveness Netw ork Extensiveness General Social Trust Party Affiliations Mean (SD) Mean (SD) Mean (SD) Strong Democrat 1.29(1.30)1.84(1.94)2.02(0.42) Not Strong Democrat 0.98(1.17)1.55(1.94)1.97(0.44) Independent Democrat 0.92(1.05)1.65(1.81)1.94(0.47) Independent 0.77(0.98)1.25(1.85)1.94(0.42) Independent Republican 0.91(1.07)1.50(1.82)2.06(0.47) Not Strong Republican 1.13(1.12)1.54(1.76)2.09(0.50) Strong Republican 1.64(1.25)1.98(1.89)2.08(0.51) F[6, 1456]=14.069 p .001, N=1462 F[6, 1458]=3.972 p .001, N=1464 F[6, 862]=2.554, p .019, N=868 Table 5-2. Party Identification and Netw orks Intensiveness and Extensiveness Demographics No Intensiveness Single Intensiveness Multiple Intensiveness No Membership Single Membership Multiple Memberships Party Affiliations % % % % % % Strong Democrat 33.8631.0835.0633.0721.1245.82 Not Strong Democrat 44.3130.5925.1041.0223.4435.55 Independent Democrat 45.3829.2325.3835.8818.3245.80 Independent 50.1830.3219.4949.2821.5829.14 Independent Republican 45.2430.9523.8137.6028.0034.40 Not Strong Republican 35.7133.3330.9537.6221.9040.48 Strong Republican 18.6934.5846.7326.6423.8349.53 2=77.003, p .001 2=41.012, p .001

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80Table 5-3. Gender and Social Capital Demographics Network Intensiveness Netw ork Extensiveness General Social Trust Gender Mean (SD) Mean (SD) Mean (SD) Male 1.08 (1.19)1.67 (1.92)1.98 (0.47) Female 1.11 (1.17)1.56 (1.85)2.05 (0.45) F [1,1461]=0.235, p .628, N=1462 F [1, 1463]=1.067, p .302, N=1464F[1, 867]=5.083, p .001, N=868 Table 5-4. Gender and Network Intensiveness and Extensiveness Demographics No Intensiveness Single Intensiveness Multiple Intensiveness No Membership Single Membership Multiple Memberships Gender % % % % % % Male 40.0930.1129.8037.0622.5140.43 Female 37.8132.6429.5638.5522.4139.04 2=1.226, p .542 2=.389, p .823 Table 5-5. Age and Social Capital Demographics Network Intensiveness Netw ork Extensiveness General Social Trust Age Mean (SD) Mean (SD) Mean (SD) Less than 30 Years Old 0.79(1.01)1.29 (1.79)1.85(0.40) More than 30 Years Old 1.17(1.20)1.68(1.90)2.05(0.47) F [1, 1461]=24.148, p .001, N=1462 F [1, 1463]=10.106, p .002, N=1464 F[1, 867]=24.990, p .001, N=868

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81Table 5-6. Age and Network Intensiveness and Extensiveness Demographics No Intensiveness Single Intensiveness Multiple Intensiveness No Membership Single Membership Multiple Memberships Age % % % % % % Less than 30 Years Old 50.1830.8219.0043.5324.4632.01 More than 30 Years Old 36.1531.6732.1836.5621.9941.45 2=24.728, p .001 2=8.551, p .014 Table 5-7. Education and Social Capital Demographics Network Intensiveness Netw ork Extensiveness General Social Trust Education Mean (SD) Mean (SD) Mean (SD) Middle School 0.53(0.88)0.74(1.29)1.94(0.44) High School 0.92(1.06)1.27(1.61)1.97(0.45) Junior College 1.28(1.14)1.69(1.87)1.98(0.47) Bachelor 1.49(1.24)2.36(2.14)2.09(0.48) Graduate 1.87(1.34)2.92(2.09)2.21(0.47) F[4, 1458]=43.893, p .001, N=1462 F [4, 1460]=51.546, p .001, N=1464 F[4, 863]=6.432, p .001, N=867 Table 5-8. Education and Network Intensiveness and Extensiveness Demographics No Intensiveness Single Intensiveness Multiple Intensiveness No Membership Single Membership Multiple Memberships Education % % % % % % Middle School 63.6825.7910.5362.4320.6316.93 High School 42.8435.3321.8342.7824.3932.83 Junior College 27.9337.8434.2333.0425.0041.96 Bachelor 26.0627.4646.4823.5121.0555.44 Graduate 19.3122.7657.9313.1015.8671.03 2=180.147, p .001 2=166.608, p .001

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82Table 5-9. Ethnicity and Social Capital Demographics Network Intensiveness Netw ork Extensiveness General Social Trust Ethnicity Status Mean (SD) Mean (SD) Mean (SD) Minority 0.83 (1.06)1.43 (2.00)1.87(0.35) Majority 1.17 (1.20)1.66 (1.17)2.05(0.48) F [1, 1461]=20.310, p .001, N=1462 F[1, 1463]=3.500, p .062, N=1464 F[1, 867]=21.258 p .001, N=868 Table 5-10. Ethnicity and Network Intensiveness and Extensiveness Demographics No Intensiveness Single Intensiveness Multiple Intensiveness No Membership Single Membership Multiple Memberships Ethnicity Status % % % % % % Minority 46.7735.4817.7443.8723.5532.58 Majority 36.6930.4432.8736.2822.1641.56 2=27.224, p .001 2=8.896, p .012 Table 5-11. Religiosity and Social Capital Demographics Network Intensiveness Netw ork Extensiveness General Social Trust Religious Strength Mean (SD) Mean (SD) Mean (SD) Not Religious 0.64 (0.94)1.14 (1.66)1.96 (0.41) Not Very Religious 0.85 (1.09)1.37 (1.71)2.03 (0.48) Somewhat Religious 1.18 (1.16)1.40 (1.73)2.08 (0.44) Strongly Religious 1.49 (1.21)2.07 (2.05)2.00 (0.47) F [3, 1459]=44.652, p .001, N=1462 F [3, 1461]=20.218, p .001, N=1464 F [3, 865]=1.243, p .293, N=868

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83Table 5-12. Religiosity and Network Intensiveness and Extensiveness Demographics No Intensiveness Single Intensiveness Multiple Intensiveness No Membership Single Membership Multiple Memberships Religious Strength % % % % % % Not Religious 59.9122.9117.1849.1224.1226.75 Not Very Religious 51.1625.1923.6442.0524.2233.72 Somewhat Religious 31.5439.6028.8644.9716.7838.26 Strongly Religious 21.1938.5340.2827.8021.6850.52 2=157.838, p .001 2=61.862, p .001 Table 5-13. Income and Social Capital Demographics Network Intensiveness Netw ork Extensiveness General Social Trust Income Mean (SD) Mean (SD) Mean (SD) Less than 4,999 0.87 (1.10)1.49 (1.91)1.92 (0.43) Between 5,000-9,999 0.76 (0.92)1.24 (1.70)1.93 (0.43) More than 10,000 1.22 (1.22)1.76 (1.95)2.04 (0.47) F [2, 891]=6.417, p .002, N=893 F [2, 893]=2.503, p .082, N=895 F[2, 514]=1.934, p .146, N=868 Table 5-14. Income and Network In tensiveness and Extensiveness Demographics No Intensiveness Single Intensiveness Multiple Intensiveness No Membership Single Membership Multiple Memberships Income % % % % % % Less than 4,999 48.0532.4719.48 40.2627.2732.47 Between 5,000-9,999 47.4635.5916.95 51.7217.2431.03 More than 10,000 35.2230.4734.30 33.3823.6542.97 2=14.665, p .005 2=10.670, p .031

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84Table 5-15. Region and Social Capital Demographics Network Intensiveness Netw ork Extensiveness General Social Trust Region Mean (SD) Mean (SD) Mean (SD) New England 1.00 (1.00)1.70 (1.98)2.02 (0.52) Middle Atlantic 1.27 (1.23)1.72 (1.91)2.03 (0.49) East North Central 1.10 (1.17)1.58 (1.78)2.07 (0.46) West North Central 1.15 (1.25)1.72 (1.82)2.06 (0.46) South Atlantic 1.16 (1.20)1.52 (1.86)1.94 (0.43) East South Central 1.18 (1.18)1.76 (1.97)2.06 (0.48) West South Central 0.81 (1.02)1.19 (1.98)1.93 (0.43) Mountain 1.24 (1.24)2.01 (1.85)2.11 (0.48) Pacific 0.98 (1.14)1.69 (1.86)1.99 (0.47) F[8, 1462]=2.440, p .013, N=1462 F=[8, 1456]=1.896, p .057, N=1464 F[8, 860]=1.754, p .083, N=868 Table 5-16. Region and Network In tensiveness and Extensiveness Demographics No Intensiveness Single Intensiveness Multiple Intensiveness No Membership Single Membership Multiple Memberships Region % % % % % % New England 37.2137.2125.58 39.5316.2844.19 Middle Atlantic 36.1325.1338.74 34.0322.5143.46 East North Central 38.1532.5929.26 39.7818.2242.01 West North Central 37.1135.0527.84 32.6525.5141.84 South Atlantic 33.7637.2628.98 38.5426.1135.35 East South Central 33.7332.5333.73 34.9421.6943.37 West South Central 49.6930.4319.88 54.6619.8825.47 Mountain 36.7324.4938.78 24.4928.5746.94 Pacific 45.6328.1626.21 34.6221.6343.75 2=34.589, p .005 2=40.041, p .001

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85 Table 5-17. Descriptive Social Capital Dimensions of Social Capital Mean(SD) Percentage (%) N Network Intensiveness 0.908 (.823)1463 Not active in any network 38.82 568 Active in single network 31.51 461 Active in multiple networks 29.67 434 Network Extensiveness 1.018 (.881)1465 No membership 37.88 555 Single membership 22.46 329 Multiple memberships 39.66 581 General Trust 2.012 (.463) 869 Low trust 4.14 36 Moderate trust 71.12 618 High trust 24.74 215 Table 5-18. Correlations of Social Capital Network Intensiveness Network Extensiveness General Social Trust Network Intensiveness 1.000 Network Extensiveness 0.717*** 1.000 General Social Trust -0.362***-0.339***1.000 ***You need to define what your as terisks mean underneath each table

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86Table 5-19. Correlations of Networ k Intensiveness, Extensivene ss, and General Social Trust Single Intensiveness Multiple Intensiveness Single Membership Multiple Memberships General Social Trust Single Intensiveness 1.000 Multiple Intensiveness -0.190***1.000 Single membership 0.289*** 0.049***1.000 Multiple memberships 0.165*** 0.592***-0.186***1.000 General social trust -0.282***-0.273***-0.232***-0.325***1.000 Table 5-20. Social Capital and Re distributive Policy Attitudes Redistributive Policy Coef. t sig. Constant 4.687 29.0710.000 Party Identification -0.117-10.0420.000 Ethnic Minority 0.110 1.8470.065 Religiosity -0.053 -2.5040.012 Female 0.061 1.3030.193 Age -0.003 -1.6820.093 Education -0.016 -1.9110.056 Income 0.005 0.5540.579 Region High in Social Capital 0.080 1.3340.182 Single Network Intensiveness 0.035 0.4590.646 Multiple Network Intensiveness 0.081 0.9050.366 Single Membership Extensiveness -0.074 -0.9050.365 Multiple Membership Extensiveness -0.038 -0.4600.646 General Social Trust 0.164 5.1030.000 F [13, 1669]=13.949, p .001, R2=0.098, N=1682, ***p .01, **p .05, p .10

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87Table 5-21. Social Capital and Government Activism Attitudes Government Activism Coef. t sig. Constant 4.92424.1060.000 Party Identification -0.078 -5.2520.000 Ethnic Minority 0.058 0.7660.444 Religiosity -0.005 -0.1930.847 Female 0.096 1.6280.104 Age -0.003 -1.1470.252 Education -0.002 -0.1730.863 Income 0.025 2.3930.017 Region High in Social Capital 0.008 0.1100.913 Single Network Intensiveness -0.085 -0.8760.381 Multiple Network Intensiveness -0.020 -0.1730.862 Single Membership Extensiveness 0.102 0.9880.323 Multiple Membership Extensiveness 0.011 0.1030.918 General Social Trust -0.034 -0.8390.402 F[13.1669]=3.606, p .001, R2=0.027, N=1682, ***p .01, **p .05, p .10

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88Table 5-22. Social Capital a nd Attitudes toward Abortion Morality Policy: Abortion Coef. t sig Constant 0.048 0.1300.897 Party Identification -0.069 -2.5830.010 Ethnic Minority -0.167 -1.2250.221 Religiosity -0.082 -1.6960.090 Female 0.029 0.2760.782 Age 0.011 2.7130.007 Education 0.120 6.0700.000 Income 0.046 2.4050.016 Region High in Social Capital 0.295 2.1420.032 Single Network Intensiveness -1.227 -6.9760.000 Multiple Network Intensiveness -1.156 -5.6570.000 Single Membership Extensiveness -1.434 -7.6950.000 Multiple Membership Extensiveness -1.368 -7.2790.000 General Social Trust -0.084 -1.1410.254 F [13.1669]=37.427, p .001, R2=0.226, N=1682, ***p .01, **p .05, p .10

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89Table 5-23. Social Capital and Attitudes toward Gay Rights Morality Policy: Gay Right Coef. t sig Constant 0.060 0.1520.879 Party Identification -0.010-0.3480.728 Ethnic Minority -0.258-1.7610.078 Religiosity 0.023 0.4440.657 Female 0.040 0.3510.726 Age 0.002 0.3680.713 Education 0.158 7.4300.000 Income 0.050 2.4460.015 Region High in Social Capital 0.218 1.4720.141 Single Network Intensiveness -1.594-8.4300.000 Multiple Network Intensiveness -1.508-6.8620.000 Single Membership Extensiveness -1.763-8.7970.000 Multiple Membership Extensiveness -1.702-8.4260.000 General Social Trust -0.179-2.2600.024 F[13, 1669]=46.914, p .001, R2=0.262, N=1682, ***p .01, **p .05, p .10

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90Table 5-24. Regions with High Social Capital High Social Capital Redistributive Policy Government Activism Morality Policy: Abortion Morality Policy: Gay Right Coef. t sig. Coef. t sig. Coef. t sig Coef. t sig Constant 4.967 12.8910.000 4.93810.7020.000-0.279-0.2980.766 0.062 0.0630.950 Party Identification -0.150 -5.3180.000 -0.098-2.9180.004-0.111-1.6270.105-0.053-0.7460.456 Ethnic Minority -0.006 -0.0280.977 0.532 2.1780.030 0.214 0.4310.667 0.309 0.6000.549 Religiosity 0.027 0.5310.596-0.054-0.8760.382-0.004-0.0320.974 0.102 0.7800.436 Female 0.174 1.5780.116 0.102 0.7740.440 0.418 1.5540.121 0.601 2.1520.032 Age -0.006 -1.5150.131-0.002-0.3470.729 0.021 2.1030.036 0.016 1.5770.116 Education -0.033 -1.4670.144 0.007 0.2760.783 0.141 2.5750.011 0.168 2.9530.003 Income 0.007 0.3690.713 0.020 0.9150.361 0.058 1.3240.187 0.030 0.6650.507 Single Network Intensiveness 0.019 0.0890.929-0.131-0.5140.608-1.514-2.9230.004-1.932-3.5900.000 Multiple Network Intensiveness 0.090 0.3840.701 0.369 1.3100.191-1.499-2.6200.009-1.831-3.0830.002 Single Membership Extensiveness -0.051 -0.2570.798-0.061-0.2560.798-2.057-4.2390.000-2.562-5.0830.000 Multiple Membership Extensiveness -0.110 -0.4960.620-0.389-1.4610.145-1.693-3.1310.002-2.103-3.7450.000 General Social Trust 0.186 2.5900.010 0.048 0.5600.576-0.390-2.2260.027-0.685-3.7690.000 ***p .01, **p .05, p .10 F[12,286]=3.948, p .001, R2=0.142, N=298 F[12.286]=2.382, p .006, R2=0.091, N=298 F[12, 286] =9.673, p .001, R2=0.289, N=298 F[12, 286]=12.097, p .001, R2=0.262, N=298

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91Table 5-25. Regions with Low Social Capital Redistributive Policy Government Activism Morality Policy: Abortion Morality Policy: Gay Right Coef. t sig. Coef. t sig. Coef. t sig Coef. t sig Constant 4.970 18.6620.000 4.48713.6030.000 0.637 1.0980.273 0.785 1.2580.209 Party Identification -0.120 -6.0300.000 -0.072-2.9310.004-0.044-1.0190.309-0.012-0.2480.804 Ethnic Minority 0.111 1.1510.250 0.023 0.1930.847-0.078-0.3730.709-0.212-0.9370.349 Religiosity -0.069 -1.8700.062-0.017-0.3770.706-0.209-2.5910.010-0.174-2.0080.045 Female 0.019 0.2340.815 0.138 1.3950.163 0.027 0.1560.876 0.068 0.3640.716 Age -0.005 -1.8450.066-0.002-0.6170.537 0.004 0.6440.520-0.008-1.0900.276 Education -0.021 -1.4780.140 0.015 0.8560.392 0.100 3.1980.001 0.114 3.3780.001 Income -0.002 -0.1580.874 0.039 2.2490.025 0.044 1.4560.146 0.076 2.3570.019 Single Network Intensiveness 0.023 0.1770.860-0.119-0.7300.466-1.304-4.5400.000-1.568-5.0720.000 Multiple Network Intensiveness 0.095 0.5800.562-0.136-0.6730.501-1.150-3.2290.001-1.423-3.7120.000 Single Membership Extensiveness -0.079 -0.5430.588 0.266 1.4700.142-0.956-3.0070.003-1.113-3.2520.001 Multiple Membership Extensiveness 0.013 0.0850.932 0.276 1.4650.144-0.931-2.8090.005-1.120-3.1380.002 General Social Trust 0.227 4.0590.000-0.022-0.3240.746 0.044 0.3600.719 0.147 1.1210.263 ***p .01, **p .05, p .10 F[12, 613]=6.554, p .001, R2=0.114, N=625 F[12.613]=1.904, p .031, R2=0.036, N=625 F[12, 613] =13.095, p .001, R2=0.204, N=625 F[12, 613]=17.099, p .001, R2=0.251, N=625

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92 CHAPTER 6 DISCUSSION A single mother meets other single mothers in a day-care center. Those single mothers tend to experience financial and emotional difficult ies. The common experiences which they share allows them to identify with one another and crea te more personal associa tions with each other than the fact that they are all single mothers. As a result of th eir shared experiences and personal interactions, they become alike in political beliefs and preferences. Individuals social lives are not predetermi ned elements and are not always translated directly into feelings towards political agendas because people react to various parts of politics using both explicit and implicit social interactions such as cues in th eir political thinking (Conover, 1988, pp.62, 65). Based on this logic, my study argued that different elements of social capital would be activated or elevated by different types of political agendas and would vary in their influence on certain types of policy attitudes. Demographics Overall, in preliminary analyses, my study found that there is a relevant association between individuals demographi c factors and social capital. Individuals who have strong partisanship, and are older, more educated, and part of the ethnic majority (the White) tend to be more intensively involved in multiple social networks with higher levels of trust than people who have no, or lower levels of partisanship, and ar e younger, less educated, and part of the ethnic minority. However, gender has relevance only with general social trust; females are more likely to believe that people are trustful, helpful, and fair than are males. People who are very religious engage in social networks more intensively and extensively, but have similar levels of social trust toward the general public, co mpared to less religious indivi duals. In addition, in spite of some variations, different geographical regions ha ve different levels of social capital. The

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93 Mountain region, including states such as Nevada Montana, and Wyoming has higher levels of social capital compared to the West or Sout h East regions, which includes states such as Louisiana, Mississippi, and Alabama. Stereotypically, liberals are mo re in favor of welfare progr ams and spending money, while conservatives favor free enterprise Conservatives are seen as mo ralistic and religious; however liberals are seen as having more flexible mora l standards and not as re ligious. Reflectively, Republicans have been seen as moralistic and De mocrats as permissive in American politics (Erikson and Tedin, 2007, p.75, 86). Several previous researchers observed that the American public is ideologically conservative but operatio nally liberal (Free and Cantril 1967; Cantril and Cantril, 1999). Therefore, the overall majo rity of Americans tend to support government spending on various welfare policie s (Erickson and Tedin, 2007, p.95). More educated individuals tend to be more lib eral in moral based types of public policies, such as abortion and gay rights; but less educated indi viduals are more likel y to support socialwelfare spending issues, such as a guaranteed job and standa rd of living, national health insurance, and increased government se rvices (Erikson and Tedin, 2007, pp. 64-5). Among various demographic factors, religion is one of the most comprehensive social networks in U.S. society. Indi viduals active in religious networ ks are more likely to associate with other forms of civic involve ment, like voting, jury service, co mmunity projects, talking with neighbors, and giving to charity. More importan tly, religiosity has been a powerful indicator of civic engagement, especially for voluntary and cultural networks (Putnam, 2000, pp.66-7). Lastly, regarding research that shows that ethnic minorities such as Hispanics and Blacks have suffered seriously from lack of health in surance (Cochran, et al., 2006, p.256), it is natural

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94 that ethnic minorities tend to share less social cap ital, but are more suppor tive of liberal political approaches such as social welfare policies. Social Networks In terms of dimensional relationships between multiple aspects social capital, according to correlation tests, individuals who are intensively involved in a single social network tend not to engage intensively in other t ypes of networks. It seems reas onable to think that those that already had a single membership are less likely to obtain other types of membership. This finding indicates that social in teractions do not unlimitedly o ccupy individuals lives. People who are already intensively involv ed in any social network they prefer, often have less time to dedicate to other social networ ks. In addition, people who alr eady have any type of social membership do not have any motivation or desire to be a member of other social associations. According to multiple regression tests in my study, network intensiveness and extensiveness are related only to morality based policy attitudes, but are not relevant to redistributive and government activism attitudes. In addition, unlike the study that expected memberships in multiple group associations to incr ease political tolerance towards various social issues (Cigler and Joslyn, 2002), individuals who are in multiple social networks still tend to put greater values on societal order and morality over individuals free dom to choose. According to results of regressions excluding el ements of religious networks, the statistical significances are still identical with the model with regard to all types of social networks. Therefore, there are no overwhelming effects of religious networks on participants conservative policy attitudes. Therefore, the result implies that having any type of social membership increases individuals morality values on social orders, thus the members are more supportive of stronger governmental control on morality based social issu es. This tendency is more dominant in people

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95 who engage in one homogeneous social network that shares less attitudes of benevolence and tolerance to differen ces (Putnam, 2000, p.341). General Social Trust General social trust has some contradictory characteristics of social capital against other elements of social capital, such as network inte nsiveness and extensivenes s. In addition, the relationship between individuals levels of trust toward the general public and various policy attitudes is not always consistent. For instance, general social trust is highly related to positive attitudes toward government redistributive policie s and certain morality policies, such as gay rights, but has no relevance to policy attitudes toward government activism and other types of morality issues regarding abortion. There could be several explanati ons about the dynamic implications of general social trust. First of all, social trust itself contains attitude ambivalence, and the ambivalence becomes more prevalent when it is directed toward different obj ects in different degrees of political situations and social environments (Craig, Martinez, Kane and Gainous, 2005). Sec ond, the levels of trust vary and are not linear: the maximum level of general social networks could be less positively related to social toleranc e compared to moderate level of soci al trust (Hardin, 2002) Social trust is initially built up through interpersonal relati ons. Therefore, beyond certain interpersonal connections or relevant boundaries individuals tend to withdraw their social trust (Earle and Cvetkovich, 1995, p.10-11). Therefore, general so cial trust could be less prevalent among individuals who belong to any social network bo undaries than in people who were not in any social network. In addition, people who trust others are all-round good citize ns, and those more engaged in community life are both more trusting and more trustworthy (Putnam, 2000, p.137). However, as Hero points out (2003) a greater level of social cap ital can isolate the minority and

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96 ignore certain policies that are related to those people while be nefiting the majority in the society. Racially homogeneous states do well on aggregate indicators of policy, but often have very disparate relative examples of outcomes fo r racial ethnic minorities (p.402). Therefore, future research should further investigate more sophisticated social trus t measurements and the resulting implications. Divergence of Policy Attitudes In terms of redistributive polic y attitudes, individuals who ha ve higher levels of general social trust are more likely to support government redistributive policies that would help the have-nots, however other elements of social cap ital, such as social networks, do not have any significant influence on such policy attitudes. This result refl ects the different functions of social capital on even the same types of policy attitudes. Moreover, multiple elements of social capital do not have any influence on policy attitudes toward government activism that would often cr eate public good. This finding could be the result of particular tenets of government activism that are supposed to create and improve general social good. For government activism, Am ericans have mixed preferences of wanting both private choices/management and government in tervention for subsid ies (Erikson and Tedin, 2007, p.97). Regarding Putnams arguments that soci al networks and associations help citizens resolve collective problems easily, develop characte r traits that are good fo r the rest of society (Putman, 2000, pp.288-90), facilitate communicati on, improve the flow of information, and stabilize collaboration (Putnam, 1993, pp.173-74), a hi gh level of social ca pital can even reduce desire or the necessity of government actions. In addition, such different statistical significances for redistributive and government activism are al ready suggested by previous scholars, such as Lane (2000) and Wlezien (1995), who argued for c ontradictory and ambivalent policy attitudes

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97 toward different areas of redistributive and government activism policies among general American publics. According to other findings in my researc h, individuals social life patterns have the strongest relevance with policy attitudes toward government morality policies on issues like abortion and gay rights, among other types of gove rnment policies. As long as individuals engage in any type of social network, they ar e more likely to support government regulations on abortion and gay issues, placing greater value on social morality over individuals freedom to choose. General social trust, however, i nduces individuals pref erences on government regulations on gay rights, but not on abortion. These results reflect an incidence of social capital that not only ma kes people tolerant to social diversity, but also crea tes undesirable group attitudes, group differences, and societal isolations (White, 2003). For inst ance, individuals in small towns are highly engaged in their community life, but they tend to be less tolerant of differen ces and diversities (Putnam, 2000, p.352). Because social capital is often easil y established by race, gender, and political affiliations, individuals within such social netw orks are less likely to understand people from other societal or political sectors. Small communities and highly committed neighborhoods are less tolerant of homosexual teachers and inte rracial marriages for pe ople within their own communities (Putnam, 2000, p.352-53). Considering su ch a down-side of social capital, a strong and narrow level of social capital can constrain an i ndividuals freedom to choose and require governmental regulations on soci etal orders (Schudson, 1998). According to Feldman and Zaller (1992), people use diverse values, such as individualism, humanitarianism, or personal attitudes agains t big government, in determining their attitudes toward multiple policies. Therefore, there exist si gnificant levels of attitude ambivalence in their

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98 issue positions. The attitudina l ambivalence seems more predominant on governmental welfare and morality policy types. Individuals ideologica l innocence results in positive attitudes toward benevolence to the have-nots and social morality. However, it creates problems by unaware practical political tensions with inconsistent polic y attitudes and preferences for welfare or social policies (Feldman and Zaller, 1992, pp.268-69). All public policies ha ve two sides, the effects and counter-effects. These pol icies are fixing certain parts of the political problem and benefiting certain groups of people, however they also constrain some other parts of society and groups of people. Therefore, the conflict of ideo logical justifications a nd the practical operations have been difficult for policy reformers, espe cially for welfare reformers (Feldman and Zaller,1992, pp.270-71), and perpetua tes individuals ambivalent policy attitudes (Craig, Martinez, Kane, and Gainous, 2005). Overall, although a large element of social capit al, such as the levels of social trust, become more indistinguishable across diffe rent regions (Hetheri ngton, 2005, p.21), regional differences on political and social culture have ex isted. Public opinion or attitudes at the macro level of aggregation are far more orderly than single answers at the micro levels of the individual. Although some indivi dual tendencies can be cancelled out at the macro level, the macro level of attitudes was seemingly uniform and appeared obvious (Erikson and Tedin, 2007, p.93). Future research needs to address and explor e the different effects of an element of social capital at the individual level and the aggregated level of regi ons on political attitudes. There are variations in diffe rent aspects of social capit al in predicting political consequences (Cigler and Joslyn, 2002). Indivi duals use different cues to determine their political attitudes and their surroundings provide important cues. Based on how intensively and broadly individuals engage in soci al networks, they view certain i ssues in more or less positive

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99 ways (Stolle and Rochon, 2001). Therefore, it is r easonable to infer that di fferent dimensions of social networks are activated by different issues. Among vari ous different types of policy attitudes, government activism attitudes are less li kely to relate to gene ral social networks and morality policy attitudes are more strongly related to all elements of social capital. As the study predicted, various elements of soci al capital influence di fferent policy attitudes in various ways. Policy itself has multiple dimensions in purpose, process, and outcomes. Various political structures and individuals pred ispositions determined different policy preferences and induced the government to end up with certain policy choices accordingly. For instance, homogeneous communities adopt areal policies, but heter ogeneous communities will adapt segmental policies to satisfy divers e people (McCool, 1995, p.211). Although the majority of individua ls political attitudes, especi ally policy preferences, are highly related to their own interests, a great part of their preferences are determined by political predispositions and socially shared values (Erikson and Tedin, 2007, p.65). Formal political evidence and the connection with so cial capital are not yet clearly shown in the academic world (Putnam, 2000, p.146). Despite some limitation for clear causations between multiple dimensions of social capital and various policy attitudes due to uncontrollabl e variations, this research is coherent and parsimonious since policy attitudes and preferences tend to be more consistent and tractable than any other political attitudes. In addition, po licy attitudes can be easily summarized based on attitudes towards specific public policies (Erikson and Tedin, 2007, pp. 9-18). Therefore, the patterns between multi-dimensional social capital and specific policy attitudes are more likely to be reliable.

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100 In conclusion, it is important to understand the potential effect of soci al capital not only on individuals policy preferences at the level of individual, but also on direct policy efficiency at the macro level of government on more specific policy issues such as education, poverty, employment, housing, and other living environmen t (The National Economic and Social Forum, 2003). Further research needs to be done to cons truct more reliable and valid causations.

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101 APPENDIX A SOCIAL CAPITAL Social Network Intensiveness Indicate whether you belong to a political party (Never belonged (1), used to belong (2), belong but do not participate (3), belong and actively participate (4)) Indicate whether you belong to a trade union or professional associa tion (Never belonged (1), used to belong (2), bel ong but do not participate (3), belong and actively participate (4)) Indicate whether you belong to a church or ot her religious organiza tion (Never belonged (1), used to belong (2), bel ong but do not participate (3), belong and actively participate (4)) Indicate whether you belong to a sports, leisure, or cultural groups (N ever belonged (1), used to belong (2), belong but do not participate (3), bel ong and actively participate (4)) Indicate whether you belong to another voluntary association (Never belonged (1), used to belong (2), belong but do not participate (3), belong and activ ely participate (4)) *Robert Putnams social capital index (2000, pp.27, 291); Kwak, Shan, and Holbert (2004) categorization; Letki (2004)s membership categorization Table A-1. Factor Analysis on Social Network Intensiveness Factor Component belongs to a political party 0.871 belongs to a trade union or professional association 0.854 belongs to a church or ot her religious organization 0.886 belongs to a sports, leis ure, or cultural group 0.889 belongs to another vo luntary association 0.888 Social Network Extensiveness (Sum of memberships) Whether you have a membership in fraterna l group (Q: We would like to know something about the groups or organizations to which indi viduals belong. Here is a list of various organizations. Could you tell me whether or not you are a member of fraternal group? no (0), yes (1)) Whether you have a membership in service group (Q: We would lik e to know something about the groups or organizations to which indi viduals belong. Here is a list of various organizations. Could you tell me whether or not you are a member of service group? no (0), yes (1)) Whether you have a membership in political club (Q: We would like to know something about the groups or organizations to which indi viduals belong. Here is a list of various

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102 organizations. Could you tell me whether or not you are a member of political club? no (0), yes (1)) Whether you have a membership in labor un ion (Q: We would like to know something about the groups or organizations to which indi viduals belong. Here is a list of various organizations. Could you tell me whether or no t you are a member of labor union? no (0), yes (1)) Whether you have a membership in sports club (Q: We would like to know something about the groups or organizations to which indi viduals belong. Here is a list of various organizations. Could you tell me whether or no t you are a member of sports club? no (0), yes (1)) Whether you have a membership in youth gr oup (Q: We would like to know something about the groups or organizations to which indi viduals belong. Here is a list of various organizations. Could you tell me whether or no t you are a member of youth group? no (0), yes (1)) Whether you have a membership in school se rvice (Q: We would like to know something about the groups or organizations to which indi viduals belong. Here is a list of various organizations. Could you tell me whether or not you are a member of school service? no (0), yes (1)) Whether you have a membership in hobby cl ub (Q: We would like to know something about the groups or organizations to which indi viduals belong. Here is a list of various organizations. Could you tell me whether or not you are a member of hobby club? no (0), yes (1)) Whether you have a membership in school fraternity (Q: We would like to know something about the groups or organizations to which individuals belong. Here is a list of various organizations. Could you tell me wh ether or not you are a member of school fraternity? no (0), yes (1)) Whether you have a membership in nati onality group (Q: We would like to know something about the groups or organizations to which individuals belong. Here is a list of various organizations. Could you tell me whet her or not you are a member of nationality group? no (0), yes (1)) Whether you have a membership in farm organization (Q: We would like to know something about the groups or organizations to which individuals belong. Here is a list of various organizations. Could you tell me wh ether or not you are a member of farm organization? no (0), yes (1)) Whether you have a membership in liter ary or art group (Q: We would like to know something about the groups or organizations to which individuals belong. Here is a list of various organizations. Could you tell me whet her or not you are a member of art group? no (0), yes (1))

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103 Whether you have a membership in church group (Q: We would lik e to know something about the groups or organizations to which indi viduals belong. Here is a list of various organizations. Could you tell me whether or not you are a member of church group? no (0), yes (1)) Whether you have a membership in veteran group (Q: We would lik e to know something about the groups or organizations to which indi viduals belong. Here is a list of various organizations. Could you tell me whether or not you are a member of veteran group? no (0), yes (1)) Whether you have a membership in profe ssional society (Q: We would like to know something about the groups or organizations to which individuals belong. Here is a list of various organizations. Could you tell me whet her or not you are a member of professional society? no (0), yes (1)) Whether you have a membership in any othe r (Q: We would like to know something about the groups or organizations to which indi viduals belong. Here is a list of various organizations. Could you tell me whether or no t you are a member of any other? no (0), yes (1)) *Allan Cigler and Mark Joslyn (2002)s study, The extensiveness of group membership and social connectedness Table A-2. Factor Analysis on Social Network Extensiveness Factor Component membership in fraternal group 0.419 membership in service group 0.595 membership in veteran group 0.228 membership in political club 0.384 membership in labor union 0.249 membership in sports club 0.552 membership in youth group 0.558 membership in school service 0.560 membership in hobby club 0.439 membership in school fraternity 0.398 membership in nationality group 0.245 membership in farm organization 0.235 membership in literary or art group 0.521 membership in professional society 0.614 membership in church group 0.623 membership in any other 0.292

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104 General Social Trust (Mea n of three trust scale) Whether people helpful or looking out for them selves (Q: Would you say that most of the time people try to be helpful, or that they are mostly just looking out for themselves? Not helpful (1), Depends (2), Helpful (3)) Whether people are fair or try to take advantage of others (Q: Do you think most people would try to take advantage of you if they got a chance, or would they try to be fair? Take advantage (1), Depends (2), Fair (3)) Whether people can be trusted (Q: Generally speaking, would you say that most people can be trusted or that you can't be too careful in life? Cannot trust (1), Depends (2), Trust (2)) *Putnam (2000); Letki (2004); James Gibson (2001)s index Table A-3. Factor Analysis on General Social Trust Factor Component Helpful 0.780 Trust 0.735 Fair 0.795

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105 APPENDIX B POLICY ATTITUDES Redistributive Policy Whether government should reduce income di fferences (Q: Some pe ople think that the government in Washington ought to reduce the income differences between the rich and the poor, perhaps by raising the taxes of wealt hy families or by giving income assistance to the poor. Others think that th e government should not concer n itself with reducing this income difference between the rich and the poor. Here is a card with a scale from 1 to 7. Think of a score of 7 as meaning that the government ought to reduce the income differences between rich and poor, and a score of 1 meaning that the government should not concern itself with reducing income diff erences. What score between 1 and 7 comes closest to the way you feel? (Government should not (1), Government should (7)) Whether government should improve standard of living (Q: I'd like to talk with you about issues some people tell us are important. Plea se look at CARD BC. Some people think that the government in Washington should do everyt hing possible to improve the standard of living of all poor Americans; th ey are at Point 1 on this ca rd. Other people think it is not the government's responsibility, and that each pe rson should take care of himself; they are at Point 5. Where would you place yourself on th is scale, or haven't you have up your mind on this? (Rescaled to Government shoul d not (1), Governme nt should (7)) Whether government should help pay for medi cal care (Q: In genera l, some people think that it is the responsibility of the government in Washington to see to it that people have help in paying for doctors and hospital bills. Others think that these matters are not the responsibility of the federal gove rnment and that people should take care of these things themselves. Where would you place yourself on this scale, or haven't you made up your mind on this? (Government should not (1), Government should (7)) Table B-1. Factor Analysis on Redistributive Policies Factor Component improve standard of living 0.816 reduce income should government reduce income differences 0.784 help pay for medical care 0.740 Government Activism Whether government needs to do more to im prove & protect national health (Q: We are faced with many problems in this country, none of which can be solved easily or inexpensively. I'm going to name some of th ese problems, and for each one I'd like you to tell me whether you think we're spending too mu ch money on it, too little money, or about the right amount. Are we spending too muc h, too little, or about the right amount on improving & protecting nations health? Too much done (1), About Right (4), Too little done (7))

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106 Whether government needs to do more to im prove nations education system (Q: We are faced with many problems in this country, none of which can be solved easily or inexpensively. I'm going to name some of th ese problems, and for each one I'd like you to tell me whether you think we're spending too mu ch money on it, too little money, or about the right amount. Are we spending too muc h, too little, or about the right amount on improving national education system? Too much done (1), About Right (4), Too little done (7)) Whether government needs to do more to improve & protect environment (Q: We are faced with many problems in this country, none of which can be solved easily or inexpensively. I'm going to name some of th ese problems, and for each one I'd like you to tell me whether you think we're spending too mu ch money on it, too little money, or about the right amount. Are we spending too muc h, too little, or about the right amount on improving and protecting the envi ronment? Too much done (1), About Right (4), Too little done (7)) Whether government needs to do more to so lve problems of big ci ties (Q: We are faced with many problems in this country, none of wh ich can be solved eas ily or inexpensively. I'm going to name some of these problems, a nd for each one I'd like you to tell me whether you think we're spending too much money on it, too little money, or about the right amount. Are we spending too much, too litt le, or about the right amount on solving problems of big cities? Too much done (1), About Right (4), Too little done (7)) Table B-2. Factor Analysis on Government Activism Factor Component improving & protecting nations health 0.829 improving nations education system 0.823 improving & protecting environment 0.782 solving problems of big cities 0.576 Morality policy On Abortion Whether allow abortion: Defect in the baby (Q : Please tell me whether or not you think it should be possible for a pregnant woman to obtain a legal abortion, if there is a strong chance of serious defect in the baby? No (1), Yes (7)) Whether allow abortion: No more children (Q: Please tell me whether or not you think it should be possible for a pregnant woman to obt ain a legal abortion If she is married and does not want any more children? No (1), Yes (7) Whether allow abortion: Endangered by the pregnancy (Q: Please tell me whether or not you think it should be possible for a pregnant woman to obt ain a legal abortion, if the woman's own health is seriously endangere d by the pregnancy? No (1), Yes (7))

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107 Whether allow abortion: Poverty (Q: Please te ll me whether or not you think it should be possible for a pregnant woman to obtain a legal abortion, if the family has a very low income and cannot afford any more children? No (1), Yes (7)) Whether allow abortion: Rape (Q: Please te ll me whether or not you think it should be possible for a pregnant woman to obtain a legal abortion, if she became pregnant as a result of rape? No (1), Yes (7)) Whether allow abortion: Unwanted marriage (Q : Please tell me whethe r or not you think it should be possible for a pregnant woman to obt ain a legal abortion, if she is not married and does not want to marry the man? No (1), Yes (7)) Whether allow abortion: Any reason (Q: Please tell me whether or not you think it should be possible for a pregnant woman to obtain a legal abortion, if the woman wants it for any reason? No (1), Yes (7)) Table B-3. Factor Analysis on Abortion Factor Component not married 0.889 wants no more children 0.872 cant afford more children 0.871 any reason 0.866 serious defect 0.717 rape 0.693 health seriously endangered 0.584 On Gay Rights Whether allow homosexual sex relations (Q: What about sexual relations between two adults of the same s e x d o you think it is always wrong, almost always wrong, wrong only sometimes, or not wrong at all? Always wrong (1), Almost always wrong (3), Depends (4), Sometimes wrong (5), Not wrong at all (7)) Whether allow homosexual to speak (Q: Should a men who admits that he is a homosexual be allowed to speak and make a speech in your community, or not? Not allow(1), Allow(7)) Whether allow homosexuals to teach (Q: Should a men who admits that he is a homosexual be allowed to teach in a collage or university, or not? Not allow(1), Allow(7)) Whether allow homosexuality books(Q: If some people in your community suggested that a book he wrote in favor of homosexuality should be taken out of your public library, would you favor removing this book, or not? Remove(1), Not Remove(7))

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108 Table B-4. Factor analysis on gay rights Factor Component homosexual to teach 0.826 homosexual to speak 0.810 homosexuals book in library 0.769 homosexual sex relations 0.605

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119 BIOGRAPHICAL SKETCH Hyun Jung Yun grew up in South Korea and completed her undergraduate work majoring in Political Science at Ajou University. Starti ng with her undergraduate senior year as an exchange student, she continued her masters de gree studying in political science and doctorate in the fields of political sc ience and journalism and communi cations at the University of Florida in the United States of America Her research interests are in political perception, the poli tical communication process, policy attitudes, persuasion, and geopolitics across different levels of the individual, small group, and aggregate group. More specifically, her rese arch in the field of political communication explores the relationship between political in formation process and individuals political attitudes in different geopolitical circumstance. In the same line of interdisciplinary research, her research in political science investigates how individuals beliefs a bout various policies are influenced by varying levels of multi-dimensi onal social capital and communication networks. Her research in journal publications demons trates how individuals political perceptions and attitudes are influenced by pol itical predispositions within a group and by political resources within a given political and media system at the aggregate level. In addition, she had coauthored several book chapters examining news coverage of policy issues and political candidates across different political regions to obs erve the relationship between di fferent political characteristics and political information effects. She is cu rrently working on analyz ing the dual spirals of silence in policy opinion form ation between issue minority an d issue majority, effects of relationship between media and pol itics on voter perceptions, as we ll as political cynicism and information efficacy in young voters. She also has participated in grant-suppor ted research projects including the Florida Department of Healths 2004 Project in Medi a Terrorism Preparation under Dr. Mary Ann

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120 Ferguson and Dr. Lynda Lee Kaid, Uvote inter-un iversity research on U. S. elections under Dr. Lynda Lee Kaid, and United States Election Assistance Commissions project establishing election law database under Dr. Lynda Lee Kaid a nd Dr. Cliff Jones The former project dealt with media advocacy, government public informa tion, and issue management on terrorism. The Uvote research has focused on political advocac y and political information effects. The development of electronic database of U.S. elect ion laws intended to provide U.S. citizens easy internet search function for comprehensive U.S. el ection law. She has worked for these projects as a data analyst and project manager. She also worked as data archiving assist ant for ICPSR (Inter-university Consortium for Political and Social Research) for a part of gr aduate assistantship duty. She was trained in advanced methodology through ICPSR as well as by the departments of statistics, political science, and journalism and mass communications Her methodological training across different fields includes managements of da ta through various applications a nd various levels of statistics such as linear regression, categorical anal ysis, multivariate analysis, maximum likelihood analysis, game theory, content anal ysis, scaling, and measurement. Her next project is to collect linearly coherent multi-level data that li nks individual perceptions, attitudes, and pr eferences with the aggregate level of media and political predispositions in different pol itical regions, election turnouts, policy efficiency, and other media-politics routines in order to conduct research with theoreti cally reliable connections across different levels of dynamics. Hyun Jung Yun who has two doctorate degrees, one in political scienc e and the other in journalism and communications, will work as an assistant professor at Texas State University starting from August 2007.