• TABLE OF CONTENTS
HIDE
 Title Page
 Acknowledgement
 Table of Contents
 List of Tables
 List of Figures
 Abstract
 Introduction
 Research design
 Characteristics of the populat...
 Construction of the scales
 Attitudinal profiles of scient...
 Summary and suggestions for future...
 Appendix
 Bibliography
 Biographical sketch














Group Title: attitudinal profile of selected scientists in the university and Federal government
Title: An attitudinal profile of selected scientists in the university and Federal government
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 Material Information
Title: An attitudinal profile of selected scientists in the university and Federal government
Physical Description: xi, 150 leaves : ; 28 cm.
Language: English
Creator: Watkins, George A
Publication Date: 1970
Copyright Date: 1970
 Subjects
Subject: Scientists -- United States   ( lcsh )
Sociology thesis Ph. D   ( lcsh )
Dissertations, Academic -- Sociology -- UF   ( lcsh )
Genre: bibliography   ( marcgt )
non-fiction   ( marcgt )
 Notes
Thesis: Thesis - University of Florida.
Bibliography: Bibliography: leaves 143-149.
Additional Physical Form: Also available on World Wide Web
General Note: Manuscript copy.
General Note: Vita.
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Volume ID: VID00001
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notis - ACX9136

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Table of Contents
    Title Page
        Page i
    Acknowledgement
        Page ii
    Table of Contents
        Page iii
        Page iv
    List of Tables
        Page v
        Page vi
        Page vii
    List of Figures
        Page viii
    Abstract
        Page ix
        Page x
        Page xi
    Introduction
        Page 1
        Page 2
        Page 3
        Page 4
        Page 5
        Page 6
        Page 7
        Page 8
        Page 9
        Page 10
        Page 11
        Page 12
        Page 13
        Page 14
        Page 15
        Page 16
        Page 17
        Page 18
        Page 19
        Page 20
        Page 21
        Page 22
    Research design
        Page 23
        Page 24
        Page 25
        Page 26
        Page 27
        Page 28
        Page 29
    Characteristics of the population
        Page 30
        Page 31
        Page 32
        Page 33
        Page 34
        Page 35
        Page 36
        Page 37
        Page 38
        Page 39
        Page 40
        Page 41
        Page 42
        Page 43
        Page 44
        Page 45
        Page 46
        Page 47
        Page 48
        Page 49
        Page 50
        Page 51
    Construction of the scales
        Page 52
        Page 53
        Page 54
        Page 55
        Page 56
        Page 57
        Page 58
        Page 59
        Page 60
        Page 61
        Page 62
        Page 63
        Page 64
        Page 65
        Page 66
        Page 67
        Page 68
    Attitudinal profiles of scientists
        Page 69
        Page 70
        Page 71
        Page 72
        Page 73
        Page 74
        Page 75
        Page 76
        Page 77
        Page 78
        Page 79
        Page 80
        Page 81
        Page 82
        Page 83
        Page 84
    Summary and suggestions for future research
        Page 85
        Page 86
        Page 87
        Page 88
        Page 89
        Page 90
        Page 91
        Page 92
        Page 93
        Page 94
    Appendix
        Page 95
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        Page 136
        Page 137
        Page 138
        Page 139
        Page 140
        Page 141
        Page 142
    Bibliography
        Page 143
        Page 144
        Page 145
        Page 146
        Page 147
        Page 148
        Page 149
    Biographical sketch
        Page 150
        Page 151
Full Text





AN ATTITUDINAL PROFILE OF SELECTED SCIENTISTS

IN THE UNIVERSITY AND FEDERAL GOVERNMENT















By
GEORGE ALFRED WATKINS















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











UNIVERSITY OF FLORIDA









ACKNOWLEDGMENTS


The work upon which this dissertation is based was supported

in part by funds provided by the University of Florida's NASA Institu-

tional Grant to the Department of Sociology. This writer is indebted

to Dr. E. Wilbur Bock and Professor Sugiyama lutaka, principal investi-

gators for the project, for their advice and efforts in designing the

research and in construction of the interview schedule used for col-

lecting the data.

Dr. Gerald R. Leslie, Chairman of the Department of Sociology

and Chairman of the Supervisory Committee, and Dr. Benjamin L. Gorman

have given freely of their time to this writer. Their efforts are

sincerely appreciated, as are the many "sociological insights" gained

by this writer from working with them., Dr. Richard F. Larson and

Dr. Austin B. Creel are to be thanked for. their helpful suggestions

in the writing of this dissertation.

Special thanks are extended to Miss Nancy Cooper, student assist-

ant to the principal investigators, for her assistance and demonstrated

competence in the compilation of the data.

If this dissertation makes a contribution to sociology it is due

primarily to the efforts of these persons and others in the Department

of Sociology at the University of Florida. This writer assumes full

responsibility for any errors of commission or omission contained

within this dissertation.








TABLE OF CONTENTS


Page

ACKNOWLEDGMENTS.................................................... ii

LIST OF TABLES..................................................... v

LIST OF FIGURES................................................... viii

ABSTRACT........................................................... ix

CHAPTER

I INTRODUCTION ..............................................

Theoretical Relationship of Institutions
to Attitudes................................... .
Theoretical Relationship of Attitudes to
Behavior........................................ 3
Institutionalized Scientific Norms and
Attitudes....................................... 7
Federal Funding of Research.......................... 9
Specific Hypotheses to be Tested..................... 18

II RESEARCH DESIGN............................................ 23

Sampling Procedures................................... 24
Data Collection....................................... 27
Data Processing and Analysis......................... 28

II CHARACTERISTICS OF THE POPULATION ......................... 30

Area of Specialization............................... 30
Sex................................................. 32
Age .................................................. 32
Education............................................. 34
Father's Education................................... 36
Father's Social Status ............................... 38
Geographic Mobility.................................. 41
Family Size.......................................... 44
Religious Affiliation................................ 47
Summary .............................................. 47

IV CONSTRUCTION OF THE SCALES................................ 52

Ideal Scientific Orientation Scale................... 54








TABLE OF CONTENTS (continued)


Page

CHAPTER

VI (continued)

Commitment Scale................................. 59
Job Satisfaction Scale ........................... 63
Summary .......................................... 65

V ATTITUDINAL PROFILES OF SCIENTISTS.................... 69

Tests of Major Hypotheses........................ 69
Other Hypotheses Tested ................... ...... 72
Discussion ....................................... 78

VI SUMMARY AND SUGGESTIONS FOR FUTURE RESEARCH........... 85

Suggestions for Future Research.................. 91

APPENDIX A.......................:............................ 95

APPENDIX B .................................................... 120

BIBLIOGRAPHY.................................................. 143

BIOGRAPHICAL SKETCH ............................................. 150








LIST OF TABLES


ble Page

1 NUMBER AND PERCENTAGE DISTRIBUTION OF SCIENTISTS,
BY JOB SITUATION.................................. 25

2 PERCENTAGE DISTRIBUTION OF SCIENTISTS' AREAS
OF SPECIALIZATION, BY JOB SITUATION.............. 31

3 NUMBER AND PERCENTAGE DISTRIBUTION OF SCIENTISTS'
AGES, BY JOB SITUATION........................... 33

4 NUMBER AND PERCENTAGE DISTRIBUTION OF SCIENTISTS'
HIGHEST ACADEMIC DEGREE, BY JOB SITUATION......... 35

5 NUMBER OF PERCENTAGE DISTRIBUTION OF SCIENTISTS'
FATHERS' EDUCATION USING SIX CATEGORIES,
BY JOB SITUATION.................................. 37

6 NUMBER AND PERCENTAGE DISTRIBUTION OF SCIENTISTS'
FATHERS' SOCIAL STATUS IN THREE CATEGORIES,
BY JOB SITUATION ................................... 40

7 NUMBER AND PERCENTAGE DISTRIBUTION OF MOVES OF
SCIENTISTS BEFORE FIRST JOB, BY JOB SITUATION.... 42

8 NUMBER AND PERCENTAGE DISTRIBUTION OF MOVES OF
SCIENTISTS AFTER FIRST JOB, BY JOB SITUATION..... 43

9 NUMBER AND PERCENTAGE DISTRIBUTION OF SIZE OF
SCIENTISTS' FAMILIES OF ORIENTATION, BY
JOB SITUATION.................................... 45

10 NUMBER AND PERCENTAGE DISTRIBUTION OF SIZE OF
SCIENTISTS' FAMILIES OF PROCREATION, BY
JOB SITUATION..................................... 46

)1 NUMBER AND PERCENTAGE DISTRIBUTION OF SCIENTISTS'
RELIGIOUS AFFILIATIONS, BY JOB SITUATION......... 48

12 FACTOR MATRIX OF ATTITUDES ON IDEAL SCIENTIFIC
ORIENTATION ..................................... 56

13 RANK-ORDER OF FACTORSBY MEAN LOADINGS OF ATTITUDES,
ON IDEAL SCIENTIFIC ORIENTATION.................. 59

14 COMPARISON BETWEEN THE GUTTMAN SCALE SCORES AND
FACTOR MATRIX RANKING OF FINAL TEN ITEMS
ON IDEAL SCIENTIFIC ORIENTATION.................. 60








LIST OF TABLES (continued)


Table Page

15 IDEAL SCIENTIFIC ORIENTATION SCALOGRAM ................ 61

16 FINAL SEVEN ITEMS IN THE COMMITMENT SCALE............. 63

17 COMMITMENT SCALOGRAM .................................. 64

18 FINAL TEN ITEMS FOR THE JOB SATISFACTION SCALE......... 66

19 JOB SATISFACTION SCALOGRAM ............................ 67

20 TESTS FOR DIFFERENCES ON IDEAL SCIENTIFIC
ORIENTATION SCALE SCORES, NASA AND
UNIVERSITY SCIENTISTS............................ 70

21 TESTS OF ASSOCIATION BETWEEN IDEAL SCIENTIFIC
ORIENTATION AND COMMITMENT SCALE SCORES,
TOTAL SAMPLE AND SELECTED SUBSAMPLES............. 71

22 TESTS OF ASSOCIATION BETWEEN JOB SATISFACTION
AND COMMITMENT SCALE SCORES, TOTAL SAMPLE
AND SELECTED SUBSAMPLES.......................... 72

23 TESTS FOR DIFFERENCES ON JOB SATISFACTION
SCALE SCORES, NASA AND UNIVERSITY SCIENTISTS..... 75

24 TESTS FOR DIFFERENCES ON COMMITMENT SCALE
SCORES,NASA AND UNIVERSITY SCIENTISTS............ 77

25 TESTS OF ASSOCIATION BETWEEN IDEAL SCIENTIFIC
ORIENTATION AND JOB SATISFACTION SCALE
SCORES, TOTAL SAMPLE AND SELECTED SUBSAMPLES..... 78

26 NUMBER AND PERCENTAGE DISTRIBUTION OF SEX OF
SCIENTISTS, BY JOB SITUATION.................... 121

27 NUMBER AND PERCENTAGE DISTRIBUTION OF SCIENTISTS'
FATHERS' SOCIAL STATUS IN NINE CATEGORIES,
BY JOB SITUATION................................. 122

28 NUMBER AND PERCENTAGE DISTRIBUTION OF SCIENTISTS'
MARITAL STATUS, BY JOB SITUATION................. 123








LIST OF TABLES (continued)


Table Page

29 ITEM SET WITH ASSIGNED SUBUNIVERSES AND PERCENTAGE
DISTRIBUTION OF FAVORABLE RESPONSES FOR IDEAL
SCIENTIFIC ORIENTATION ........................... 124

30 COMPLETE FACTOR MATRIX OF ITEMS ON IDEAL SCIENTIFIC
ORIENTATION....................................... 129

31 FREQUENCY AND DISTRIBUTION OF RESPONSES FOR FINAL
TEN ITEMS ON IDEAL SCIENTIFIC ORIENTATION......... 133

32 PERCENTAGE OF FAVORABLE RESPONSES ON ITEMS FOR
INCLUSION IN COMMITMENT SCALE.................... 136

33 FREQUENCY AND DISTRIBUTION OF RESPONSES FOR FINAL
SEVEN ITEMS IN THE COMMITMENT SCALE.............. 137

34 PERCENTAGE OF FAVORABLE RESPONSES TO ITEMS ON
JOB SATISFACTION..... ........................... 139

35 FREQUENCY AND DISTRIBUTION OF RESPONSES FOR FINAL
TEN ITEMS ON JOB SATISFACTION SCALE.............. 140








LIST OF FIGURES


Figure Page

1 Test of Relationship Between Job Satisfaction and
Commitment Scale Scores When Scientist's Job
Situation Is Controlled.......................... 73

2 Relationship Between Ideal Scientific Orientation
and Commitment Scale Scores, University NASA
Scientists, University Non-NASA Scientists,
and Federal NASA Scientists By Age Categories.... 81








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

AN ATTITUDINAL PROFILE OF SELECTED SCIENTISTS
IN THE UNIVERSITY AND FEDERAL GOVERNMENT

By

George Alfred Watkins

August, 1970

Chairman: Dr. Gerald R. Leslie
Major Department: Sociology


Science as an institution is considered to be normative for

scientists trained within it. Scientists learn and/or acquire a set

of values, beliefs, and attitudes within the institutional framework

of science which governs their behavior. As the scientists move into

job situations, their attitudes about science and about their jobs

merge into a competitive framework. If science is normative for all

scientists regardless of whether they are working in industry, federal

government, or in a university, then some "universal" attitudes about

science should be discernible among them.

Working with data collected from a University of Florida NASA

Institutional Grant to the Department of Sociology, the normative

aspects of science as an institution are examined. Through the con-

struction of an Ideal Scientific Orientation Scale, a Commitment Scale,

and a Job Satisfaction Scale, the following hypotheses are tested:

(1) There is no difference in the ideal scientific orientation of







scientists in the university and scientists in federal NASA projects;

(2) The higher the ideal scientific orientation scores of scientists,

the more they will adhere to their commitment in practice; (3) There

is no relationship between job satisfaction and the effectiveness of

scientists; (4) There are no differences in job satisfaction between

scientists in the university and scientists in federal NASA projects;

(5) There is no difference in the degree of professional commitment

of university and federal scientists; and (6) There is no relationship

between scientists' ideal scientific orientations and their job satis-

faction.

The above hypotheses are tested on samples of scientists from

the University of Florida consisting of scientists who have received

NASA Institutional Grants from the university and scientists in the

same departments who have not received such grants, as well as a sample

of scientists from the Goddard Space Flight Center, Greenbelt,

Maryland, and from the Marshal Space Flight Center, Huntsville, Ala-

bama. The results indicate that there is an overriding scientific

norm along which the scientists in the sample can be scaled using

the Guttman scaling technique. It is further determined that dif-

ferences in commitment and job satisfaction do exist, with university

scientists holding NASA grants being the most committed and more

satisfied with their jobs than the federal NASA scientists. Job

situation seems to be the variable most affecting the scientists'

commitment.







It is suggested that since differences in commitment and job

satisfaction exist, the implications of these differences be explored

further. Other suggestions are made reflecting the differences found

among the scientists in the various samples.












CHAPTER I

INTRODUCTION


Science is an institution. As an institution, science possesses

shared and transmitted values and normative attitudes which define the

permissible patterns of behavior. Science, like other socially organized

activities, is a moral enterprise. This implies that the culture of

science is more than habitual behavior. Its norms codify the values

and attitudes which are judged appropriate for men (Kaplan, 1965:112).


Theoretical Relationship of Institutions to Attitudes

When people, with their own individual experiences and attitudes,

come together over a period of time there arises a collective attitude

from the experience of their sustained relationships and the merging

of their individual attitudes. The set of values, beliefs, and attitudes

which arises in this process, called institutionalization, becomes

normative for the individual and becomes a reference point for his future

behavior. After the individual has been socialized by the experience in

the institution he takes with him in future interaction the new attitudes

which he has acquired.

When a group of people are working together over
some time, their emergent behavior tends to be-
come their customary way of behaving. Out of this
extended emergent interaction and activity and
sentiment develop notions shared by all about what
the members of the group ought to do under given
circumstances. These notions we will call norms.
Norms are not what people most often actually do
(the mean average, for example). Norms are what
people in a group think they ought to do under
given circumstances (Athos and Coffey, 1968:88).











A norm is considered to be institutionalized when two conditions

are met. First, a great number of the members of the social system

accept the norm and internalize it. Second, the norm becomes sanctioned

and members are expected to be guided by the norm in appropriate cir-

cumstances (Johnson, 1960:20). It must be noted that even though an

institution is recognized as normative, very few, if any, social insti-

tutions completely exhaust the normative patterning of any relationship.

.one of the ways in which social norms may
vary, certainly, is in the degree of agreement
among those who are subject to them concerning
the exact range of permissible behavior (Johnson,
1960:28).

Thomas and Znaniecki (1918) in writing about the study of sociology

emphasize that it is a special science devoted to the study of relation-

ships between attitudes and a special category of values called social

rules. Attitudes become part of an individual's orientation to action

based on some social value which arose out of the institution (Thomas

and Znaniecki, 1918:56 et passim). An individual's attitudes after his

socialization in the institutional process differ from his previous

attitudes. This may be conceptualized briefly by tracing this process.

When individuals experience affective, evaluative, and/or cogni-

tive discrepancies in their experiences, they may come together to

articulate the recognized discrepancy. From the process of articulation

come recognized needs which lead to action or non-action, which are

expressed by "collective consent." The final stage in the change of

the individual's attitudes to those of the collectivity becomes expressed

in the institutionalization process.










Institutionalization may be defined as a process
consisting of changes in established patterns of
interaction and/or the development and substitution
of new patterns of interaction for previous ones,
resulting from the more or less reciprocal actions
of more than one actor (Zollschan and Hirsch, 1964:
91).

Science has undergone such an institutionalization process. As

an institution, science possesses shared norms and attitudes which are

passed on in the socializing of neophyte scientists. Depending upon the

initial commitment of the neophyte, the intensity of his socialization,

and the availability of other scientists to teach the neophyte, the

socialization process will have appropriate outcomes (Brim and Wheeler,

1967:60 et passim).


Theoretical Relationship of Attitudes to Behavior

It is also important in the investigation of the normative atti-

tudes of science to understand the relationship between attitudes and

behavior. That this relationship is regarded as problematic can be seen

from the tremendous amount of literature directed to it. For example,

Thomas and Znanecki, in trying to describe the study of attitudes in

a social-psychological framework, state:

By attitude we understand a process of individual
consciousness which determines real or possible
activity of the individual (Thomas and Znaniecki,
1918:22).

More "current" definitions also imply a relationship between

attitudes and behavior. Attitudes are seen as: (I) implying charac-

teristic modes of readiness in reacting to objects, situations, and

persons (Sherif, 1952:262); (2) being expressions, by words or deeds,











of one's reaction toward or feeling about persons, things, or situa-

tions, representing the subjective sum of one's inclinations, prejudices,

preconceived notions, ideas, and convictions (Horrocks, 1964:678); and

(3) as being a relatively enduring organization of beliefs around some

object or situation predisposing one to respond in a preferential manner

(Rokeach, 1968:112).

The last definition of an attitude is particularly useful in try-

ing to define the relationship of attitudes to behavior. An attitude

represents a cluster of two or more interrelated elements, or underlying

beliefs.

A belief is any simple proposition, conscious or
unconscious, inferred from what a person says or
does, capable of being preceded by the phrase,
"I believe that" . (Rok'each, 1968:113).

Beliefs, whether descriptive, evaluative, or prescriptive, are

predispositions to action. This implies that an attitude is a set of

interrelated predispositions to action, which according to Rokeach's

definition of attitude, are organized around an object or situation.

Important in the concept of attitude is the necessity of shared

"criteria referents." This implies that one can assume a continuum

of relevance for any referent, which is differentially shared.

Attitudes have been traditionally conceived of as having three

components. Breer and Locke (1965:37), for example, use attitude to

refer to three kinds of orientations: cathectic (preferences), cogni-

tive (beliefs), and evaluative (values). Beliefs within an attitude

organization have also been conceived of as having three components:










(1) cognitive, since it represents one's knowledge which is held with

varying degrees of certitude; (2) affective, which refers to the elicit-

ing of varying degrees of intensity under certain conditions; and

(3) behavioral, since the belief is a response predisposition of varying

intensity and therefore should lead to action when properly activated

(Rokeach, 1968:113-114). Rokeach's view is consistent with that of

Breer and Locke in that attitudes have cognitive and affective proper-

ties by virtue of the fact that the interrelated beliefs comprising

them have interdependent cognitive and affective properties.

That an attitude has a behavioral component can be shown by

considering briefly the several dimensions which are employed in describ-

ing the attitudinal organization.

These dimensions can with more or less equal
ease be employed to describe the organization
of (1) the several beliefs contained within an
attitude, (2) several attitudes within a more
inclusive, attitude system, or (3) all of man's
beliefs, attitudes, and values within his total
cognitive system. It should be stressed that
a change in one part produces a cognitive strain
or inconsistency within the system, thus giving
rise to forces leading to reorganization in the
whole system (Rokeach, 1968:116-117).

Sherif (1952), Horrocks (1964), Rokeach (1968), Thomas and

Znaniecki (1918), Halbgewachs (1965), and Fendrich (1967) all imply that

the traditional relationship between attitudes and behavior is a causal

one. That is, an attitude is a predisposition of some sort, whether


IAlthough Halbgewachs (1965) and Fendrich (1967) write about this
traditional relationship, both deal extensively with the difficulty
involved in predicting behavior from attitudes. Halbgewachs states that
the difficulty is one of measurement and inconsistency with social experi-
ence, while Fendrich writes that the difficulty is the restriction of most












it is a predisposition to respond, to evaluate, to be motivated, or to

act. For the purposes of this study, predisposition to respond is

understood to mean responding either verbally or nonverbally. It is

further understood that that which is being referred to is the situa-

tion in which the respondent is being presented with "symbols" which

elicit responses according to his own definition of the situation. An

attitude then represents an organization of beliefs and it has a be-

havioral component since the beliefs comprising an attitude, regardless

of whether they describe, evaluate, or advocate, represent predisposi-

tions which, when activated, lead to response (Rokeach, 1968:120).

An attitudinal response does not occur in a vacuum. It must be

elicited in the context of some social situation. If one is concerned

about social behavior, one must recognize that the individual responds

not only to the object, but also to the situation. Behavior is thus a

function of the interaction between two attitudes--attitude-toward-

object and attitude-toward-situation (Rokeach, 1968:127).

It is Thomas and Znaniecki (1918) who note that,in addition to

the attitudes which express themselves directly in individual actions,

one can also find an:

.indirect manisfestation in more or less
explicit and formal rules of behavior by which the
group tends to maintain, to regulate, and to make
general and more frequent the corresponding type of
action among its members (Thomas and Znaniecki, 1918:31).

attitudinal research to theoretical monism. It is assumed for the pur-
poses of this study that there is some sort of causal relationship
between attitudes and behavior with recognition that both situational
experiences and other intervening variables may be confounding variables
in the test of the relationship.











These rules of behavior may be treated in at least two ways.

First, one may consider them to be manifestations of attitudes since

the group demands specified behavior and the attitude which elicits

this behavior is supposedly shared by all members. Second, since the

rule exists at all, it is implied that there are contra-actions which

are suppressed by the rules. The relevance of the rules for the members

of the group is differentially shared and therefore for each member

the rules have different levels of intensity.


Institutionalized Scientific Norms and Attitudes

The morality of science is largely responsible for its social

organization in the United States. If one searches the

.writings about the "scientific attitude,"
especially when they come from the pens of
experienced scientists, we can find a very large
area of agreement about the integrating moral com-
ponents of science (Barber, 1953:85).

Barber identified five such areas of agreement which represent

ideal ethical standards in science. They are the ideals of "ration-

ality," "universalism," "individualism," "communality," and "disin-

terestedness." They are the governing norms of science which are more

influential in pure scientific settings than in applied settings

(Barber, 1953:88 et passim).2


For Barber, "pure science is defined as science which is pri-
marily and immediately devoted to the development of conceptual schemes,
such development including their extension, revision, and testing, an
inherently endless process of establishing provisional truth. Applied science
issciencewhich is devoted to making conceptual schemes instrumental to
some other social purpose than that of the pursuit of conceptual schemes
and ends-in-themselves" (Barber, 1953:95). Although such a strict dichotomi-
zation of science is rejected by some (i.e., Kidd, 1959 and Bryson, 1947),
it will serve as the basic division of science for this study.











Characteristic of science as an institution and as a moral enter-

prise are the patterns of potentially conflicting pairs of norms which

arise within it. Merton notes several institutionalized pairs of norms

which are tension creating for the scientist. Among those he lists are

the following: (1) the scientist must be ready to make his newfound

knowledge available to his peers as soon as possible, but he must avoid

an undue tendency to rush into print; (2) the scientist should make

every effort to know the work of predecessors and contemporaries in his

field, but he should defend his new ideas and erudition will only

stultify creative work; (3) scientific knowledge is universal, belong-

ing to no nation, but each scientific discovery does honor to the nation

that fostered it; and (4) the scientist should recognize his prime

obligation to train new generations of scientists, but he must not

allow teaching to preempt his energies at the expense of advancing

knowledge (Kaplan, 1965:113). Such normative contradictions within

the institution of science contribute to the ambivalence felt by

scientists in their work.

In addition to the conflicting norms recognized by Merton, the

scientist's orientation to social responsibility has been seen as a

cause of ambivalence. Although the social responsibility of science

and of scientists has been at least implicitly recognized for many

years (Kaplan, 1965), concern in this country over the social responsi-

bility of scientists has deepened only since the Manhattan Project.


These norms are restated in Perrucci and Gerstl (1969:41-44).

As noted by Barber (1953), this increased concern has been more
manifest among scientists than among any other group.











Among the positions taken by scientists regarding their social

responsibility are at least the following: (1) scientists have some

general kind of social responsibility for the consequences of their

discoveries and are therefore obligated to consider their position

in society with a more precise definition of their social responsi-

bility; (2) scientists should accept total responsibility for the social

consequences of science and try to prevent the most harmful ones; and

(3) scientists should resent the unwarranted acceptance of too much

social responsibility and the imposition of such responsibility by

laymen (Barber, 1953:225 et passim). For Barber, positions (2) and

(3), which represent, respectively, full responsibility and an "ivory

tower" approach, are too extreme and therefore untenable. Barber

favors the first position with additional emphasis to be placed on the

study of the social and political processes themselves. The latter

represent channels through which scientific findings are implemented.


Federal Funding of Research

The importance of the political channel to scientists' "pre-

cise definition of their social responsibility" can be witnessed by the

increasing participation of the federal government in research in this

country. Although efforts were made to keep science and politics

separate, through such devices as the establishment of the Smithsonian

Institute and the National Academy of Sciences, it seems inevitable

that the federal government in this country would commit itself to

science. At least two circumstances contribute to the increase in












federal government's involvement. First, the federal government is

increasingly interested in the applications of science as a result of

the Manhattan Project. Second, science needs the funding and sup-

portive activities the federal government is able to give.

The federal government is very committed to science, as indi-

cated by its recent role as finance of most of the research done in

the United States. In 1965, for example, the federal government spent

approximately 15 percent of its administrative budget, or about $15

billion, for research and development (Barber, 1966:5). Eighty percent

of these funds were paid to nongovernment contractors, such as industry

and universities and colleges. Germane to this dissertation is the

distribution of these funds to research in the United States. Nearly

90 percent of the federal government's expenditures for research have

been for applied science. Thus, in 1965, NASA spent about $5 billion

for research (Barber, 1966:5). The government contributes only 10 per-

cent of its research funds for basic science (Barber, 1953; Price, 1954;

Kidd, 1959; Etzioni, 1964; Wiesner, 1965; and, Barber, 1966).

This pattern of funding is reflected in the federal government's

support of university research. From 75 to 80 percent of this nation's

research and development and about 75 percent of all research conducted

in colleges and universities is financed from federal funds, which in

1966 was over $1.9 billion. Less than 10 percent of this amount is spent


Documentation of both circumstances can be found in Thornton
(1939), Price (1954), Kidd (1959), Snow (1961), Dupre and Lakoff (1962),
National Academy of Sciences (1965), and Barber (1966). That these
circumstances are not confined to the United States can be seen in
Seward (1967).











on basic research, which is considered by some to be the very heart of

new knowledge which should be pursued for its own sake (Manuto, 1967:

394).


Federal Funding of Basic Research in American Universities

One serious problem which arises from the federal government's

extensive support of American science and from its distribution and

allocation of research funds is the nature of and conduct of basic

research in American universities. Through their scientists, American

universities perform two important functions for science. They inte-

grate science with the rest of society through interdisciplinary

exposure and they promote the internal development of science. In

promoting its internal development':

American universities provide facilities, taken
in the broadest sense to include social atmosphere
as well as physical equipment, for the research
which underlies the formulation of everchanging,
ever more generalized conceptual schemes. Also,
they continually train new researchers, the train-
ing usually being in close connection with the
current research activities of the mature scientists
who make up the faculty. . Thus the university
becomes a moral community which not only enforces
scientific standards but even incorporates new
members into that moral community. For these
several reasons, then, the indispensable autonomy
of science requires not only a secure place for
the university in American society, but also an
equally secure place for science within the uni-
versity (Barber, 1953:142).


A second major problem, but one which is not part of this study,
was recognized by Barber. "While billions of dollars are going into
the performance of research tasks, virtually no consistent attention
is being given to the pertinent policies of the dispensing departments
and agencies and the long-term implications for American society at large"
(Barber, 1966:5).











That universities have such good equipment and facilities, and

that universities have funds for projects through which future scientists

are trained is due in large measure to the adequacy of federal support

to university research (Dupre and Lakoff, 1962 and Hailsham, 1963).

However, such funding by the federal government carries serious impli-

cations for scientists' research and is of great concern to the manner

in which these scientists define their social responsibility.

It has long been argued that additional funding of basic research

in the universities by the federal government is needed (e.g., Bush,

1945). Criticisms of lack of federal support of basic research (e.g.,

Kaplan, 1965) are cogent. Barber, for example, notes:

One conclusion for an American scientific policy
seems inescapable. Science in American universi-
ties must be maintained, even strengthened. In
part this is a task for the university scientists
themselves. But in part it is also the responsi-
bility of the whole society, that is, through its
agent, the national government (Barber, 1953:148).

Society's agent, the federal government, has responded to the

needs of science in the universities.7 But as noted earlier, the federal

government seems to have done so motivated by self-interest.

The thrust of major components of the federal
government concerned with science today is
predominantly oriented toward specific missions.
This is clearly represented by the nature of
the basic responsibility of the major federal
supporters of research: the Department of
Defense, AEC, NIH, and NASA. . Federal support


For further discussions of the federal government's response
see Folsom (1958:169-175), Shannon (1964:976-978), Weiss (1964:1184-
1218), Brooks (1967:1706-1712), Orlans (1967:665-668), Pake (1967:
517-520), and Pursell (1968:145-164).











to schools is predominantly for research--$1.6
billion in 1963--and this, by and large, is
"project" financing (Shannon, 1964:977).

It seems apparent that the federal government is funding re-

search largely according to its own needs as a political unit. Kaysen

makes a strong argument for the continuance of federal sponsorship of

research through the following four points: (1) it is a major input

to the advance of applied science and technology, from which there

flows continuing growth in this country's military capability and

productive capacity; (2) there is an intimate relation between the

conduct of research and the provision of higher education in science

and technology; (3) experience has shown that an applied research and

development effort benefits from a close relation with basic research

in attempting to solve specific practical problems; and, (4) the corps

of scientists working in basic research represent an important reserve

of capability in applied research that can be drawn upon when national

needs dictate (National Academy of Science, 1965:149-150).

Even though Kaysen presents a strong argument for the support

of basic research, again the emphasis is on "directed" research which

will be of some benefit to the federal government. His argument is

quite unlike that of Kistiakowsky.

If the social climate and support mechanisms are not
such as to encourage the free exploration of new
ideas rapidly and effectively, our technology will
die on the vine because, in the absence of the re-
sults of new, undirected basic research, applied
work tends to become more and more confined in
increasingly expensive refinements and elaborations
of old ideas (National Academy of Sciences, 1965:171).












The pattern of federal sponsorship of research has had serious

implications for the organization of science in this country and, more

importantly, for the autonomy of scientists within the university. The

incorporation of science into the federal government is increasing the

amount of formal organization of scientific research (Barber, 1953:127).

Even where the question of the application of science is not of concern,

pressure exists which encourages scientists to organize among themselves

formally to better deal with other parts of the bureaucracy within

which they find themselves. For example, groups of university

scientists have set up formal organizations to arrange contracts and

to deal with the government bureaucracies which are responsible for

supplying an increasing share of the funds for their research (Barber,

1953:128).

In adapting to the needs of the federal government to guarantee

the continuance of federal support, the university system is coming

under severe criticism.

Besides thoroughly corrupting the traditional
functions of a university, such support has trans-
formed it into an agency of military research,
training, and indoctrination. The creation of
special institutions for research and development
is indicative of the way in which the university
has responded to the needs of the Federal Govern-
ment. Such examples include . the Jet Pro-
pulsion Laboratory associated with the California
Institute of Technology and under contract to the
Army and the National Aeronautics and Space Admin-
istration (Manuto, 1967:394-395).


Bertrand Russell (1968) earlier addressed himself to the need
for such pressure groups.












The ever-increasing problem for the university in accepting

federal funds is that of maintaining its autonomy for the development

of conceptual schemes while taking funds and doing research for the

federal government. The emphasis upon freedom as a unique contribution

of universities has important implications for the attitude of uni-

versities toward federal research funds. If the maintenance of free-

dom is a primary objective of the university, then the university

should pay close attention to the effects of federal research funds

on the freedom of the faculty members and the freedom of the univer-

sity as an institution (Kidd, 1959;33-34).

Kistiakowsky poses the question which is germane to this dis-

cussion: Is freedom of scientific inquiry considered and protected

in the allocation of federal funds? He states that such freedom is

insured in "big science" since such organizations become, in essence,

separate governing bodies. The question is more problematic in
'9
"little science." Barber writes about such autonomy among univer-

sity scientists.

many of them now face the moral dilemma that
they cannot have both outside funds and this freedom.
This is only one aspect, to be sure, of the larger
problem which university science now faces, the
problem of maintaining its autonomy for the develop-
ment of conceptual schemes while taking funds (from
the federal government). . (Barber, 1953:154).

If freedom of inquiry is to be maintained in the university,

both the university and university scientists must resist the pressure


Big science is identified with research institutes while little
science is identified with individual investigators working on smaller
projects.











for accepting sharply delineated projects and contracts for research

which may be useful as training devices. Such contracts are useful

for developmental or applied work, but place a premium on the continua-

tion of existing trends rather than on the exploration of new ones

(Weiss, 1964:1208-1209). Even if an investigator is engaged in basic

research, he can hardly be called free if he has to write in great

detail what he wishes to do, justify fully any alteration of his plans,

write detailed periodic reports of his progress, supply lengthy justi-

fication for his expenditures, plan on the assumption that his funds

may be curtailed at any time, and prove his political conformity

(Kidd, 1959:104).

When one considers the present organization of science in the

United States, the intimate relationship of science and the federal

government, and the impositions placed on freedom of inquiry in the

universities through bureaucratic structures and the resulting

anxieties, the problem of a scientist experiencing ambivalence about

institutionalized normative attitudes becomes apparent.


Federal Funding of Research in the National Aeronautics
and Space Administration

The almost paternal relationship between the federal government

and scientists in this country is best exemplified in the National

Aeronautics and Space Administration, hereafter referred to as NASA.

Federal support of NASA has been praised because of NASA's contribu-

tion to science in general.











The NASA effort is not confined, as so many seem
to assume, to a single objective such as landing
men on the moon. Rather, as was the case with
NACA, it is a broad-based research and development
effort which is designed to meet the needs of any
agency of the Government having work to do in space
(Burke, 1966:351).

Even though NASA has accomplished its stated goals and, in addi-

tion, has accomplished many other unspecified objectives (that is, spin

offs), it is still criticized. For example, Abelson argues that NASA

has affected the balance of scientific research in this country in at

least the following three ways: (1) NASA hires disproportionately

in the younger age categories and in physics as an area of specializa-

tion; (2) when Congress votes to support space research, it votes to

take competent people away from other activities; and (3) the space

program is having damaging effects on technical resources such as the

weapons program (Burke, 1966:354 et passim).

Indicative of the effects of federal sponsorship of NASA and

other federal agencies is the change which is occurring from what

Barber writes:

S. despite the great social contributions made
by Government scientific research, its public
prestige has never been very high, probably be-
cause the prestige of all Government employment
in the United States has not been very high. There
are very few American scientists who consider
Government the most satisfactory type of career.
Even among scientists already employed by the
Government, one survey of attitudes showed only
37% felt that the greatest career satisfaction
could be had in the government. Of university
scientists, only 1% felt this way, and only 5%
of industrial scientists shared their feelings
(Barber, 1953:173).










Today, NASA has introduced a competitive factor which raises

its attractiveness. Both Burke (1966) and Killian (1964) recognize

the necessity of the federal government introducing this competitive

factor.

A top man can get a salary increase amounting to
as much as 25 percent by going to work for Govern-
ment. . The weight of secrecy is removed,
the scientist becomes socially respectable, and he
can enjoy publication . (Burke, 1966:357).

Even so, the problem of freedom of inquiry or autonomy remains.

Since the rules governing federal employment have been designed pri-

marily for administrative purposes rather than scientific ones, more

opportunities are created for promotions and top salaries for men with

seniority and administrative ability than for men with "scientific

ability" (Barber, 1953:171). Government scientists must, on many

occasions, choose between job advancement and scientific opportunity.

NASA has become a respectable arm of the federal government. The

federal government spends more than $5 billion a year on NASA and as

many as 100,000 scientists are involved in NASA projects (Fortune, 1962:

37). But most of these scientists are engineers or technicians who

work in applied areas. Few NASA scientists work in basic research

areas. Having been trained within the "scientific institution," the

problem of ambivalence because of normative contradictions should be

apparent.


Specific Hypotheses to be Tested

This study proposes to compare the attitudes of scientists

in the university and scientists in federal NASA projects. It will











explore the problem of normative contradictions through a variety of

approaches. It will: (1) develop an attitudinal scale for measuring

the scientist's conception of the ideal scientific orientation; (2) con-

struct a scale which will reveal, to some degree, the scientist's per-

formance in relation to that ideal; (3) develop an attitudinal scale

for measuring job satisfaction; and (4) test the interrelations among

these measures and compare university scientists in two job situations

with scientists in federal NASA projects.10

Given the structure of federal support for scientific research,

the principal dwelling place of basic research is in the university

and of applied science in government and industry. But some science

in the university is at least incidentally applied, and a little of

it is explicitly so (e.g., NASA-supported research). In the federal

government, some basic research has to be carried out in order to have

theories to apply to the solution of problems which are set by the

specific goals of the participating organizations. So it is apparent

that some of both kinds of science can be found in both situations.

Barber states the situation as follows:

.pure and applied science always have an
important influence on one another, whether they
are concretely separated or not, in the same or
in different types of social organizations.
Indeed, they are necessarily mutually dependent,
for not merely does pure science provide new
theories for social application, but these appli-
cations in turn furnish the instruments and condi-
tions for the easier advance of pure science (Barber,
1953:100).


1The university scientists are located in two job situations.
One group is composed of those university scientists who have ever had
a NASA grant. The other group is composed of university scientists do-
ing research under other than federal sponsorship.











The assumption is made here that there is an overriding

scientific orientation which is normative regardless of whether the

scientist is in the university or working on NASA projects in the

federal government. The first hypothesis to be tested in this study

is: There is no difference in the ideal scientific orientation of

scientists in the university and scientists in federal NASA projects.

The scientist's ideal scientific orientation will be measured by an

attitudinal scale to be constructed from the scaling of items 1

through 46 on pages 108 through 113 of the interview schedule in

Appendix A. The Guttman scalogram procedure will be used.

Kaplan (1965) and Bernal (1967) state that "good performers"

among scientists possess the characteristic of self-reliance. This is

in accord with Pelz and Andrews' (1966) observation that high per-

forming scientists and engineers are deeply involved in and committed

to their disciplines. From an extension of both of these, it can be

assumed that the highly committed scientist will be a better performer

or more productive than the less committed scientist. The second

hypothesis is: The higher the ideal scientific orientation scores

of the scientists, the more they will adhere to their commitment in

practice. This hypothesis will hold for the scientists in all

three job situations. The items on Professional Information and

Organization Participation (pages 115 through 117) of the interview

schedule in Appendix A will be used to construct a scale of scientific

commitment.











Eiduson (1962) cites three reasons why discrepancies exist be-

tween what scientists say they should be doing and what they are in

fact doing. First, scientists state that they should be doing creative

research, but only 5 percent of a sample taken in 1959 reported doing

such work. Second, there is no spokesman for a scientific group which

speaks with a universal voice on a given policy. The association of

scientists shares the pluralistic, fragmented, and internally competi-

tive attributes of other group participants in American society, whether

political, business, professional, or the like. Third, regarding the

research process itself, some scientists see themselves as zealous re-

searchers, some see themselves as good diagnosticians, some as scholars,

and so on. This means that great stylistic variations in scientific

research do exist and can be specified. Within relatively similar

activities, scientists do differentiate themselves from one another.

Pelz and Andrews (1966) note further that effective scientists are

not necessarily satisfied with their jobs even if they have high status

and good opportunities for professional growth. The third hypothesis

is: There is no relationship between iob satisfaction and the effec-

tiveness of scientists. This hypothesis will hold for the scientists

in all three job situations. The attitudes of the scientist on job

satisfaction will be measured through the construction of an attitudi-

nal scale to be developed from the items on pages 106 and 107 of the

interview schedule in Appendix A. A scientist's effectiveness will

be measured by his score on the commitment scale to be constructed.




22





Several related hypotheses and corollaries will be tested in

the analysis of the data.












CHAPTER II

RESEARCH DESIGN


In January, 1969, the Department of Sociology at the University of

Florida was awarded a grant from the NASA Institutional Grant to the

University. The purpose of the grant was to undertake a study of scien-

tists at the University of Florida who had received similar awards from

the NASA Institutional Grant. The specific objectives of the project

were to: (1) determine and evaluate the reasons why individuals choose

a university and/or scientific career over other careers; (2) determine

the reasons why these scientist-professors decided to engage in NASA

projects; (3) determine the relative importance given by the scientist-

professors to space research activities in comparison with other action

research and/or action programs such as urban renewal; and (4) measure

the commitment to science of the scientist-professors. Fifty-three

NASA grants had been made between 1964 and 1969, involving thirty-four

scientists at the University.

The project investigators in the Department of Sociology also

decided to interview scientists at the University who had never re-

ceived NASA grants and who were in the same departments as those

scientists who received the grants. Further, they decided to inter-

view scientists outside the University who were working for NASA in

the same areas of specialization or disciplines as those scientists

in the University. These decisions yielded three groups of scientists












for comparison: university NASA, university non-NASA, and federal

NASA. This design permits variation in either variable, university or

NASA affiliation, and makes possible the assessment of the independent

effects of either. Such a design is consistent with the testing of

the hypotheses already stated.

Field work, consisting of three stages, was necessary for the

collection of data for these three subsamples. After a pretest of the

interview schedule (Appendix A) on five University of Florida scientists,

the first stage of the field work was started in February 1969. It con-

sisted of interviewing University of Florida scientists. After comple-

tion of the first stage in March 1969, the second stage was started and

completed in May 1969. The second,stage consisted of interviewing

scientists at the Goddard Space Flight Center, Greenbelt, Maryland. The

third stage was started and completed in July 1969, and consisted of

interviewing scientists at the Marshal Space Flight Center, Huntsville,

Alabama.


Sampling Procedures

The first stage of the field work utilized both a total available

universe and an interval probability sample. In the selection of scien-

tists at the University of Florida who had ever received a grant under

the NASA Institutional Grant, the total available universe was sampled.

From 1964 until 1969, thirty-four scientists at the University had re-

ceived such grants. As Table 1 reveals, only twenty-six of these

scientists were still at the University when the interviews were conducted.












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Six of the scientists not available had left the University and four

scientists were on leave of absence. Thus, twenty-six scientists,

representing all of those available, were interviewed (Table 1).

Interval probability sampling (Selltiz, et al., 1965:523) was

employed in the selection of a comparison group of other scientists

in the same academic departments as the NASA scientists. A list was

made identifying the scientists by departments. Using a table of

random digits to select the entry point on the list, scientists were

selected at intervals which limited their number to that of the availa-

ble universe of NASA scientists. Twenty-six scientists were inter-

viewed from these departments (Table 1).

The second stage of the field work consisted of interviewing

the universe of scientists at the Goddard Space Flight Center, Green-

belt, Maryland, who were in the same disciplines as the NASA university

scientists. From a list of scientists provided by NASA officials,

twelve of the fifteen scientists in the universe were interviewed.

Three scientists were on vacation and not available for interviewing

(Table 1).

The third stage of the field work consisted of interviewing

the same universe of scientists at the Marshal Space Flight Center,

Huntsville, Alabama. From a list of twenty-six scientists, twenty-two


The space flight centers at Greenbelt, Maryland, and at Hunts-
ville, Alabama, were chosen to minimize cost and because of the simi-
larity of research and disciplines at these sites to the research and
disciplines in the University of Florida.











were available for interview. Four scientists refused to be interviewed,

leaving eighteen scientists actually interviewed (Table 1).

Although twenty-six scientists were interviewed in each of the

two university subsamples, and twelve and eighteen scientists were

interviewed at Goddard and Marshal Space Flight Centers, respectively,

the final number of interviews used for analysis is smaller because a

few interview schedules from each subsample had to be discarded for in-

completeness. The final number of interviews, as seen in Table 1, totaled

seventy-three; twenty-four in each of the university subsamples, ten

from Goddard Space Flight Center, and fifteen from Marshal Space Flight

Center.


Data Collection

The interview schedule used in this study contained eight separate

sections. They included: (1) Household and Family Composition--data on

persons related to the respondent including their sex, age, marital

status, education, religious affiliation, occupational status; (2) General

Social Background--data on the respondent year by year from birth to

present date, including place of residence, occupation held, educational

status, and family status; (3) Job Satisfaction--attitude statements on

job satisfaction; (4) Ideal Scientific Orientation--a set of forty-five

attitude statements on ideal scientific orientation; (5) Attitude Toward

Religion--a set of nineteen statements on the church and science;

(6) Professional Information--patents and/or patent applications, techni-

cal manuscripts and reports of formal talks, journal articles or research











reports published, number of research grants applied for, all in the

last five years, and number of professional and scholarly subscribed

to; (7) Organizational Information--number of professional organizations

respondent belongs to, type of organization, frequency of attendance at

professional meetings in past three years, number of papers read at pro-

fessional meetings in past three years, and the offices held by the re-

spondent in these organizations; and (8) open-ended questions on

respondent's reasons for taking his present job and his likes and dis-

likes of the job.


Data Processing and Analysis

The interview schedule used in the larger project of which this

study is a part was long and complex, and yielded a vast amount of data.

Only those data specifically related to the hypotheses stated in Chapter I

were analyzed by this writer. The following information was coded for

use in this study: (1) from information on household and family composi-

tion, data on respondent's father's education and occupational status,

and the religious affiliation of the respondent; (2) from the general

social background data, respondent's education and marital status; (3) re-

sponses to the attitudinal statements on job satisfaction and ideal scien-

tific orientation; and (4) responses to the items on professional and

organizational information. The attitude items were scored using the

Cornell Technique for Guttman Scaling. Other data used were trans-

ferred, along with the above, to eighty-column IBM cards.

Absolute frequencies and percentage distributions were computed

for the following information: area of specialization; age; sex;





29





education; father's education; father's social status using occupational

classifications; geographic mobility both before and after first job;

marital status; size of family of orientation and of procreation; and

religious affiliation.

Used in the testing of the hypotheses and their corollaries were:

(1) factor analysis (Fruchter, 1954); (2) Mann-Whitney U (Siegel, 1956),

and (3) Spearman rank order correlation coefficient (Siegel, 1956).











CHAPTER III

CHARACTERISTICS OF THE POPULATION


This chapter is devoted to presentation of a profile of the

characteristics of the scientists in the total sample. Data are pre-

sented for each subsample separately. Where possible, data on the

general population of scientists within the United States are presented

for comparison.


Area of Specialization

As noted earlier, Abelson contends that NASA draws dispropor-

tionately from certain areas of specialization. Table 2 reveals that

astronomy is the only area which is overrepresented in the NASA samples.

When one considers that the national percentage given in Table 2 includes

two other areas of specialization, the heavy concentration of astronomers

in both NASA subsamples becomes even more noticeable. Physics is repre-

sented more heavily in the federal NASA subsample than it constitutes

of the national population of scientists according to the "Summary of

American Science Manpower, 1968" (National Science Foundation, 1970).

Two areas of specialization are underrepresented in these NASA

subsamples. Chemistry represents 52 percent of all scientists on the

national level, while constituting only 25 percent of the university

NASA subsample and only 8 percent of the federal NASA subsample. The

other area of specialization which appears to be underrepresented is

mathematics. While mathematics has 14 percent of scientists on the










TABLE 2

PERCENTAGE DISTRIBUTION OF SCIENTISTS'
AREAS OF SPECIALIZATION, BY JOB SITUATION


Job Situation Nat
National
Area of University University Federal Science
Specialization NASA Non-NASA NASA Foundationa


Astronomy 17 17 8 3b

Physics 21 21 28 18

Chemistry 25 21 8 52

Aerospace b
Engineering 17 17 12 -

Chemical
Engineering 4 4 8 13

Mechanical
Engineering 4 8 8

Metallurgical c
Engineering 0 4 8

Nuclear
Engineering 4 4 4 -

Mathematics 4 0 4 14

Physiology 4 4 0 b

Other 0 0 12 -c



aPercentages computed from the"Summary of American Science Man-
power, 1968" (National Science Foundation, 1970).

bCategory includes Astronomy, Aerospace Engineering, and Physiology.

CCategory includes Chemical Engineering, Mechanical Engineering,
Metallurgical Engineering, Nuclear Engineering, and Other.











national level, it has only 4 percent of the university NASA and federal

NASA subsamples.

Thus, some disproportionate NASA recruiting seems verified among

the areas of specialization included in this research. Physics and

Astronomy are overrepresented in one and both NASA subsamples, respec-

tively. Chemistry and mathematics are underrepresented in both NASA sub-

samples. The other areas of specialization cannot be compared because

of the lack of comparable national data.


Sex

Only 9 percent of the personnel listed in Employment of Scien-

tists and Engineers in the United States (National Science Foundation,

1968) are women. In the subsamples included in this research, women

amount to only 4 percent; one female in the federal NASA subsample

(Table 26, Appendix B). The "N" here is so small that comparisons

are virtually meaningless, but one can note the underrepresentation

of women in all scientific endeavors.


Age

Burke also found that NASA draws disproportionately from among

younger scientists (Burke, 1966). Table 3 reveals that this is true for

the federal NASA subsample. Again, using data from the "Summary of

American Science Manpower, 1968" (National Science Foundation, 1970),

it can be determined that 54 percent of the scientists registered with

the National Science Foundation are under the age of forty--the mean

age being 44.1 years. In the federal NASA subsample, 60 percent are











TABLE 3

NUMBER AND PERCENTAGE DISTRIBUTION OF SCIENTISTS'
AGES, BY JOB SITUATION


Standard
Age Categories Me an Deia
Mean Devia-
20-29 30-39 40-49 50-59 60-65 Total Age tion

University
NASA 44.6 (7.0)

Number 0 9 8 6 1 24

Percent 9 38 33 25 5 100


University
Non-NASA 41.0 (9.5)

Number 1 12 6 3 2 24

Percent 4 50 25 13 8 100


Federal
NASA 38.1 (8.1)

Number 2 13 7 3 0 25

Percent 8 52 28 12 0 100


National
Science
Foundationa 44.1

Percent 21 33 26 14 6 100


aComputed from National Science Foundation (1970).










under forty with a mean age of 38.1 years. However, when one looks at

the university NASA subsample, only 38 percent are under forty with a

mean age of 44.6 years. That the university NASA subsample differs so

much from the federal NASA subsample may be a function of the different

educational requirements for employment in the two job situations. It

may also be that the awarding of university NASA grants demands that the

recipient have completed the doctoral degree.


Education

The available data indicate that, nationally, 99 percent of

scientists have at least a bachelor's degree, 69 percent have at least

a master's degree, and 39 percent have at least a doctoral degree

(Employment of Scientists and Engineers in the United States,

National Science Foundation, 1968). Table 4 indicates that these

samples are more educated when compared to the national figures. In

the university subsamples, 100 percent of university NASA scientists

have completed at least the doctoral degree, and 96 percent of the

university non-NASA subsample have done so. However, university non-

NASA scientists have a higher rate of post-doctoral work. When one

looks at the federal NASA subsample, it appears that it is less edu-

cated than the national scientific population. Only 20 percent of

the federal NASA subsample have completed the doctoral degree and no

one in the subsample has done post-doctoral work.

According to the "Summary of American Science and Manpower,

1968" (National Science Foundation, 1970), 40 percent of the scientists






TABLE 4

NUMBER AND PERCENTAGE DISTRIBUTION OF SCIENTISTS' HIGHEST ACADEMIC DEGREE,
BY JOB SITUATION


Highest Academic Degree

B.A. or B.A.+ or M.A. or M.A.+ or
B.S. B.S.+ M.S. M.S.+ Ph.D. Post Ph.D. Total

University
NASA

Number 0 0 0 0 19 5 24

Percent 0 0 0 0 79 21 100

University
Non-NASA

Number 0 0 0 1 15 8 24

Percent 0 0 0 4 63 33 100

Federal
NASA

Number 8 4 4 4 5 0 25

Percent 32 16 16 16 20 0 100

National
Science
Foundation

Percent 30 30 39 99b
aNational Science Foundation (1968).
One percent of the national total had less than a B.A. or B.S.











registered with the National Science Foundation work in educational

institutions, 10 percent work for the federal government, and 50 percent

elsewhere. Concern here is only with those in educational institutions

and in the federal government. By design, 66 percent of the scientists

in this sample are in an educational institution and 34 percent are in

the federal government. The differing educational demands of the

several institutions imply varied educational compositions of their

staffs. Differences among the subsamples and between samples and the

universe accurately reflect this structural variability.


Father's Education

When one looks at the educational achievement of the fathers

of the respondents (Table 5), one finds great differences among the

subsamples. For those scientists working in the university and having

NASA grants, 51 percent of their fathers have completed at least a

bachelor's degree. Among those scientists working in the university

without NASA support, only 38 percent of their fathers have completed

at least a bachelor's degree. Of those scientists working on federal

NASA projects outside the university, only 24 percent of their fathers

have completed at least a bachelor's degree.

If one looks at the percent of fathers who have completed only

high school then the same pattern emerges as above. Federal NASA


To the best knowledge of this writer, no comparable national data
exist for this category or for the remaining categories in this chapter
with the exception of father's social status. Since the number of scien-
tists has doubled in the period 1960 to 1968 (National Science Foundation,
1970), no national data for periods earlier than 1968 are used.







TABLE 5

NUMBER OF PERCENTAGE DISTRIBUTION OF SCIENTISTS' FATHERS'
EDUCATION USING SIX CATEGORIES, BY JOB SITUATION


Father's Education

Less than High School Less than
High School Complete B.A. B.A. M.A. Ph.D. Total

University
NASA

Number 5 4 3 6 3 3 24

Percent 20 17 12 25 13 13 100

University
Non-NASA

Number 4 7 4 4 1 4 24

Percent 17 28 17 17 4 17 100

Federal
NASA

Number 6 12 1 1 4 1 25

Percent 24 48 4 4 16 4 100












project scientists' fathers are more likely to have had only a high

school education than either university NASA or university non-NASA

scientists. Forty-eight percent of the federal NASA scientists'

fathers have completed only high school, while 28 percent of the

university non-NASA scientists' fathers have done so, and 17 percent

of the university NASA scientists' fathers have done so.

A similar pattern emerges when one looks at the percentage of

fathers who have completed less than a high school education. Federal

NASA scientists' fathers rank first with 24 percent, university NASA

scientists' fathers second with 20 percent, and university non-NASA

scientists' fathers third with 17 percent.

When one looks at the completion of the doctoral degree among

the scientists' fathers, it can be determined that university non-NASA

scientists' fathers rank first with 17 percent, university NASA scien-

tists' fathers second with 13 percent, and federal NASA scientists'

fathers third with 4 percent. As with the scientists' own educational

achievements (Table 4), the university subsamples have higher educa-

tional levels than the federal NASA subsamples among the scientists'

fathers.


Father's Social Status

Barber, in writing about the advantages of a democratic society

to the furtherance of science, states:

Because of the highly developed and highly specialized
abilities which scientists must have, the advance of
science requires that it be a "career open to talent,"
one in which ability occurring in the lower classes may










climb into the professional scientific classes. And
so it has been very largely in the modern world.
Science would soon stagnate if it's functionaries were
mostly mediocrities whose occupational positions had
been ascribed to them on the basis of their family
affiliations (Barber, 1953:70-71).

From available national data (U. S. Bureau of the Census, 1969),

it is obvious that science is a "career open to talent." Assuming that

all scientists are professionals, when one looks at the social status

of their fathers one sees that 52 percent of the fathers nationally are

blue collar workers. Eleven percent are white collar workers and 37 per-

cent are professionals.

A different pattern appears among the scientists included in this

study (Table 6). For the university NASA subsample, 38 percent of the

scientists' fathers are classified as blue collar, none as white collar,

and 62 percent are classified as professional. In the university non-

NASA subsample, 25 percent of the scientists' fathers are classified

as blue collar, 13 percent as white collar, and, again, 62 percent

as professional. The federal NASA subsample shows 32 percent in the

blue collar category, 13 percent in the white collar category, and

the remaining 55 percent are classified as professionals. These

patterns may differ from the national because the distribution of

scientists on the national level includes a much wider range of

places of employment than the restricted subsamples used here. The

higher educational achievement of these subsamples has already been

2When one further divides the three main social status categories
into nine categories (Table 27, Appendix B), one can determine that a
further modification occurs within the subsamples. Even within the
lowest four social status categories which are grouped as blue collar
in Table 6, the fathers of the scientists are disproportionately in
the categories of farmers, operatives and craftsmen.











TABLE 6

NUMBER AND PERCENTAGE DISTRIBUTION OF
SCIENTISTS' FATHERS' SOCIAL STATUS IN
THREE CATEGORIES, BY JOB SITUATION


Social Status Category
Blue White
Collar Collarb Professionalc Total


University
NASA

Number 9 0 15 24

Percent 38 0 62 100

University
Non-NASA

Number 6 3' 15 24

Percent 25 13 62 100

Federal
NASA

Number 8 3 14 25

Percent 32 13 55 100



aBlue Collar includes farm laborer and laborers, service workers,
farmers, operatives, and craftsmen.

white Collar includes salesmen (retail) and clerical workers.

CProfessional includes proprietors, salesmen (other), managers,
and professionals.











noted. It may be that the term "professional" is more accurately

applied to scientists in these subsamples than to those in the national

registry, and that occupational recruitment, when only high echelon

positions are considered, is less "open" than it might otherwise appear.


Geographic Mobility

Blau and Duncan contend that geographic migration is positively

involved in occupational success.

The basic finding . is that the careers of migrants
are in almost all comparisons, clearly superior to those
of nonmigrants. . (Furthermore) . migrants tend
to attain higher occupational levels and to experience
more upward mobility than nonmigrants, with only a few
exceptions (Blau and Duncan, 1967:271-272).

Although comparable data are not available for scientists at the national

level, it will be shown that migration may be one of the factors or

mechanisms through which scientists in this study are channeled to places

where their potential can be realized.

If one looks at the number of moves made before these scientists'

first jobs, a definite pattern emerges (Table 7). Federal NASA scien-

tists have made the fewest moves with 92 percent having made from one

to five moves. University non-NASA scientists were in the middle with

63 percent having made from one to five moves, and university NASA

scientists made the greatest number of moves, since only 45 percent

made from one to five moves. The impact of these percentages may be

modified when it is considered that the number of moves before first

job include, for most of the scientists, moves necessary for the com-

pletion of their academic degrees. That federal scientists have made











TABLE 7

NUMBER AND PERCENTAGE DISTRIBUTION OF
MOVES OF SCIENTISTS BEFORE FIRST JOB, BY JOB SITUATION



Number of Moves


1 5 6 10 11 or more Total


University
NASA

Number 11 13 0 24

Percent 45 55 0 100

University
Non-NASA

Number 15 6 3 24

Percent 63 25 12 100

Federal
NASA

Number 23 2 0 25

Percent 92 8 0 100




the fewest moves may be explained, in part, by their lower overall educa-

tional achievement when compared to the university scientists. Also

included is the effect of the occupational and/or social mobility pattern

of the scientists' parents during his dependency.

If one looks at the number of moves made by scientists after having

taken their first jobs (Table 8), the same pattern emerges. Federal NASA











TABLE 8

NUMBER AND PERCENTAGE DISTRIBUTION OF
MOVES OF SCIENTISTS AFTER FIRST JOB, BY JOB SITUATION


Number of Moves

1 5 6 10 11 or more Total

University
NASA

Number 18 5 1 24

Percent 75 21 4 100

University
Non-NASA

Number 20 3 1 24

Percent 84 12 4 100

Federal
NASA

Number 22 3 0 25

Percent 88 12 0 100




scientists appear to have made the fewest moves, with 88 percent having

made five or fewer. University non-NASA scientists make the next

fewest moves with 84 percent having made five or fewer, and university

NASA scientists make the most moves with 75 percent having made five

moves or fewer. Geographic mobility in this instance may be a function

of age. A review of Table 3 confirms this statement in that federal











NASA scientists make the fewest moves and are the youngest, university

NASA scientists make the most moves and are the oldest, and university

non-NASA scientists comprise the middle category.


Family Size

Blau and Duncan demonstrate that size of family of orientation is

related to father's education and occupation (Blau and Duncan, 1967:333

et passim). Table 9 reveals that federal NASA scientists have more

large families of orientation with 32 percent having six or more members

excluding the respondent. University NASA scientists are next with 17

percent having six or more members, and university non-NASA scientists

have the fewest large families of orientation, with only 8 percent having

six or more members. A review of Table 5 and Table 6 supports Blau and

Duncan's contention that family size is related to education and occu-

pation among the scientists' fathers. For example, federal NASA

scientists have more large families of orientation, their fathers have

the lowest academic achievement, and their fathers also have the low-

est social statuses of the three subsamples. This seems consistent

with Table 4 which reveals that the federal NASA scientists, even

though now classified as professionals, have the lowest academic

achievement.

Since only one respondent in the sample is not married (Table 28,

Appendix B), it might be useful to look at the size of the respondent's

family of procreation (Table 10). Again, Blau and Duncan contend:











TABLE 9

NUMBER AND PERCENTAGE DISTRIBUTION OF SIZE OF
SCIENTISTS' FAMILIES OF ORIENTATION, BY JOB SITUATION


Size of Family Excluding Respondent

1 5 6 or more Total


University
NASA

Number 20 4 24

Percent 83 17 100


University
Non-NASA

Number 22 2 24

Percent 92 8 100


Federal
NASA

Number 17 8 25

Percent 68 32 100





.contracting a marriage and protecting it from
disruption--is an asset, if a comparatively minor one,
for an occupational career (Blau and Duncan, 1967:359).

It can be determined from Table 10 that both university NASA and

federal NASA scientists have fewer large families than did their fathers.












TABLE 10

NUMBER AND PERCENTAGE DISTRIBUTION OF SIZE OF SCIENTISTS'
FAMILIES OF PROCREATION, BY JOB SITUATION


Size

1 5


of Family Excluding Respondent

6 or more Total


University
NASA

Number

Percent


University
Non-NASA

Number

Percent


Federal
NASA

Number

Percent


University non-NASA scientists exhibit more generational continuity. That

is, in both the family of orientation and in the family of procreation,

8 percent of the university non-NASA scientists come from families of six

or more members. It is important to remember that university NASA scien-

tists are the oldest and therefore their family size is probably more

representative of completed fertility. On the other hand, federal NASA











scientists are the youngest and therefore it can be reasonably assumed

that their family size will increase. Whether it will increase enough to

be similar to their families of orientation remains to be seen.


Religious Affiliation

Barber states that little is known about the religious backgrounds

and affiliations of scientists. He notes that Catholics are underrepre-

sented in science, that few figures are available for the Jews, and that

Protestants are overrepresented (Barber, 1953:136-137).

In Table 11, one can see that Catholics are underrepresented in

the sense that, although they comprise over 20 percent of the national

population (Barber, 1953), they are found in only 8 percent of the uni-

versity NASA scientists and in 4 percent of the university non-NASA

scientists. They are best represented in federal NASA scientists, with

16 percent. No Jews are found among the university NASA scientists.

They are found among the university non-NASA scientists and among the

federal NASA scientists--14 percent and 4 percent, respectively. Those

denominations classified as Protestant comprise 84 percent of the uni-

versity NASA subsample, 74 percent of the university non-NASA subsample,

and 76 percent of the federal NASA subsample.


Summary

In the presentation of the demographic data it was found that

there are similarities and differences among the samples used in this

research and the national scientific population. The following represent

briefly the observed similarities and differences.












TABLE II

NUMBER AND PERCENTAGE DISTRIBUTION OF SCIENTISTS'
RELIGIOUS AFFILIATIONS, BY JOB SITUATION


Religious Affiliation

Protestant Catholic Jewish None Total


University
NASA

Number 20 2 0 2 24

Percent 84 8 0 8 100

University
Non-NASA

Number 18 1 3 2 24

Percent 74 4 14 8 100

Federal
NASA

Number 19 4 I 1 25

Percent 76 16 4 4 100


aIncludes Baptist, Christian, Episcopal, Lutheran, Methodist,
Mormon, Presbyterian, and Protestant.


First, it appears Abelson's contention that NASA draws dispor-

portionately from certain areas of specialization is correct. When com-

pared to the national group, physics is overrepresented in the federal

NASA subsample and astronomy is overrepresented in both NASA subsamples.

On the other hand, chemistry and mathematics are underrepresented.











Second, Burke's observation that NASA draws disproportionately

from among younger scientists receives some support. The federal NASA

subsample has higher percentages of its population under forty years of

age than does the national group. Although the university NASA sub-

sample is substantially older than the federal NASA subsample, it was

suggested that their affiliation with NASA through grants might be a

function of the system used by NASA in awarding grants, and the occu-

pational requirement of the university in demanding that university

scientists have doctoral degrees.

Third, as is true of the national group, women are underrepre-

sented in these samples of scientists. Although women comprise 9 per-

cent of the national group, they amount to only 4 percent of the federal

NASA subsample in this research.

Fourth, in relation to education, one sees that the university

subsamples are more highly educated than the national group. The

federal NASA subsample appears as less educated. The reason for such

differences was suggested as being the different educational demands

of the various institutions in which the scientists are located.

Fifth, the social statuses of the fathers of these scientists

differed from those of the national group. The samples used in this

study have higher percentages of fathers from the professional category

than does the national group. It was suggested that perhaps the term

"professional" is more accurately applied to scientists in this study

than to those in the national group.












Additional descriptive demographic data were presented for which

comparisons could not be made with national data. The following are

some of the characteristics of these samples of scientists.

First, definite patterns emerged on the education of the scientists'

fathers. University NASA scientists' fathers had the highest rate of

completion of the bachelor's degree, followed by university non-NASA

scientists and then by federal NASA scientists. Federal NASA scientists'

fathers were shown to be most likely to have completed only a high school

education. University non-NASA scientists' fathers had the highest rate

of completion of post-doctoral work, followed by university NASA scien-

tists' fathers.

Second, when the scientists' families of orientation and procrea-

tion were considered by size, it was determined that the federal NASA

subsample had more large families, followed by university NASA scientists.

Both of these subsamples presently have more small families than among

those from which they came. The university non-NASA subsample showed

the greatest generational continuity in family size.

Third, concerning religious affiliation, 84 percent of the uni-

versity NASA subsample is Protestant. Protestants are 74 percent of

the university non-NASA subsample and 76 percent of the federal NASA

subsample. Catholics are found to be underrepresented in all three

subsamples. Jews are best represented among the university non-NASA

subsample and by the federal NASA subsample.

The overall picture presented by the presentation of the demo-

graphic data has some utility for a profile of the scientists included





51





in this study. Conclusions about differences between these samples and

the national group should be made cautiously because of the different

sources of data, different methods of data collection, and different

times of data collection.












CHAPTER IV

CONSTRUCTION OF THE SCALES


In an attempt to get at the problem of normative contradictions

as presented in Chapter 1, three scales have been developed and will be

used in testing the hypotheses. A scale measuring the scientists' ideal

scientific orientation is presented. Next, a scale measuring commitment

and/or performance regarding the scientific ideal is presented. Last,

a scale measuring the scientists' job satisfaction is presented. The

interrelations among these scales will be tested in the next chapter.

In construction of the scales, the technique of Guttman cumula-

tive scaling is used. The Guttman scaling technique allows one to

rank a respondent as higher or lower than another respondent according

to the pattern of responses to a set of statements. In order for an

area to be considered scalable, it is necessary that:

S. the responses to a set of items in that area
arrange themselves in certain specified ways. In
particular, it must be possible to order the items
such that, ideally, persons who answer a given
question favorably all have higher ranks than per-
sons who answer the same questions unfavorably.
From a respondent's rank or scale score we know
exactly which items he endorsed. Thus we can say
that the response to any item provides a definition
of the respondent's attitude (Stouffer, et al.,
1950:5).

The respondent's scale score is thus an indication of his rank order

position with respect to the underlying variable or scalable area.


For a discussion of some of the pitfalls in the use of this
technique, see Festinger (1947:149-161) and Schooler (1968:296-303).











Unidimensionality is achieved when a single scale score is derived which

is the measure of one factor only.

If a single, quantitative score is to represent
without ambiguity, the behavior of an individual
on the set of items in the interview schedule, then
it must be possible, knowing each respondent's score,
to know his behavior on each and every statement in
the set. Guttman calls this the principle of repro-
ducibility (Remmers, 1954:99).

It should be noted that reproducibility by itself is not a suffic-

ient criterion for scalability. One must also consider the range of

marginal distributions, pattern of errors, number of items in the scale,

and the number of response categories in each item (Stouffer, et al.,

1950:78).

The scales in this study are constructed using the Cornell Tech-

nique (Edwards, 1957:178-184) for meeting the five criteria for the con-

struction of a Guttman scale: (1) a coefficient of reproducibility of

at least .90 percent to approximate a perfect scale (Stouffer, et al.,

1950; Riley, 1963); (2) an acceptable range of marginal distribution

such that each item has at least 20 percent and no more than 80 percent

favorable responses (Riley, 1963); (3) a pattern of errors in which no

one scale type has non-scale types whose pattern of errors exceed 5 per-

cent of the total number of respondents (Stouffer, et al., 1950; Riley,

1963; Edwards, 1957); (4) number of items in the scale being from five

to ten (Stouffer, et al., 1950); and (5) an acceptable number of re-

sponses to each item to insure scalability (Stouffer, et al., 1950).











Ideal Scientific Orientation Scale

Sixty-five attitudinal statements were administered to the re-

spondents who were asked to respond with "Strongly Agree," "Agree,"

"Undecided," "Disagree," and "Strongly Disagree." Forty-six of those

items pertain to the scientists' ideal scientific orientation, thirty-

nine of which meet the criterion of the 80/20 split (Riley, 1963).


Rationale for the Items in the Set

Each item, or statement, in the set can be placed in one of two

subuniverses. Items assigned to the first subuniverse are intended to

discriminate among respondents' feelings about the ideal scientific

orientation in applied research. Items assigned to the second subuni-

verse are intended to discriminate'among respondents' feelings about

the ideal scientific orientation in pure research. Table 29, Appendix

B, presents the thirty-nine statements, the subuniverse to which each

is assigned in the construction of the scale, and the percentage of

favorable responses to each item when the Cornell Technique is employed.


Test for Scalability

Since it was not known whether the respondents' ideal scientific

orientations matched the applied-pure dichotomy, the original subuni-

verses were subjected to a factor analysis (Fruchter, 1954). Only thirty

of the thirty-nine items factored with loadings of .40 or higher.


For a discussion of the use of subuniverses and factor analysis
in the construction of Guttman scales, see Stouffer, et al.(1950),
Loevinger (1948:507-527), and Perrucci and Gerstl (1969).











Although factor analysis starts from a different premise than does

Guttman scaling, it was employed in the construction of this scale

in an effort to isolate and validate the respondents' feelings.

In factor analyzing the items, it was discovered that there

apparently are three factors, or subuniverses, and not two as originally

conceived (Table 12). The factors are given descriptive names which

correspond to the original subuniverses, with a residual category. The

three factors are labeled "Applied Research Orientation," "Basic Re-

search Orientation," and "Residual Research Orientation." The latter

is labeled "Residual" because no other sensible rubric suggested it-

self. The factors are then ranked by the strength of their mean

loadings (Table 13).

Each of these factors was then subjected to Guttman Scalogram

Analysis. All ten items which comprise the final Ideal Scientific

Orientation Scale (Table 14) come from the second subuniverse or fac-

tor, "Basic Research Orientation" (Table 12). Even though "Applied

Research Orientation" has a higher mean factor loading than the

"Basic Research Orientation," only the latter is scalable according

to the five criteria for constructing a Guttman scale.

The following criteria are met in the construction of the Ideal

Scientific Orientation Scale: (1) the coefficient of reproducibility

is .933; (2) each item has at least 20 percent and no more than 80 per-

cent favorable responses; (3) no pattern of errors as represented by

non-scale types comprise more than 5 percent of the total number of









TABLE 12

FACTOR MATRIX OF ATTITUDES ON IDEAL SCIENTIFIC ORIENTATIONa


Factors

Item I I1 III
No. Item Applied Basic Residual

2 This job is all right when no others
are available 0.55251
4 No matter what happens this job always
comes first 0.44869
5 This used to be a good job, but not
anymore 0.56803
6 Scientist in university not as productive as
scientist in industry because of lack of
pressure on immediate goals 0.70712
13 The best way to evaluate a man is by his
success in his occupation 0.52761
15 Work is necessary because it is the most
important thing in molding character 0.48665
19 Smith should take the position 0.63791
20 A respected researcher but poor teacher
should get promotion, not good teacher
with no research 0.60647
22 I would rather be known and respected
throughout institution where I work than
in my field at various institutions 0.53371
24 Space program should be continued to
guarantee world leadership in scientific
and technical knowledge 0.50020
26 Refusal to conquer space would mean a
period of Dark Ages for mankind 0.58132








TABLE 12 (continued)

Factors
Item II I l
No. Item Applied Basic Residual

29 Scientist should investigate something
which will alleviate problems of mankind
not just of a purely theoretical nature 0.70270
30 Many of our present urban problems would
have been avoided if scientist hadn't
ignored them initially 0.44911
37 Format is more important in getting
article published than content 0.54402

36 Subjective evaluation of scientists'
proposals hinders research 0.51279
7 Government emphasis on applied science
hinders science in this country 0.58711
11 Scientist better off with private funds
because of freedom 0.50387
17 Family should back scientist regardless 0.60693
18 Scientist does not take positions which
will interfere with research 0.59311
21 Scientist should do research even if not
interested if it offers other rewards 0.52788
32 Do research regardless of social con-
sequences 0.51893
35 Agencies to seek scientists to develop
their own area 0.67817
38 Teaching in university hinders research 0.46368
39 Scientist better off in university because
prestige 0.59236










TABLE 12 (continued)

Factors

Item I I I III
No. Item Applied Basic Residual

1 Working allows one to put his own ideas
into operation 0.43140
9 Advantage of teaching in university is that
it stimulates research 0.61348
25 Country would be better off if space money
were spent on societal programs 0.58404
28 Scientist should be blamed for eventual
destruction of the world because they
provided the means to do so 0.43405
31 Sometimes it is necessary for scientist
to engage in research whose results
will not be made public 0.46320
33 Present system of applying for and
receiving research grants hinders science 0.44481



aComplete factor matrix--Appendix B.












TABLE 13

RANK-ORDER OF FACTORSBY MEAN LOADINGS OF
ATTITUDES, ON IDEAL SCIENTIFIC ORIENTATION


Factor Label Mean Loadinga

I Applied Research Orientation .64049

II Basic Research Orientation .55848

III Residual Research Orientation .49516



aSee Table 30, Appendix B, for item loadings for each factor.


respondents (Table 15); (4) the final number of items in the scale is

ten; and (5) the items are dichtdmized according to the Cornell Tech-

nique and every scale type is represented by at least 5 percent of the

total number of respondents (Table 31, Appendix B).


Commitment Scale

Ten of the fourteen items on Professional Information and Orga-

nizational Participation were used in the construction of the Commit-

ment Scale. The items were dichotomized using the Cornell Technique

(Table 32, Appendix B).


Rationale for the Items Used

The items selected are indicative of the scientist's commitment

to his ideal scientific orientation. They are based on at least three

assumptions. First, the items on patent and patent applications in the










TABLE 14

COMPARISON BETWEEN THE GUTTMAN SCALE SCORES AND FACTOR MATRIX
RANKING OF FINAL TEN ITEMS ON IDEAL SCIENTIFIC ORIENTATION


Guttman Factor
Scale Item Rank
Score
1 Scientists should take advantage of opportunities which II
represent "milestones" for them, regardless of the social
consequences of that research.
2 The ideal situation for advancement of science is for II
agencies to seek scientists to develop their own areas
of study, regardless of the nature of their study.
3 Dr. Smith is a prominent scientist who is dedicated to II
his work. His dedication has precipitated many family
conflicts and his family must make a decision regarding
their relation to their father. The family should back
him regardless of the difficulties involved.
4 The scientist is better off working in the university II
than with government because he gets more in terms of
prestige.

5 Teaching obligations hinder one's research in the II
university setting.
6 Professor Pierce has an opportunity to work on a research II
project which is considered the "chance of a lifetime."
Although Professor Pierce has no real interest in the
goals of the project he should consider taking the position
because of the opportunities to do work with renowned
scientists and to publish extensively.

7 A good scientist should not take any position which will II
interfere with his research.
8 Although government funds for research are greater than II
funds from private foundations, the scientist is better
off with funds from the private foundations, because of
the freedom to do the research he desires.
9 Development of science in this country is being hindered II
because of the emphasis of government funding on applied
research.
10 Scientific development in this country is hindered because 1I
the scientist's proposal is subject to the scrutiny of his
peers. This subjects him to the subjective evaluation of
his colleagues.







TABLE 15


IDEAL SCIENTIFIC ORIENTATION SCALOGRAM


Scale Type of
Subject


Most Oriented


cno ;oa
0 (D (D
D 0 -I

1 n a

3 ( "

a,


> 0 /ln
(D < -
>01
-0n
0<-*
a/ 3
or-f
-o -.
or
V,
?^


1 1 1

1 1 1


Scale Pattern
1= Favorable Response
2= Unfavorable Response


w 10


on
- 0r-t 0
3 fi

- 5 ro

a -.
-1 -h r

/i -h
1-1


(D (D
0D 0. n
(j (n -
n n


I: tQ


3

VI -h (D -

0. 0 0
.-t 3


m (D -0 o
00 -00n

a -rta n
0 0 --.
o -3 0 -4
ni a
Jn-a ,
-' 0-


c (D
(. M-
a ar


-> mn
-(D 3

0-.0
V,
a -
(B 0
101
000t/


I I


-< c
3 c cr
I--'-*
DI r


00 <
-Ia n


Distribution of
the Respondents





Non- Perfect
Scale Scale Total


I 1 1 1 1 1 7a 5 12

S 1 1 1 1 1 0 4a 3 7

1 1 1 1 1 0 0 3 3 6

1 1 1 0 0 0 4a I 5

1 1 1 0 0 0 0 4a 4 8

1 1 0 0 0 0 0 2 3 5

1 0 0 0 0 0 0 2 3 5

0 0 0 0 0 0 0 3 3 6

0 0 0 0 0 0 0 2 6


Least Oriented


Total Subjects


1 0 0 0 0 0 0 0 0 0 4a 1 5

0 0 0 0 0 0 0 0 0 0 _7 1 8

44 29 73


aRepresent different response patterns within scale type. Does not exceed 5% as a non-scale type.


m I I I I I I


' ' '











last five years and the number of research grants applied for in the

last five years serve as one measure of the scientist's involvement

in the research process (Pelz and Andrews, 1966). Second, the items

on the number of technical papers accepted by professional journals

and number of journals subscribed to and read are all measures of the

extent to which the scientist shares and receives ideas with the

"scientific community" (Barber, 1953). Lastly, the items on the num-

ber of professional organizations belonged to, attendance at their

meetings, and the number of papers read at those meetings, give one a

measure of the scientist's professional identification (Kaplan, 1965).

Table 32, Appendix B, gives the distribution of favorable responses

to those items.


Test for Scalability

Using the Guttman Technique of Scalogram Analysis, the final

scale of seven items was constructed (Table 16). The scale meets the

following criteria: (1) a coefficient of reproducibility of .926;

(2) each item has at least 20 percent and no more than 80 percent

favorable responses; (3) no pattern of errors as represented by non-

scale types exceed more than 5 percent of the total number of respon-

dents (Table 17); (4) the final number of items, seven, is between

Guttman's recommendation of five to ten; and (5) the items are dicho-

tomized according to the Cornell Technique and every scale type has

at least 5 percent of the total number of respondents within it (Table

33, Appendix B). The final scalogram for the Commitment Scale is pre-

sented in Table 17.











TABLE 16

FINAL SEVEN ITEMS IN THE COMMITMENT SCALE


Favorable Responses
Item
No. Item Percent Splita

I Number of professional organizations the
respondent belongs to .79 1-2

2 Frequency of attendance at professional
meetings ..76 2-3

3 Number of scholarly and professional
journals subscribed to .71 2-3

4 Number of papers read at professional
meetings .64 0-1

5 Number of published journal articles
or research reports .54 0-1

6 Number of research grants applied for .48 0-1

7 Number of professional journals read
regularly .36 5-6


amusing the Cornell Technique, the items are coded I and 2. One
indicates favorable or high response while 2 represents unfavorable or
low response. The splits are made along real numbers; that is, for
example, in the first item the split is--l organization is unfavorable,
2 or more organizations favorable.


Job Satisfaction Scale

Twenty-two items on job satisfaction were administered to.the re-

spondents. Again, they were asked to respond with "Strongly Agree,"

"Agree," "Undecided," "Disagree," and "Strongly Disagree." All twenty-

two items meet the 80/20 dichotomization requirement.









TABLE 17

COMMITMENT SCALOGRAM


Scale Pattern
I= Favorable Response and Commitment
2= Unfavorable Response and Commitment


Scale Type of
Subject






Most Committed


Lest Committed

Total Subjects


N OJ -0 Z
0 --i c
t 0 3
- 0 -h 0
0 D (D
0-lam

--.


-- a
(D
o 0 C,


1 1
1 1










1 0

0 0


SoC 0

Co -

( 0C 0 <


-ro -a
D 0 -0
-3 (a D

3 -+
0 (D
ID,
0L


73 ;U > C- -a
S(D- 0 C
o0 -1 -
ma- -0
..
0


) 0 -,
S0) 0
< 0on
CSC 0

co(o
01 I


Distribution of
the Respondents


Non- Perfect
Srale Sral


T tal 1


S1 1 1 1 18 19

1 0 8a 4 12

1 0 0 4a 4 8

1 1 0 0 0 3 4 7

1 0 0 0 0 5a 1 6

0 0 0 0 0 3 4 7


1 5


0 0 0 0 0


2 9


34 39 73


Represent different response patterns within scale type. Does not exceed 5% as a non-scale type.


Scale Scale Tota










Rationale for the Items in the Set

Pelz and Andrews (1966) conducted the most recent and, in this

writer's opinion, the most elaborate study of attitudes and measures

of job satisfaction among scientists in different organizational

settings in the United States. The items used in the construction of

the Job Satisfaction Scale were drawn from a review of this extensive

research. The distribution of favorable responses, using the Cornell

Technique, is presented in Table 34, Appendix B.


Test for Scalability

Ten items are included in the final scale on Job Satisfaction

(Table 18) which meet the following criteria: (1) a coefficient of

reproducibility of .915; (2) eachitem has at least 20 percent and no

more than 80 percent favorable responses; (3) no pattern of errors

as represented by non-scale types exceeds more than 5 percent of the

total number of respondents (Table 19); (4) a final scale of ten items;

and (5) dichotomization of items according to the Cornell Technique

with every scale type representing at least 5 percent of the total

number of respondents (Table 35, Appendix B). The final scalogram

for the Job Satisfaction scale is presented in Table 19.


Summary

In this chapter, three scales were constructed to be used in the

testing of the hypotheses for this study. The scales on Ideal Scien-

tific Orientation, Commitment, and Job Satisfaction all met the five











TABLE 18

FINAL TEN ITEMS FOR THE JOB SATISFACTION SCALE


Favorable Responses

Item
No. Item Percent Splita

1 Opportunity for spontaneous research .75 2-3

2 Adequacy of salaries .71 2-3

3 Freedom of communication and appeal .69 2-3

4 Adequacy of laboratories .60 2-3

5 Fairness of process for giving in-
creases in salary .58 2-3

6 Adequacy of faculty (employee) office
space .45 2-3

7 Good faculty-student (supervisor-
employee) relations .39 2-3

8 Fundamental scholarly achievement .30 2-3

9 Scholarly writing .22 2-3

10 Faculty voice in administrative
selections .21 2-3


The Cornell Technique is used in the
in this scale. 1= Strongly Agree, 2= Agree,
and 5= Strongly Disagree.


dichotomization of the items
3= Undecided, 4= Disagree,


requirements of Guttman scaling: (1) coefficient of reproducibility--

Ideal Scientific Orientation, .933, Commitment, .926, and Job Satisfac-

tion, .915; (2) each item in each scale had at least 20 percent and no

more than 80 percent favorable responses; (3) each scale had no pattern







TABLE 19


JOB SATISFACTION SCALOGRAM


Scale Type of
Subject










Most Satisfied


mc -0
m :3 0
n 0 a


0-o
o -
In
-h


Scale Pattern
1= Favorable Response and Satisfaction
2= Unfavorable Response and Satisfaction


C.3 9 (
3
> C CL
0 0



:b3
7


-- 1 -o -,

Lo 0 m


I =1
0 3 0 :


vl
In


;0 < UW
(D -- 0

- 3 0
30 0
S-0co
o 0r

(D (D I
a, I


o o
a- 3-
-*0 0
, 0 03
< 3

(Dlrt
a -
lb -


0-<- =
man
-- .
Da,(


I >
a
3


Distribution of
the Respondents


Non- Perfect
Scale Scale


1 1 1 1 1 .1 1 1 1 1 2


1 1 1 1 1 1


Total


9


1 1 0 4a 2


1 1 1 1 1 1 1 1 0 0 5a 2

1 1 1 1 1 1 1 0 0 0 4a 1


1 1 1 1


0 0 0


1 1 1 1 1 0 0 0 0 0 6a 1


1 1 1 1 0 0 0 0 0 0

1 1 1 0 0 0 0 0 0 0


4a 3

6a 1


Least Satisfied


Total Subiects


1 1 0 0 0 0 0 0 0 0 2

1 0 0 0 0 0 0 0 0 0 6a


47 26


aRepresent different response patterns within scale type. Does not exceed 5% as a non-scale type.


~ -----











of errors as represented by non-scale types exceeding more than 5 per-

cent of the total number of respondents; (4) final number of items were

between five and ten, ten for the Ideal Scientific Orientation Scale,

seven for the Commitment Scale, and ten for the Job Satisfaction Scale;

and (5) all items in each scale were dichotomized according to the

Cornell Technique and every scale type of each scale had at least 5 per-

cent of the total number of respondents for each scale within it.

Since each scale meets the criteria set forth in the literature

on Guttman scaling, it is assumed that they are valid instruments to

be used in the testing of the hypotheses. It remains to be seen what

limitations these scales have for the data in this study.











CHAPTER V

ATTITUDINAL PROFILES OF SCIENTISTS

To present attitudinal profiles of the scientists in the various

subsamples, the following tests of associations and tests of differences

are made on the Guttman scale scores. In testing the associations among

Ideal Scientific Orientation scores, Job Satisfaction scores, and Commit-

ment Scale scores, the Spearman rank order correlation coefficient is

used (Siegel, 1956:202-213). In testing the differences between each

pair of subsamples in Guttman scale scores, the Mann-Whitney U is used

(Siegel, 1956:116-127).2


Tests of Major Hypotheses

Using the .05 level of significance for rejecting or not rejecting

the null hypotheses, the following major hypotheses are tested. The

tests of the hypotheses will be given in the same order in which they

appeared in the first chapter.


Spearman rank order correlation coefficient is a "measure of
association which requires that both variables be measured on at least
an ordinal scale so that the objects or individuals under study may
be ranked in two order series"(Siegel, 1956:202). The three sets of
scale scores are ranked in two series when two are compared separately.
Because of the large proportion of observations tied for certain ranks,
a correction factor was incorporated in the test to prevent inflation
of rho.

2The Mann-Whitney U test is used "when at least ordinal measure-
ment has been achieved . to test whether two independent groups
have been drawn from the same population" (Siegel, 1956:116).











FIRST MAJOR HYPOTHESIS: There is no difference in the ideal

scientific orientation of scientists in the university and scientists

in federal NASA projects.

This hypothesis cannot be rejected at the .05 level of signifi-

cance using the Mann-Whitney U test (Table 20). It would seem there is

an overriding scientific orientation which is normative for the scien-

tist whether he is working in the university or in a federal NASA

project. Whether one looks at the university subsamples or the federal

NASA subsample, or any combination of the three, it appears there are

no differences among the subsamples in the scientific orientation of

scientists. It might be concluded that science, as an institution, has

been and is normative for the scientists in this study.

TABLE 20
TESTS FOR DIFFERENCES ON IDEAL SCIENTIFIC ORIENTATION
SCALE SCORES, NASA AND UNIVERSITY SCIENTISTSa

Job
Situations Z Scores Probability Null Hypothesis
Federal NASA
versus 0.1517 p< .8808 Not Rejected
University

University NASA
versus -1.0454 p< .2937 Not Rejected
University Non-NASA

University NASA
versus -0.5925 p< .5485 Not Rejected
Federal NASA

University Non-NASA
versus 0.3313 p< .7414 Not Rejected
Federal NASA

aMann-Whitney U used.
Two-tailed tests.











SECOND MAJOR HYPOTHESIS: The higher the ideal scientific orien-

tation scoresof the scientists, the more they will adhere to their commit-

ment in practice.

It appears that this hypothesis must be rejected. There is no

relationship between ideal scientific orientation and commitment in any

of the samples included in this study. The lack of association holds

for the total sample and for the subsamples when considered separately

(Table 21). The implications of the lack of association between ideal

scientific orientation and commitment will be discussed in another part

of this chapter.


TABLE 21

TESTS OF ASSOCIATION BETWEEN IDEAL SCIENTIFIC ORIENTATION
AND COMMITMENT SCALE SCORES, TOTAL SAMPLE AND SELECTED SUBSAMPLES


Job b
Situations Spearman's rho Significant

University NASA, University Non-NASA,
Federal NASA -0.095 No

University NASA, University Non-NASA -0.152 No

University NASA 0.243 No

University Non-NASA -0.191 No

Federal NASA -0.025 No

aSpearman's rank order correlation coefficient used.
One-tailed tests.


THIRD MAJOR HYPOTHESIS: There is no relationship between job

satisfaction and the effectiveness of scientists.











Job satisfaction attitudes and Commitment Scale scores appear

to be related in the combined subsamples (Table 22). However, when job

situation is controlled (Table 22 and Figure I), the relationship dis-

appears and the null hypothesis is accepted. This lack of association

between job satisfaction and effectiveness holds for the total sample

and each subsample when considered separately. Apparently, Pelz and

Andrews' observation that effective scientists are not necessarily

satisfied with their jobs is supported.


TABLE 22

TESTS OF ASSOCIATION BETWEEN JOB SATISFACTION AND COMMITMENT
SCALE SCORES, TOTAL SAMPLE AND SELECTED SUBSAMPLESa


Job b
Situations Spearman's rho Significant

University NASA, University Non-NASA,
Federal NASA 0.269 .05

University NASA, University Non-NASA 0.163 No

University NASA 0.319 No

University Non-NASA -0.019 No

Federal NASA 0.274 No


aSpearman's rank order correlation coefficient used.
Two-tailed tests.


Other Hypotheses Tested

Construction of the Ideal Scientific Orientation Scale, Commit-

ment Scale, and Job Satisfaction Scale suggested other hypotheses to

this writer which are not presented in Chapter I of this study. The




73








AA 0 00


10- AA A A 0


9- A A 0 0 0


8- AO A 0 0 00

o
U
S 7- A 0 AO O O


AA A AO AA
0





.0
5-- LA AL A o



0
-- AA 00 A AO


2-- A LA A





0 1I I I t

1 2 3 4 5 6 7 8
Commitment Scale Scores

A= University Scientists O= Federal NASA Scientists


Figure I. Test of Relationship Between Job Satisfaction and Commit-
ment Scale Scores When Scientist's Job Situation Is
Controlled.











following hypotheses concerning job satisfaction, commitment, and the

relationship between ideal scientific orientation and job satisfaction

are presented in an attempt to give a more adequate profile of the

scientists in this study.


Job Satisfaction

Barber states that research has shown that scientists feel that

little career satisfaction is obtained by working for the federal

government. He shows that, proportionately, more university scientists

feel career satisfaction is possible in the university than federal

scientists feel is possible in the federal government (Barber, 1953:

173). It was suggested in Chapter I that the competitive salaries

which NASA offers may have eliminated these differences in attitudes

on job satisfaction between scientists working in the university and

scientists working for the federal government. With the sample of

university scientists and federal NASA scientists in this study, the

following null hypothesis is tested.

FOURTH HYPOTHESIS: There is no difference in attitudes on job

satisfaction between scientists in the university and scientists in

federal NASA projects.

Using the Mann-Whitney U, the hypothesis is rejected at the .05

level of significance (Table 23). Apparently there are differences

in the attitudes on job satisfaction among the subsamples in this

study. When one looks at Table 23, one sees that whenever either

university subsample, or the two combined, is compared with the











TABLE 23

TESTS FOR DIFFERENCES ON JOB SATISFACTION SCALE SCORES,
NASA AND UNIVERSITY SCIENTISTSa


Job b
Situations Z Scores Probability Null Hypothesis

Federal NASA
versus -2.5174 p< .0118 Rejected
University

University NASA
versus 0.8730 p< .3844 Not Rejected
University Non-NASA

University NASA
versus 2.2130 p< .0272 Rejected
Federal NASA

University Non-NASA
versus 2.1207 p< .0340 Rejected
Federal NASA


aMann-Whitney U used.
Two-tailed tests.

federal NASA subsample, some differences in job attitudes appear. When

one compares the university NASA subsample with the university non-NASA

subsample, there is apparently no difference in their attitudes on job

satisfaction. The implication of these tests is that the federal

government's pay incentive apparently has not eliminated the differences

in attitudes as noted.


Commitment Scale

It has been noted that science has become rather bureaucratized

in the United States (Barber, 1953; Kidd, 1959; and Burke, 1966). As











science in the United States becomes more and more dependent on the

federal government for support, the formal channels of communication

and, for example, grant applications become more structured and

specified. However, it is the opinion of this writer that the

bureaucratization of science in the university has had fewer adverse

effects on the productivity of the scientists in the university than

bureaucratization of science in federal agencies has had on federal

NASA scientists. This may simply be a function of the university

being less perfectly bureaucratized. Because the items in the Commit-

ment Scale give one a measure of the scientists' productivity, it was

decided to test for differences between the subsamples on commitment.

FIFTH HYPOTHESIS: There is no difference in the commitment

of scientists in the university and of scientists in federal NASA

projects.

The hypothesis is rejected at the .05 level of significance

(Table 24). It appears that scientists in the university differ in

their commitment from scientists in federal NASA projects. Further-

more, when one compares the subsamples with one another, not only

does the relationship hold for each university subsample when compared

with the federal NASA subsample, but within the university differences

in commitment exist. Inspection of the data reveals that scientists

working in the university with NASA grants are the most productive

on the items used in the Commitment Scale and therefore, by implica-

tion, are the most productive of the three subsamples used in this

study.












TABLE 24

TESTS FOR DIFFERENCES ON COMMITMENT SCALE SCORES,
NASA AND UNIVERSITY SCIENTISTSa


Job
Situations Z Scores Probability Null Hypothesisb

Federal NASA
versus -5.7650 p< .0000 Rejected
University

University NASA
versus 2.4279 p< .0150 Rejected
University Non-NASA

University NASA
versus 5.7195 p< .0000 Rejected
Federal NASA

University Non-NASA
versus 4.2016 p< .0000 Rejected
Federal NASA


aMann-Whitney U used.
bTwo-tailed tests.


Ideal Scientific Orientation and Job Satisfaction

Job conditions may place constraint on performance, encouraging

or inhibiting behavior which fulfills the scientists' values. Such

circumstances might be frustrating or pleasing. Since it has been

demonstrated that there may be an overriding scientific orientation

which is normative for all scientists and that job performance (com-

mitment) varies, the relationship of orientation to job satisfaction

is tested.












SIXTH HYPOTHESIS: There is no relationship between scientists'

ideal scientific orientations and their job satisfaction.

The null hypothesis cannot be rejected at the .05 level of sig-

nificance (Table 25). Whether one looks at the total sample or the

subsamples separately, the lack of association holds. It appears that

ideal scientific orientation, which has been shown to be normative for

all scientists, is not contingent upon job satisfaction among the

scientists in this study.


TABLE 25

TESTS OF ASSOCIATION BETWEEN IDEAL SCIENTIFIC ORIENTATION
AND JOB SATISFACTION SCALE SCORES, TOTAL SAMPLE AND
SELECTED SUBSAMPLESa


Job b
Situations Spearman's rho Significant

University NASA, University Non-NASA,
Federal NASA -0.031 No

University NASA, University Non-NASA -0.156 No

University NASA -0.297 No

University Non-NASA 0.186 No

Federal NASA 0.260 No


Spearman's rank order correlation coefficient used.
Two-tailed tests.


Discussion

It would appear that there is no difference in the ideal scien-

tific orientation of scientists in the university and in federal NASA












employment. The Ideal Scientific Orientation Scale has demonstrated

that there may be an overriding normative attitude along which these

scientists are distributed. Even though it is noted by Barber (1953),

Kaplan (1965), and Kidd (1959), and others that both applied and pure

research are carried on in the university and in the federal govern-

ment, the basic orientation of scientists both in the university and

in NASA projects is to be a pure scientific approach. This would

seem to support Etzioni's observation that among scientists:

.basic research has a higher status than
applied research, and, left on their own, scientists
might well neglect applied research (Etzioni, 1964:
48-50).

It has further been noted (test of the fifth hypothesis) that

there are differences in Commitment Scale scores between university

scientists and federal NASA scientists. University NASA scientists

are the most committed, followed by university non-NASA scientists

and then federal NASA scientists. This may be the result of both the

nature of the Commitment Scale and/or the structure of the university

which, if one may speculate, allows and provides greater opportunities

for university scientists to score "high" on the index. It may also

be a function of age. The most productive or committed subsample is

also the oldest (reference, Table 3), the least committed is the

youngest, and the subsample which is in the middle on commitment is

also in that position on age.

If there are no differences among scientists' orientations,

but there are differences in their commitment, what is the relationship











between ideal scientific orientation and commitment? It was hypothe-

sized that the higher the scientists' ideal scientific orientation

scores, the more committed they would be. However, when this hypothesis

was tested, there was no apparent relationship.

Although this second major hypothesis was rejected, some rela-

tionships appear when one plots the respective scores according to job

situation and controls for age. Although all of the following explana-

tions of these relationships are tentative, they may be useful for

further exploration of the relationship between Ideal Scientific

Orientation scores and Commitment Scale scores. These relationships

are not tested in this study because the "N" is too small in each

instance.

First, when one looks at the breakdown of the scientists by

age categories (under and over forty years of age) and job situation,

it becomes apparent that among university NASA scientists, both under

and over forty years of age, a negative relationship exists between

ideal scientific orientation and commitment (Figure 2). That is, the

higher the university NASA scientists' Ideal Scientific Orientation

scores, the lower their Commitment Scale scores. When one looks at

the university non-NASA scientists, one finds the category under forty

years of age showing a positive relationship between ideal scientific

orientation and commitment. The university non-NASA scientists show no

relationship for the age category over forty years of age. When one

looks at the federal NASA scientists, a positive relationship exists

for both age categories. That is, the federal NASA scientist subsample










O A An


AO O ALA


O AO AA











A 0 AA


a A A AA


Ao


* 0O O


I I I I I I


1 2 3 4 5 6

Commitment Scale Scores


I I
7 8


Under 40 Over 40


University NASA
University Non-NASA
Federal NASA


Figure 2. Relationship Between Ideal Scientific Orientation and
Commitment Scale Scores, University NASA Scientists,
University Non-NASA Scientists, and Federal NASA Scientists,
By Age Categories.


* n


A6 A












reflects a pattern: the higher the Ideal Scientific Orientation

scores, the higher the Commitment Scale scores.

Second, in trying to explain these relationships it may be

useful to look at the broad categories of respondents' ages, education,

and fathers' social status (Tables 3, 4, and 6, respectively). In

Table 3, it is demonstrated that the university subsample is the "oldest"

in the sense that 62 percent of the subsample is over forty years of

age, with a mean age of 44.6 years. University non-NASA scientists have

46 percent in this age category, with a mean age of 44.0 years, and

federal NASA has only 40 percent, with a mean age of 38.1 years. The

relationship between ideal scientific orientation and commitment, when

looked at by age and job situation, seems to go from a positive associa-

tion (i.e., university non-NASA under forty and the total federal NASA

subsample), to no association (i.e., university non-NASA very forty),

to a negative association (i.e., total university NASA subsample).

Another possible explanation can be given from the data collected

on the respondents' education. Table 4 shows that the university NASA

subsample is the most highly educated. It is followed by the university

non-NASA subsample, and then the federal NASA subsample. The differences

are fairly large. With 100 percent of the university NASA subsample

having completed the doctoral degree, 96 percent of the university non-

NASA having done so, and with only 20 percent of the federal NASA sub-

sample having done so, some relationship between ideal scientific

orientation and commitment and education of the respondents seems





83


plausible. Specifically, the greater the formal training of the scien-

tists, the more negative the relationship.

A third explanation can be given from the data collected on the

social status of the scientists' fathers. Table 6 shows that the

university NASA scientists come largely from the professional and blue

collar categories (62 percent and 38 percent, respectively). Among the

university non-NASA subsample, 62 percent come from the professional

category, 13 percent from the white collar category, and 32 percent from

the blue collar category. It could be that the relationship between

ideal scientific orientation and commitment can be attributed to the

social class differences among the subsamples.

When one looks at the work settings in which the scientists are

located and tests the relationship between attitudes on job satisfaction

and on ideal scientific orientation, and between job satisfaction and

commitment, it appears that the former are not related and that the

latter are related. The test of the fifth hypothesis demonstrated that

there are differences in attitudes on job satisfaction among the sub-

samples. The university scientists appear to be more satisfied with

their jobs than the federal NASA scientists. It was found further

that there is no relationship between attitudes on job satisfaction

and ideal scientific orientation in the test of the sixth hypothesis.

Although some relationship between job satisfaction and commit-

ment was initially established, when job situation was controlled the

relationship disappeared. It would appear that Pelz and Andrews'











observation that the effectiveness of scientists is not necessarily

related to job satisfaction is supported. However, it might be con-

cluded that effectiveness and job situation are related since the

university NASA scientists and the university non-NASA scientists are

both more satisfied with their jobs and more committed, or productive,

than the federal NASA scientists.

When all of the above is considered, it appears that job situa-

tion is the most important determining variable in the tests of the

stated relationships. Structurally, university employment seems to be

more conducive to job satisfaction and to productivity or commitment

then does federal employment.











CHAPTER VI

SUMMARY AND SUGGESTIONS FOR FUTURE RESEARCH


Science is an institution possessing shared normative attitudes

defining permissible patterns of behavior. Implicit in these attitudes

are normative contradictions which arise when scientists find themselves

in different job situations with different reward systems.

This study has attempted to compare the attitudes of university

scientists with NASA grants with the attitudes of other university

scientists without such grants and with the attitudes of scientists

in federal NASA projects. It compared the attitudes of scientists in

the sample according to job situation through construction of an Ideal

Scientific Orientation Scale, a Commitment Scale, and a Job Satisfaction

Scale.

An elaborate and complex interview schedule was used to inter-

view scientists at the University of Florida with NASA Institutional

Grants, scientists in the same university departments without such

grants, and federal NASA scientists at the Goddard Space Flight Center,

Greenbelt, Maryland, and at the Marshal Space Flight Center, Huntsville,

Alabama. In addition to the responses to statements used in the con-

struction of the three scales, the following data were used to present

social profiles of the scientists: (1) respondents' fathers' educa-

tion and occupational status; (2) respondents' religious affiliations;

(3) respondents' education and marital status; and (3) standard demo-

graphic data such as respondents' areas of specialization, age, sex,












geographic mobility, size of families of procreation, and size of

families of orientation.

The demographic information revealed similarities and dif-

ferences between the samples used in this research and the national

scientific population. The following were established. First,

physicists are overrepresented in the federal NASA subsample and

astronomy is overrepresented in both NASA subsamples. Chemistry and

mathematics are underrepresented in both NASA subsamples. This seems

to support Abelson's (Burke, 1966) claim that NASA affects scientific

manpower in the United States through disproportionate employment.

Second, Burke's (1966) observation that NASA also draws dis-

proportionately from among younger scientists was generally supported.

When compared to the national group of scientists, the federal NASA

subsample has a higher proportion under forty years of age. The

university NASA subsample, however, is substantially older than the

federal NASA subsample, and is very much like the national group when

the age categories of under and over forty years of age are compared.

It is suggested that this difference between the two NASA subsamples

is attributable to the higher educational demands of the university

setting as well as to the necessary qualifications for receiving a

NASA grant.

Third, women are underrepresented in these samples when compared

to the national group. Women are also underrepresented in the national

group in that they comprise only 9 percent of it. This suggests that

women are, in general, underrepresented in scientific endeavors.











Fourth, it appears the university subsamples are more highly

educated than the national group, while the federal NASA subsample

is less educated than either group. Again, the higher educational

demands of the university seem to account for the differences. The

lower educational demands of federal NASA employment may account for

the lower educational achievement of NASA scientists.

Fifth, differences between this sample and the national group

appear in the social status of the scientists' fathers. These samples

have higher percentages of fathers in the professional category than

does the national group. The differences may be the result of the

wider range of employment of scientists in the national group when

compared to the three job situations represented in this study.

Other demographic data are presented for which comparisons with

the national group are not possible. Data on the education of the

scientists' fathers revealed that university NASA scientists' fathers

are more likely to have at least the Bachelor's degree. University

non-NASA scientists' fathers were next, followed by the federal NASA

scientists' fathers. The latter were most likely to have completed

only a high school education.

Data on size of the scientists' families of orientation and

procreation show the federal NASA subsamples to have more large families

of orientation. The NASA subsamples are shown to have more small fami-

lies of procreation than those from which they came. The greatest

generational continuity is shown by the university non-NASA subsample.











Data on religious affiliation showed Protestants to be most

heavily represented in the university NASA subsample, followed by the

federal NASA subsample and the university non-NASA subsample, respec-

tively. Catholics were most common in the federal NASA subsample while

Jews were most common in the university non-NASA subsample.

Three scales were constructed to test the hypotheses concerning

differences, if any, among the subsamples. Each of the three scales

met the requirements for Guttman scaling as follows: (1) coefficient

of reproducibility of at least .90--Ideal Scientific Orientation

Scale, .915, Commitment Scale, .926, and Job Satisfaction Scale, .915;

(2) each item in each scale had at least 20 percent and no more than

80 percent favorable responses; (3) each scale had no pattern of errors

represented by non-scale types exceeding more than 5 percent of the

total number of respondents; (4) final number of items were between five

and ten--ten for the Ideal Scientific Orientation Scale, seven for the

Commitment Scale, and ten for the Job Satisfaction Scale; and (5) all

items in each scale were dichotomized according to the Cornell Technique

and every scale type of each scale had at least 5 percent of the total

number of respondents for each scale within it. It is assumed that

these scales are valid instruments since they meet the criteria set

forth in the literature on Guttman scaling (Stouffer, et al., 1950;

Edwards, 1957; and Riley, 1963).

The following hypotheses were tested using the Spearman rank

order correlation coefficient and the Mann-Whitney U test. (1) There

is no difference in the ideal scientific orientation of university











scientists and scientists in federal NASA projects. (2) The higher

the ideal scientific orientation scores of the scientists, the more

they will adhere to their commitment in practice. (3) There is no

relationship between job satisfaction and the effectiveness of scientists.

(4) There is no difference in job satisfaction between university

scientists and scientists in federal NASA projects. (5) There is no

difference in the professional commitment of university scientists

and of scientists in federal NASA projects. (6) There is no relation-

ship between scientists' ideal scientific orientations and their job

satisfaction.

The test of the first hypothesis revealed that there seems to be

an overriding scientific orientation which is normative for scientists

regardless of their job situations. It was concluded that science, as

an institution, is normative for the scientists in this study. However,

even though these scientists were found to be scalable along a pure

research orientation with no significant differences by job, the test

of the sixth hypothesis showed that there is no relationship between

ideal scientific orientation and job satisfaction. This suggests that

job satisfaction does not necessarily affect the scientists' ideal

scientific orientations, even though university scientists are more

satisfied with their jobs than are the federal NASA scientists.

When the relationship between ideal scientific orientation and

commitment was tested, no relationship was immediately discernible. When

this relationship was analyzed by job situation and by two age categories,

some relationships appeared. For university NASA scientists in both age




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