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Group Title: Conference on Gender Issues in Farming Systems Research and Extenion, University of Florida, February 26 to March 1, 1986
Title: Research, recommendation, and diffusion domains: a Farming Systems approach to targeting
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Title: Research, recommendation, and diffusion domains: a Farming Systems approach to targeting
Series Title: Conference on Gender Issues in Farming Systems Research and Extenion, University of Florida, February 26 to March 1, 1986
Physical Description: Book
Language: English
Creator: Wotowiec, Peter
Poats, Susan
Hildebrand, Peter E.
Publisher: University of Florida
Publication Date: 1986
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Subject: Farming   ( lcsh )
Agriculture   ( lcsh )
Farm life   ( lcsh )
University of Florida.   ( lcsh )
Spatial Coverage: North America -- United States of America -- Florida
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Volume ID: VID00001
Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved, Board of Trustees of the University of Florida

Table of Contents
    Front Cover
        Page i
    Title Page
        Page ii
    Abstract
        Page iii
    Main
        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
    Reference
        Page 15
        Page 16
Full Text


















Conference on
GENDER ISSUES IN FARMING SYSTEMS
RESEARCH AND EXTENSION


~













RESEARCH, RECOMMENDATION, AND DIFFUSION DOMAINS:
A FARMING SYSTEMS APPROACH TO TARGETING













By


Peter Wotowiec Jr., Susan Poats, and Peter E. Hildebrand


Paper submitted to the 1986 conference on
Gender Issues In Farming Systems Research And Extension

University of Florida
Gainesville, Florida 32611
February 26, 1986


~
i~F












ABSTRACT


This paper explores a methodology for targeting on-farm research
on the basis of gender, social, physical, and biological consider-
ations, which will lead to more efficient technology development and a
more socially conscious distribution of the benefits of agricultural
research and extension. The domain concept in farming systems research
and extension (FSR/E) is discussed, and refinements are suggested to
sharpen the targeting focus at each stage of the farming systems
sequence.

Research, recommendation, and diffusion domains are compared and
contrasted in definition and practical utilization in FSR/E field
activities. An example is given to illustrate the potential of this
refined targeting methodology. It is concluded that this conceptual
framework is an important tool for ensuring consideration of
heterogeneity among farming systems and for accounting for gender,
social, and biophysical factors in decisions made at each stage of the
farming systems research and extension process.










RESEARCH, RECOMMENDATION, AND DIFFUSION DOMAINS:
A FARMING SYSTEMS APPROACH TO TARGETING

Peter Wotowiec Jr., Susan Poats, and Peter E. Hildebrand 1/



TARGETING FARMING SYSTEMS ACTIVITIES: HOMOGENIZING VARIABILITY?

Inherent in the farming systems approach is the recognition of
the complexity and variability of the circumstances and problems faced
by farmers in managing their farms as a whole, comprised of
inter-related crop, animal, household, and off-farm enterprises.
Diversity in farming systems must be recognized in developing
appropriate technologies for the farmers who manage those systems.
Targeting, on the other hand, entails the grouping together of
similar clientele so efforts might be efficiently focused. However,
by describing a group of farming systems as relatively homogeneous,
based upon a few simple factors, existing variability among farms is
often not sufficiently considered by Farming Systems Research and
Extension (FSR/E) practitioners (Cornick & Alberti 1985).

Although the concept of targeting might seem contrary to the
recognition of heterogeneity among farms, it is an essential component
of the farming systems approach. It is not practical to conduct
research tailored specifically to a few individual farmers. On the
other hand, research carried out for farmers in general is unlikely to
produce technologies which are appropriate to all the varied types of
farming systems present. How can FSR/E teams attempt to define and
target homogeneous groups of farming systems without losing sight of
the heterogeneity among them? This issue is mirrored in the different
positions taken by farming systems practitioners.




1/ Respectively:

Research Assistant, Agricultural & Extension Education Department;
Associate Director, Farming Systems Support Project;
Professor, Food and Resource Economics Department.
University of Florida. Gainesville, FL. 32611.









One point of view stresses the early definition of homogeneous
groups of farmers using the recommendation domain concept, so as to
guide subsequent research activities. Collinson (1979, 1980), Gilbert
et al. (1980), and Franzel (1985) advocate ex ante delineation of
recommendation domains based on secondary data and preliminary
surveys, followed by a formal survey to refine the domain boundaries.
Both Collinson and Franzel describe a technique of defining
recommendation domains through interviews with extension agents and
local authorities before actually commencing activities and
interactions with farmers. Early definition of recommendation domains
is based upon a few relatively easily identifiable factors such as
soil type, agroecological zones, and crop type and management
(Harrington and Tripp 1985). These authors note or imply the
importance of continuing the refinement of domain boundaries
throughout the sequence of on-farm adaptive research, but the idea
remains that subsequent reassessment of recommendation domains is
often not vigorously pursued.

A more recent view states that grouping homogeneous farming
systems should not take place until the researchers have an adequate
understanding of the variability inherent in local farming systems,
usually not gained early in the work in an area. Cornick and Alberti
argue that recommendation domains established early are frequently
poorly conceived. This early definition of recommendation domains
leads to a premature assumption of homogeneity. In turn, this may lead
to a bias owing to a lesser emphasis upon the study of potential
variability in factors not initially considered such as long term
climate-induced trends in cropping patterns, household decision-making
and labor allocation, or relationships between on-farm and off-farm
activities. For example, Cornick and Alberti note:

"...the roles of women and children that can be critical
factors in the development and subsequent adoption of
technologies are often explicitly excluded from consideration
in recommendation domains. This occurs because the usual time
frame for development of recommendation domains is inadequate
to the task of understanding intra-household dynamics and the
importance they hold in the system" (p. 1).









Socioeconomic factors in particular are often not fully integrated
into domains defined early, owing to the longer time period necessary
to gather this information. In general, proceeding with on-farm
research and other activities on the basis of a hastily achieved
assumption of homogeneity could result in inefficient conduct of
subsequent research and might lead to the promotion of solutions which
are not appropriate to farmers (p. 25).

In this paper we explore the issue of variability versus
homogeneity in the targeting of farming systems research and extension
activities. After a brief review of targeting in FSR/E using
recommendation domains, problems in the conventional use of this
concept are further considered. A refined concept of targeting and the
role of domains in FSR/E is described in an attempt to bring together
the two differing viewpoints and to begin to resolve the targeting
quandary.

OVERVIEW OF TARGETING AND RECOMMENDATION DOMAINS

Targeting For Efficiency And Social Equity

Farming systems research and extension must differentiate between
various potential farmer-client groups and determine the particular
needs of each, if technologies are to be developed which clearly meet
those needs (Byerlee & Hesse de Polanco 1982). Most literature on the
subject of targeting in farming systems has stressed the increase in
efficiency of farming systems research and extension activities made
possible through focusing upon specific, relatively homogeneous farmer
groups.


Efficiency in allocation of research resources is essential if a
program is to reach and benefit a maximum number of farmers. By
focusing scarce resources upon roughly similar groups of farmers,
research programs are able to carry out investigation on a selected
number of representative farms, and later transfer the findings to the
comparable situations faced by other farmers.









Targeting is also important in justifying the farming systems
approach to institutional policy makers who are concerned about social
equity in the distribution of the benefits likely to result. Farming
systems practitioners use targeting concepts to assist them in making
decisions which increase the likelihood of an optimal distribution of
research results among the members of a community.

Conventional Concept Of Recommendation Domains

The concept of "recommendation domains" has been widely used in
targeting farming systems research since Perrin et al. (1976) first
introduced the idea. It is described and defined by Byerlee et al.
(1980) in the following manner:
"... a recommendation domain (RD) is a group of farmers with
roughly similar practices and circumstances for whom a given
recommendation will be broadly appropriate. It is a
stratification of farmers, not area: farmers, not fields, make
decisions on technology. Socioeconomic criteria may be just as
important as agroclimatic variables in delineating domains.
Thus resulting domains are often not amenable to geographical
mapping because farmers of different domains may be
interspersed in a given area" (p. 899).

Using this definition, neighboring farm households might be
placed in different recommendation domains because of differences in
availability of family labor. In societies where women cultivate
different crops than those of the men, female farmers could comprise a
recommendation domain separate from male farmers even if they are from
the same family.

Expanding Upon The Definition Of Recommendation Domain

Perrin et al. originally conceived of the notion of
recommendation domains as an aid to researchers for targeting the
development of technologies to specific audiences. The concept has
been expanded since then to include a number of additional situations
and purposes. Some of the most common applications of recommendation
domains include the following, gleaned from current literature on the
topic:










making policy decisions
identifying priority issues for research
specifying clientele for developing recommendations
selecting representative sites and farmer-cooperators
focusing analysis of surveys and on-farm trials
orienting extensionists to groups of similar farmers
transferring adapted technology to appropriate farmers
enhancing equitable distribution of FSR/E benefits


As Harrington and Tripp point out, the domain concept is vital to
every stage of the on-farm research process. However, it is apparent
from reviewing writings on the subject that the concept and definition
of recommendation domain not only changes at each stage, but also
varies according to the individual who applies it and to the end
sought. Because of wide variability among farmers and farms, and owing
to the dynamic nature of the farming systems development sequence, it
appears that some confusion exists among FSR/E practitioners as to the
general meaning and use of the term recommendation domain.

On-Farm Variability And Conventional Recommendation Domains

The emphasis by Byerlee et al. upon "farmers, not fields" as the
sole basis for the delineation of recommendation domains is not
warranted because of the variability found in some field situations.
Cornick and Alberti cite the case of farmers in the community of
Quimiaq in the mountains of Ecuador who manage different cropping
patterns in different agroecological zones, a product of altitude,
temperature and rainfall variation on the mountain slopes.

Not only does each farm cross agroecological zones, but the cropping
patterns found in each field vary greatly from year to year. For
example, depending upon a farmer's perception of trends and yearly
changes in climatic conditions, bean and/or fava bean intercrops will
be assigned to maize fields located at varying elevations along the
slope.









Gender and intra-household variables are often neglected in the
process of defining a recommendation domain because of the relatively
more difficult and lengthy task of collecting and analyzing data on
these variables. As opposed to the usefulness of secondary data on
agroecological characteristics for defining recommendation domains,
existing information concerning gender and household variables often
reveal little useful insight for this purpose. Additionally, gender
and household information which does exist may be difficult for FSR/E
teams to acquire locally.

Nevertheless, superficial understanding of these variables
without continued investigation can lead to erroneous assumptions
about farmer behavior, (particularly about female farmers), and to the
design of inappropriate technologies. FSR/E practitioners need to keep
this concern in mind. By prematurely striving to define homogeneity
among farm households and their farms, it is possible to overlook the
variability which exists among them.

REFINING THE CONCEPT OF DOMAINS

It is our argument that the issue of targeting in farming systems
research and extension has become confusing because we have been
trying to stretch the definition of the term "recommendation domain"
to cover too many situations and too many different purposes. Farming
systems practitioners must begin to develop a common understanding of
how the use and definition of "domains" change as the farming systems
sequence progresses from initial characterization through problem
diagnosis, testing, adaptation, evaluation, and, finally, to the
delivery of the new technology to the farmer.

It is essential to account for the heterogeneity present in
farming systems, even while delineating relatively homogeneous groups.
We propose a refined and expanded concept of the use of domains in
targeting, designed to distinguish between differing intents and uses
of domains, while allowing enhanced consideration of the diversity
among farm households and farming systems.











Essentially this is accomplished by recognizing a problem focus in the
definition of the domains, by tying the changing concept of domain
more closely to the farming systems sequence, and by stressing a
greater inclusion of socioeconomic considerations into the targeting
process. We believe the refinements outlined below are more on the
order of a sharpening of focus not a changing of terminology, which
will lead to increased utility of this method of targeting in the
field.

Any of the three types of domains described below may be defined
within specific geographic boundaries for ease in conceptualization,
but it is imperative to realize that domains do not necessarily
include all the area within the boundaries prescribed. Because domains
are based upon a specified problem focus and upon socioeconomic
considerations in addition to the more geographically mappable factors
of climate, altitude, and soil, they are actually interspersed
intermittently in a discontinuous pattern throughout a geographic
area.

Research Domains: Targeting For Variability

A research domain is a problem-focused environmental
(agroecological and socioeconomic) range throughout which it is
expected that hypothesized solutions to a defined problem could have
potential applicability and therefore should be tested. Research
domains are determined during the initiation of research activities,
largely by consideration of biophysical (agroecological) factors, with
some attention to socioeconomic and gender issues.

Recommendation Domains: Targeting For Homogeneity

Research domains are comprised of one or more agro-socioeconomic
recommendation domains, which are tentatively defined based upon the
response of a specific technology to the actual agro-socioeconomic
conditions found on farms. A recommendation domain is a group of
farmers (or farmers and their fields) with a common problem for which
a tested solution meets their (the farm decision-makers') biophysical
and socioeconomic requirements for adoption.










In the Ecuadorian case cited by Cornick and Alberti,
recommendation domains would be based not only upon farm households,
but also upon their separate fields which are not contiguous, but
widely dispersed in location and altitude. Each household might fall
into several recommendation domains depending upon; (1) where, along
the agroecological gradient of the mountainside, their fields are
located; (2) the climate-related crop management decisions made for
each of those fields; and, (3) the particular problem solutions to be
tested.

Recommendation domains are seen as tentative in nature throughout
the on-farm adaptive research process. Recommendation domains are
initially hypothesized by the FSR/E team on the basis of on-farm
exploratory and refinement trials, information collected through
directed surveys, and subsequent on-farm verification trials. Over
time, as more information is gathered, the recommendation domains are
refined and redefined so as to closer approach reality.

Diffusion Domains: Targeting For Communication

Diffusion domains are interpersonal communication networks through
which newly acquired knowledge of agricultural technologies naturally
flows (Hildebrand 1985). Informal flow of information through a
community grapevine is substantial (Rogers 1983). From farmer to
farmer, neighbor to neighbor, store operator to patron, information
about new ideas moves through a farming community. Thus, awareness of
a new technology being verified in on-farm trials, and of its response
under local conditions, takes place among farmers and their families
who are not directly involved in the on-farm research.

A farming systems team can operate so as to enhance the
informational effect of on-farm research activities in a community. By
understanding the local communication networks in an area, the FSR/E
team can strategically locate on-farm verification trials in each
diffusion domain to enhance the diffusion of information about a new
technology among potential users. This ensures a broader, more
equitable distribution of information because it has the potential of
reaching farmers who are difficult to reach through conventional
extension methods. These are farmers who rely greatly upon localized
interpersonal communication to acquire information.
8










Frequently, information about new technologies developed in
agricultural programs tends to be communicated only through male
information networks. In some societies information about technologies
is diffused only slowly, if at all, from men to women, even within a
household. Female farmers are clearly disadvantaged in learning about
new technologies if they cannot participate in male-oriented
dissemination programs. Definition and use of diffusion domains in the
FSR/E testing process allows practitioners to recognize and plan for
the fact that men and women often have different communication
networks.

FIELD USE OF THE DOMAIN CONCEPT

In practice, farming systems teams work in a project area located
on the basis of geographical and political considerations rather than
biological conditions or socioeconomic concerns. Within a project
area, project focus can be based on a specific priority commodity
commonly produced by farmers in the area, or may be based on
socioeconomic considerations such as an emphasis upon small farmers or
women farmers. The farming systems team working in the area may have
responsibility for determining project focus. Only seldom, however,
will the team have input into defining the project area. Even though
of great importance in targeting farming systems efforts, the process
of selecting the project area and project focus lies beyond the scope
of this paper. The discussion will commence with subsequent stages of
the targeting process. For the sake of brevity and clarity, a
relatively simple example will be used.

A Case Of Targeting In The Farming Systems Approach

The following example is drawn from farming systems activities in
Central America (Ruano 1977, Hildebrand and Cardona 1977, Reiche Caal
et al. 1976). Although based on actual experiences and cases, some
liberty has been taken with its portrayal here to show how this
refined concept of domains might have been advantageously applied.










A farming systems team from the national research institute,
composed of three agricultural technicians, one economist, and one
anthropologist (all males), was assigned to a certain hilly section of
the country. The team mandate, in accordance with national
agricultural production objectives, was to work on improving the
production of basic grains among small, resource-limited farmers in
the project area (a commodity and socioeconomic based project focus).

S Initial informal reconnaissance of the area and a review of
secondary information revealed that the area was comprised of
relatively flat, fertile lands in the valley bottoms and poorer, rocky
soils on the slopes. The larger, fertile farms in the valley bottoms
were owned by wealthier farmers who were able to employ mechanization
in their cultivation systems. Tractors were used in their monocultural
stands of maize and short, improved sorghum varieties. In contrast,
the hillsides were largely devoted to small farmer cultivation, with
farms averaging about 3.5 hectares. Sorghum and maize were
interplanted using mostly traditional, taller sorghum varieties. A few
farmers employed bullocks and plows on their farms, but most
cultivated their crops by hand.

In keeping with their project focus, the team decided their
attention should be targeted on the smaller hillside farmers and
farms. A sondeo (Hildebrand 1982), or diagnostic survey, conducted in
the hillside region revealed that farmers in the hillside areas used
similar systems of intercropping maize and sorghum. They complained
that the scarcity and irregularity of rainfall had made maize
cultivation an increasingly risky endeavor. Farmers were unable to
grow enough maize to meet their consumption needs.

Because the irregularity of rainfall frequently caused the
failure of the maize crop, the more drought-tolerant sorghum was being
grown as a supplement to it. However, farmers expressed a dislike for
eating sorghum and indicated they only grew it to sell for animal
feed, using the proceeds to purchase maize. In this sense,
substituting cultivation of sorghum for maize reduced the risk of crop
failure yet provided for the household subsistence needs.









Sorghum production in the area was higher per unit planted than
maize, but still below production levels achieved elsewhere in
similar environments with improved varieties. As one facet of their
farming systems program, the team hypothesized that selected improved
sorghum varieties within the traditional cropping system could lead to
a partial solution to the identified production problem.

Based on these findings, the team denoted the hillside maize and
sorghum farmers, (and their fields), with declining maize yields as a
single research domain (problem-focused, agroecological range). A
series of exploratory trials was designed for placement throughout the
research domain.

At harvest, the team collected production data as well as
information on farmer opinions about the new varieties. Even though
the new, earlier varieties performed well on all test sites, there
were sharp differences among farmers as to their acceptability. Some
farmers were planning to keep seed and plant the new varieties again
the following season. Others were quite disinterested in the
varieties, but their reasons were unclear to the team. Based on farmer
evaluations, the team partitioned the research domain into two groups
of farmers; those interested in planting the sorghums again, and those
not. The former group became a tentative recommendation domain and
more precisely refined trials were designed to continue testing the
varieties under farm conditions, while further determining the reasons
for the farmers acceptance of the new sorghums. For the other group,
more information was needed by the team to determine why the new
sorghums were unacceptable. Thus, this group continued to constitute
the research domain.

Information had been collected to characterize the farming
systems of the area while monitoring the exploratory trials.
Continuous contact of the team members with farmers during this period
had yielded much additional socioeconomic information not apparent
from the initial sondeo activity. It began to appear that all hillside
farmers and their farm systems were not alike.









Some farmers at slightly lower elevations had soils with better
water retention characteristics than other farmers on higher slopes.
These farmers could plant maize with a greater assurance of obtaining
a harvest than those at higher locations with poorer soils. Through
additional directed interviews it was found that lower elevation
farmers tended to grow sorghum primarily as a cash crop. Because of
their favored soil conditions, they possessed enough cash from crop
sales to ensure a continuous supply of maize in the household. These
farmers did not consume sorghum.


Over time the team came to realize, though most people claimed
they did not eat sorghum, many were actually using it as a substitute
for maize. They hypothesized that sorghum consumption tended to
increase among households farming the poorer, higher elevation fields
which tended to those less well off. However, it was apparent that
farmers of this group were also those who were not interested in the
new higher-yielding sorghums. As one aspect of their attempt to
resolve this seeming contradiction, the team initiated informal
surveys with women of the households within this group. Unfortunately,
owing to socio-cultural barriers, the male team members were unable to
obtain adequate information.

This was corrected by temporarily adding to the team a female
social scientist from the institute headquarters, to conduct the
interviews. She found that these families did consume sorghum,
although they had not always done so. Decreasing maize harvests and
lack of resources for the purchase of maize had forced them to consume
sorghum. Women interviewed indicated that consumption of sorghum
implied a certain social degradation, a "shame" in the eyes of
neighbors. In many cases, a farmer whose family consumed sorghum was
considered a poor provider. To the casual observer, sorghum
consumption was not apparent among the farmers; but as the team moved
deeper into the community, they found that sorghum was an important
part of the diet among families lacking maize.









Further study of sorghum preparation, cooking and taste
preferences revealed that, like maize, it is primarily eaten in the
form of tortillas, either prepared with maize or alone. Women said
some of the new varieties tasted bitter and were not fit for
consumption. One of the new varieties was not bitter-tasting, but due
to purple glumes, it left telltale dark spots when made into
tortillas. Although the purple glumes could be removed after many
washings, this was an unacceptable alternative for most families
because of a scarcity of readily available water in the higher
elevation areas of the research domain.

Using this information, the team partitioned the original
research domain into two recommendation domains. For the earlier
tentatively defined recommendation domain, consisting of farmers who
produced sorghum destined for the animal feed market, on-farm testing
of the previously introduced new sorghum varieties was continued. For
the second recommendation domain, composed of relatively poorer
farmers producing sorghum for home consumption under less favored soil
conditions, the team recommended that the research institute acquire
or develop varieties with less coloring and no bitter taste, which
could then be tested on-farm with the farmers in this group.

Through this experience, the FSR/E team and the research
institute began to realize that, although, in the local culture,
women were not directly involved in sorghum production, they did have
considerable influence in making cropping decisions which affect
household concerns, such as consumption. Newly cognizant of the need
for an aumented social perspective in their development activities,
the team began a second phase of on-farm experimentation targeted
towards the two separate recommendation domains.

At the same time, they began to work with local extension
personnel to study the flow of agricultural information among the
farmers and households in the region. Recognizing the role which
household consumption preferences play in the adoption or rejection of
sorghum technologies, female team members and interviewers were added
to the farming systems program to ensure a balanced gender
perspective.










Among the many local information pathways, it was found that women
exchanged much information about sorghum and other agricultural crops
with other women at the weekly markets. Among men, interpersonal
communication concerning farming and crops took place on Sundays when
farmers from the surrounding countryside congregated in the town plaza
to converse and visit. By the close of the second season of farming
systems activities, the team had tentatively defined several local
diffusion domains based on gender, religious affiliation, locality
groups, and other factors. On-farm trials and extension efforts were
managed to ensure information flow to each diffusion domain.

CONCLUSION

This greatly simplified case provides an example of how the
refined domain concept allows grouping of roughly homogeneous farmers
while not losing sight of the heterogeneity inherent among them. This
conception of domains is not a static one, but one which recognizes
the changing nature of the targeting process as a result of on-going
information gathering through surveys, participant observation, and
on-farm experimentation. Maintaining a flexible determination of
domains allows for a greater understanding of the diversity of local
farming systems, of the rationale behind the behavior of farmers, and
of the effect of gender and social factors upon the local practice of
agriculture.









REFERENCES


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1980 Planni'ng technologies appropriate to farmers: Concepts and
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Byerlee, D. and Hesse de Polanco, E.
1982 The rate and sequence of adoption of improved cereal
technologies: The case of rainfed barley in the Mexican
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Collinson, M. P.
1980 A farming systems contribution to improved relevancy in
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Collinson, M. P.


1979


Cornick,
1985



Franzel,
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T. and Alberti, A.
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S.
Evaluating a method for defining recommendation domains: A
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Gilbert,
1980


E. H., Norman, D. W. and Winch, F. E.
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Michigan


Harrington, L. W. and Tripp, R.
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Hildebrand, P. E.
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Hildebrand, P. E.
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Hildebrand, P. E. and Cardona, D.
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Perrin, R. K., Winkelmann, D. L., Moscardi, E. R. and Anderson, J. R.
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Reiche Caal, Enrique, C., Hildebrand, P. E., Ruano, S. R. and Wyld, J.
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Rogers, E. M.
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Ruano, S. R.
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limitaciones. Guatemala: ICTA.




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