contextualizing farmers’ attitudes towards genetically modified crops

Contextualizing farmers’ attitudes towards genetically modified crops

Kazumi Kondoh1 and Raymond A. Jussaume Jr.21Department of Sociology, Washington State University, Pullman, Washington, USA; 2Department of Community and Rural

Sociology, Washington State University, Pullman, Washington, USA

Accepted in revised form March 23, 2005

Abstract. Analyses of the role of technological development in agriculture are central to an understanding of socialchange in agri-food systems. The objective of this paper is to contribute to the formation of a broader perspective ofhow farmers are positioning themselves with respect to controversial agricultural technologies through an empiricalanalysis of Washington State farmers’ willingness or unwillingness to try Genetically Modified Organisms (GMOs)technology on their farms. The use of this type of biotechnology in farming has been criticized for its potential harmfuleffects on natural environments and socio-cultural systems, while proponents highlight the possibilities for increasingproduction with minimal use of other inputs. An analysis of the extent of farmers’ expressed willingness to use GMOsprovides an opportunity to better understand how their diverse thoughts about controversial agricultural technologiesare shaped not only by their own experiences but also by social context. The present study does this by analyzing datafrom a farm survey conducted on a random sample of farmers from across Washington State. The results show that theproduction practices farmers utilize and the market strategies they employ may be at least as useful as farmers’ socio-economic characteristics in explaining what types of farmers appear to be more or less interested in potentially usingthis technology. Furthermore, the relationship between level of formal education and willingness to use GMOs is notstraightforward. It may hide differences between farmers with respect to where and how they received their formaleducation as well as the type(s) of knowledge they gained. It is argued that future research should recognize thediversity that exists in farmers’ interests vis-a-vis particular technologies and should also explore how these interestsare shaped by farmers’ past and present social networks and life experiences.

Key words: Agricultural biotechnology, Education, Farmer attitudes, GMOs, Socio-cultural characteristics, Tech-nology adoption, Washington State

Abbreviations: GMOs – Genetically Modified Organisms

Kazumi Kondoh is a PhD candidate in the Department of Sociology at Washington State University. Her researchinterests include environmental policies, science and technology, and sustainable agriculture.

Raymond Jussaume is an Professor and Chair, Community and Rural Sociology at Washington State University. Hisprimary areas of interest are sociology of agriculture, development sociology, and political sociology.

Introduction

The never-ending development and utilization ofincreasingly sophisticated technologies is one of thedriving forces behind the contemporary global economy.The emphasis on technological advancement is based onan ideology that the application of science to the creation ofnew technologies is essential for improving the socialcondition (Busch, 2000). Given the prominent role thattechnological advancement plays in social change, it is notsurprising that many social scientists have focused on

technological change as a useful point of analyticaldeparture. One example of the conceptual importance gi-ven by social scientists to the role of technology in socialchange is the academic debate about whether the globalpolitical economy has entered a ‘‘post-Fordist’’ era. Thisnew historical period is thought to be characterized by anincreased use of craft-oriented production technologiesand associated forms of social organization that subse-quently provide a foundation for more complex andflexible class relations and state structures (Castells andPortes, 1989; Kenney et al., 1989; Piore and Sabel, 1984).

Agriculture and Human Values (2006) 23:341–352 � Springer 2006DOI 10.1007/s10460-006-9004-6

Social science research on production agriculture hasreflected this interest in technology. Earlier research tra-ditions included human ecological studies of the influ-ence of technology in allowing human populations toadapt to environmental conditions (Albrecht andMurdock, 1990) as well as research that examined theimpact of the adoption of agricultural technologies onfarm structure and farm labor (Buttel et al., 1990). Thesetraditions have evolved as the process of technologicalmodernization in agriculture has become more complex.Technological controversies, like the use of Alar in appleproduction and the dissemination of rBGH (BovineGrowth Hormone) in the dairy industry, have made itapparent that in addition to a pro-technological mod-ernization ideology, alternative discourses now exist thatquestion the socio-cultural, environmental, and ethicaleffects of technological change (Buttel, 2000). For allmembers of society, including those who produce food,assessing the benefits and risks associated with newtechnologies has become increasingly problematic(Giddens, 2000).

The growing intensity of discussions surroundingtechnological change in agri-food systems may be besthighlighted by the debates over the desirability ofadapting biotechnology, particularly the use of geneti-cally modified organisms (GMOs), to agricultural pro-duction. Proponents argue that these technologies, whichsplice genetic material from one organism into another,could lead to a reduction in the use of petro-chemicalswhile increasing agricultural production. In a review ofthe dissemination of Bt cotton, Bt corn and Roundup-ready soybeans, Marra et al. (2002) confirmed thattransgenic crops can lead to higher profits for farmers,either as a result of reduced pesticide use (Bt cotton andRoundup-ready soybeans) or because of yield increases(Bt corn). Proponents also note that decreased pesticideuse is a desirable social and environmental goal and,thus, argue that GMO technology has the potential to bea powerful tool in the promotion of sustainable agricul-tural production systems. Additional environmentalbenefits of GM crops that can result from reduced pes-ticide applications are less soil erosion and compaction aswell as reduced fossil fuel consumption, which areattributable to less frequent use of tractors for pesticideapplications (Nelson and DePinto, 2001).

Critics of GM technology raise a variety of ecological,social, and ethical issues related to possible unforeseenlong-term impacts associated with the release of geneti-cally modified organisms into ecosystems. The potentialrisks include effects on non-target organisms such as therisks to the monarch butterfly associated with the use ofBt corn as well as the possibility of escape of the gly-phosphate tolerant gene into populations of grasses thatact as weeds in certain agricultural production systems(Kendall, 1997; Nelson and DePinto, 2001; Smith et al.,

1997). There are also philosophical and religious debatesthat include questions about whether private firms willadequately consider long-term, public-good issues thatmay result from the diffusion of biotechnologies (Batieand Ervin, 2001).

These debates over the potential benefits and risks ofGMOs are proving to be particularly stressful for agri-cultural producers. Not only must producers evaluate thepossible costs and benefits from their own perspectives,but they also find themselves caught in a tug-of-warbetween agribusiness and consumers about whether thesenew technologies should be utilized (Wilkinson, 2002).Farmers recognize that even if a technology proves to bebeneficial for on-farm management, its use could lead tochallenges in the marketplace – pressure to segregateGMO grain, for example, (Vandeburg et al., 2000;Wilson et al., 2003), or increased regulation by foreignas well as domestic political institutions. Thus, thedecision-making process surrounding adoption of newagricultural technologies has become complex for farm-ers and of interest to people and institutions that have astake in whether farmers adopt those technologies.

The objective of the research presented in this paper isto develop a preliminary assessment of how farmers’interest in GMOs is being shaped not only by their per-sonal knowledge of the technology but also by externalsocial and economic conditions. Our approach is neitherstrictly macro nor micro in perspective. Our aim is not todetermine whether individual or structural factors aremore significant in influencing farmer attitudes towardcontroversial agricultural technologies. Rather, our goalis to contribute to an emerging academic literature thatrecognizes and explains how social actors reconcilevarious competing influences during their daily lives.

We do this through an investigation of self-reportedfarmers’ attitudes in Washington State, where agriculturalproduction is highly diversified with respect to thecommodities produced and to ecological conditions. Ouranalysis recognizes that differences exist among Wash-ington agricultural producers regarding how they evalu-ate the potential benefits and risks of GMO technology.We assume that these differences are due in part to theway in which farmers balance their own assessment ofthe potential risks and benefits of a new technology withmarket and other pressures to use or not use the tech-nology. Thus, we are concerned with how farmers’ ex-pressed willingness to use GMOs may be associated withthe market structures they are part of, the types of socialnetworks they belong to, and their own personal back-grounds. In this manner, we seek to uncover some of theways in which farmers’ perceptions of a particular agri-cultural biotechnology are mediated by social structureand individual orientation. Given debates among con-sumers, policy makers, and scientists over the desirabilityof deploying GMO technology, our investigation of

342 Kazumi Kondoh and Raymond A. Jussaume Jr.

farmer interest in using this technology will provide anillustration of how human decision-making is a productof the interplay between individual perceptions andpreferences, and structural/contextual social forces.

Background

One of the earliest research traditions in agriculture hasinvestigated the process of who adopts new technologiesand why they adopt them (Nowak, 1982; Rogers, 1995). Aprimary analytical objective has been to uncover theindividual characteristics of adopters. By identifying thosefarmerswho aremore likely to adopt new technologies, thepractical goal has been to speed up the adoption of newtechnologies by other farmers (Rogers, 1995). Theempirical evidence generated by innovation of diffusionscholars has generally found that the earliest adopters of anew agricultural technology are more likely to have highersocioeconomic status, as measured by higher educationalattainment, operate larger farms, and have greater farmincomes (Buttel et al., 1990; Fliegel, 1993).

A second research tradition, inspired by critical soci-ology, investigates the role of technology in agricultureand offers a structural analysis of the process of howtechnologies are created and what the social impacts ofadopting these technologies are on individuals andcommunities. For example, Kloppenburg (1988)demonstrated how agricultural technologies are a productof history and the particular institutional arrangementsthat arise in contemporary capitalist society. Similarly,Gilbert and Wehr (2003) argued that the process of dairyindustrialization in California was not inevitable but wasa consequence of demographic, cultural, and political-economic factors. Galjart (1971) distinguished betweenfarmers’ inability to adopt a new technology due tofinancial or other constraints from an unwillingness toutilize a particular new technology, while other researchin this tradition has investigated the impacts that agri-cultural and environmental policies and regulations haveon technological change (Barham, 1996; Ribaudo andShoemaker, 1995). It is now recognized that some agri-cultural technologies can have complex socio-economicimpacts (Dorner, 1983), including negative effects onfarm laborers (Friedland et al., 1981) and their commu-nities (Albrecht, 1998). In other words, as a result ofstructural analyses, we know that technology creationand dissemination are socially constructed processes(Middendorf et al., 2000) and that technological changein agriculture is not always driven by a need to solveproduction or social dilemmas on the farm, but can bepromoted by firms seeking to increase profits and speedup capital accumulation (Busch et al., 1989).

A third research tradition that is less rooted in thepolitical economy literature but is potentially critical has

sought to evaluate the socio-economic benefits and costsof technological dissemination. Such work was inspiredin part by the publication of Rachel Carson’s (1962) Si-lent Spring, which was one of the first attempts toquestion the environmental consequences of the use ofagricultural pesticides. Studies that assessed the costs andbenefits of new agricultural technologies began to growin number and culminated in the popular and academiccontroversies surrounding rBGH in the 1980s (Buttel,2000). The promise of rBGH was that it would lead toincreased milk production with no food safety conse-quences. But many farmers began to contest this tech-nology, both in the market and in state policydiscussions, on the grounds that it would drive manydairy farms, particularly small farms, out of business.Meanwhile, many consumers were unconvinced by sci-entific arguments that the milk was safe (Busch et al.,1991; DuPuis, 2000), and questions were raised regard-ing the effects of the use of rBGH on the welfare of dairycows (Thompson, 1997). In other words, analyses of thedevelopment and diffusion of rBGH exemplify how theprocess of agricultural technological development hasbecome increasingly caught between what Buttel haslabeled ‘‘the master-frame of technological moderniza-tion’’ and ‘‘the master-frame of socio-cultural, environ-mental, and ethical critique of relentless technologicalupheaval’’ (2000: 11).

As agricultural technological development has becomemore frequently contested, researchers have begun torecognize that alternative models of agricultural devel-opment are possible. One example is the growing liter-ature on the spread of sustainable agricultural practices.Pampel and van Es (1977) found that farmers whoadopted environmental conservation practices were morelikely to have an orientation towards farming as a way oflife rather than one whose primary motivation was profit-orientated. These findings suggest that the factors thathelp explain the adoption of non-profitable conservationpractices are different from those associated with theadoption of commercially oriented technologies. Taylorand Miller (1978) reported similar findings in their studyof water pollution control practices, while Nowak (1983)found that both ecological and economic factors could beused to predict the acceptance of soil conservationpractices. Most recently, Abaidoo and Dickinson (2002)found that farmers who utilize alternative agriculturalpractices share a worldview that is different from moreconventional farmers. These studies lend support to theargument that agricultural technological development hasbecome a complex and sometimes contested process thatcan reflect different farm management strategies, humanrelationships with the environment, and farmer positionswithin agricultural structures, including markets.

Clearly, farmers’ ideologies and management practicesare diverse (Carlson and McLeod, 1978; Smith, 1982;

Contextualizing farmers’ attitudes towards GMC 343

Salamon, 1985; Jackson-Smith and Buttel, 2003). Giventhat society as a whole increasingly is debating the valueof technological change, it seems obvious to us thatfarmers would hold diverse views on the merits and risksassociated with the use of modern agricultural technol-ogies. This is not to suggest that farmers can be dividedinto distinct groups of proponents and opponents of aparticular technology. However, while ‘‘rural people(farmers) are more knowledgeable of genetically engi-neered food and fiber products’’ (Napier et al., 2004a:409) and may be more likely to think that the benefits oftheir use may outweigh on-farm risks, it does not followthat the same farmers would not be hesitant to use thetechnology. Farmers must weigh their knowledge about atechnology like GMOs against their role in the agri-foodsystem. In other words, the literature suggests thatfarmers have diverse interests in a new technology notonly because of their own evaluation of that technology,but also because of their diverse positions in political-economic structures.

Thus, it is likely that farmers’ assessments of the risksassociated with using a controversial technology arelikely to be product of their personal knowledge of thattechnology, their social interaction with other actors informal or informal social groups, and their positions inthe political economic structure. The importance of socialinteraction in influencing farm management decision-making has been demonstrated by Coughenour andChamala (2000) and Coughenour (2003). They foundthat conservation practices spread gradually among localfarmers through innovative local networks that consistnot only of farmers but also extension specialists, localsalesmen, and others. The research further demonstratedthat, as the process of adopting these practices unfolds,the network expands into even larger networks thatinclude scientists, policy makers, and farm supply com-panies. This research, which was influenced by Actor-Network Theory,1 demonstrates how farmers can come toshare knowledge and ideas with one another via formaland informal social networks (Coughenour and Chamala,2000; Coughenour, 2003). A goal of our analysis is toexamine how similar processes may be creating contextsthat help influence how farmers respond to a controver-sial agricultural technology like GMOs, without negatingthe importance of farmer characteristics in explainingtechnological choices.

To summarize, the existing social science literature onthe role of technology in agriculture suggests that farmerdecisions about whether to utilize a particularly agricul-tural technology or set of practices involve complex, andsometimes contradictory, factors. Thus, our analysis as-sumes that farmers weigh a number of factors whenconsidering the advisability of incorporating a newtechnology into their farm operation. These include howthe innovations fit within the specific context of their

farm, their own attitudes about social, economic, andpolitical issues, and the attitudes of customers and othersin their social and business networks. In other words,while we accept that farmer access to knowledge aboutGMOs does influence a decision to adopt that technology(Napier et al., 2004b), we also accept that farmers areaware of the power agri-food systems have in the mar-ketplace (Wilkinson, 2000) and that they share ideasabout their evaluations with other individuals within thecontext of social networks. Thus, our aim is to investi-gate how farmers’ expressed willingness to use a con-troversial technology on their farms can be influenced bya mixture of their personal characteristics, social net-works, and political-economic structures.

Such an analysis of farmer interest in emerging GMOtechnologies offers great potential for examining howthese factors shape and are shaped by the choices indi-viduals have to make. GMO technology is indeed con-troversial, but the discussions among farmers on itspotential risks and benefits cover a wider range of fac-tors. For example, farmers must weigh business aspectsof the technology such as possible effects on markets andproduction costs with the environmental benefits andrisks that could affect the long-term viability of theirfarms. This is particularly true for organic farmers(Wilson et al., 2003). Given the complexity of the issuessurrounding GMO technology and the expectation thatfarmers’ analyses of these issues will evolve withincompeting social contexts, it is reasonable to hypothesizethat producers’ views about whether to adopt suchtechnology reflect how they weigh perceived risks andbenefits with their position in the agri-food system.

In other words, we develop an analytical strategy inthis paper that classifies farmers according to their statedinterest in using or not using GMOs and then investigatehow this attitude is influenced by farmers’ structuralpositions in the marketplace and social networks as wellas by more traditional indicators such as educational le-vel and size of farming operation. This will help usdemonstrate how structural factors, social context, andindividual characteristics interact and influence a farm-er’s interest in using GMO technology. By doing this, wedevelop a more nuanced explanation of the heterogeneityof Washington farmers’ willingness to use this technol-ogy as well as their view of their roles in agri-foodsystems.

Data and methods

The data analyzed in this paper were collected in a sur-vey of agricultural producers throughout WashingtonState. A sample was drawn from a list of agriculturalproperty owners that is maintained by the NationalAgricultural Statistics Service. A minimum of 10% of all


agricultural property owners in each county in the statewas selected to receive a survey. Four counties (King,Skagit, Chelan, and Grant) were over-sampled, so that300 farm owners were sampled in each of those counties.This was because the project team was particularlyinterested in analyzing differences across specific regionsof the state.

Questionnaires were sent out to 3718 addresses onMarch 29, 2002. Dillman’s (2000) Tailored DesignMethod for mail surveys was followed.2 A reminder postcard was sent on April 12th, and a follow-up mailing wassent to non-respondents on April 26th. To maximize re-turn rates, particularly from producers who may havebeen too busy with farm tasks in spring and summer, athird mailing was sent to non-respondents on November13th. One thousand twenty-six completed questionnaireswere received although, due to refusals to answer specificquestions, not all of these questionnaires were used in ouranalysis. The sample was adjusted by removing respon-dents who indicated that they sold less than $1000 ofcommodities in 2001 and by removing cases where thepotential respondent had moved, passed away, or re-ceived more than one survey. Some farmers receivedmore than one survey because they owned more than oneregistered agricultural policy. After these adjustmentswere made, the final completion rate was 49.4%.

Given that a county based stratified sampling designwas used and that the ratio of farms in each county to allfarms in the state is different for each county, we used aweighted approach to adjust the mean for eachvariable of interest. The weights were computed asYi = (Ni/N*39) where Ni is the number of farmers in icounty and N is the total number of farms in all 39counties. These weights were used to compute the three-way tables presented in this paper.

Data analysis

Variables

The focus of the analysis presented in this article is avariable from our survey that reflects farmers’ mostlyhypothetical interest in using genetically modifiedorganisms (GMOs). Currently, the dominant GMO cropsin the United States are corn, soybeans, and cotton(Schurman and Kelso, 2003), none of which are grown insignificant quantities in Washington. A GMO option doesexist for potatoes, although it is not being used widely.There had been discussion about a GMO wheat option,but early in 2004 Monsanto pulled a GMO wheat varietyfrom the federal regulatory process. This means that fewWashington farmers currently use GMO technology ontheir farms, but there is a great deal of discussion infarming circles about the potential merits and risks of this

technology. There is also an active desire on the part offarmers, researchers, policy makers, and activists togauge farmer interest in GMO technology.

Thus, our analysis dissects response patterns to thestatement, ‘‘If a genetically modified crop were availablein one of my commodity areas, I would be willing to tryit.’’ Responses to this statement varied along a five-pointLikert Scale ranging from ‘‘strongly disagree’’ to‘‘strongly agree.’’ Of the 904 individuals whose re-sponses are analyzed, 15.3% strongly disagreed with thestatement; 10.2% disagreed; 32.7% neither agreed nordisagreed; 25.3% agreed, and 16.5% strongly agreed. Inother words, nearly half of our producer respondentsexpressed a willingness to try GMOs on their farmingoperations with another third not being sure what theirchoice would be.

As noted above, the primary goal of our study was toanalyze how a farmer’s individual characteristics andposition within the agri-food system might explain thedegree to which s/he3 was willing to try a GMO crop inthe future. Selecting specific variables to reflect thesefactors is not easy. For example, formal educationalattainment is frequently seen as an individual character-istic that reflects the ability of an individual to understandthe science behind a new technology like GMOs and thusis seen as correlated with a greater acceptance of the riskof using that technology (Napier et al., 2004a). At thesame time, sociologists have often viewed educationalexperiences as part of the socialization process, and lifeat a college or university can be interpreted as an exercisein building social networks with mentors and peers.Similar arguments can be made for other variablesthought to reflect individual characteristics, influence ofsocial networks, and position within social structures.Recognizing this problem, we attempted to select vari-ables that are generally acknowledged as indicating oneor another of these factors, while recognizing the need toavoid reductionist interpretations of the results.

Therefore, we constructed nine dichotomous variablesthat reflected aspects of a farmer’s background, socialnetworks, and market position for use as independentvariables in our analysis. One pair of variables indicatedwhether the respondent had farm gate receipts of lessthan $25,000 (55% of sample) or in excess of $100,000the previous year (35% of sample). We believed thisvariable would provide a better indicator of size ofoperation than acreage, particularly in Washington Statewhere acres managed reflect the type of commoditiesproduced as much as it does size of operation. Size offarming operation generally is thought to be an indicatorof the degree of sophistication of the farm operation aswell as the manager. It, therefore, can be associated witha greater willingness to use new technologies.

Another variable we used indicated whether the farmerwho responded to our survey had completed a four-year


post-secondary course of study (47%). Education isfrequently used in technology studies and generally isassumed to reflect knowledge about science and tech-nology, correlating with a willingness to use new tech-nologies. We also utilized a variable that indicatedwhether a respondent’s parents had farmed during anypart of his/her childhood (72%). We hypothesized thatmore familiarity with farming, especially from child-hood, would be associated with greater knowledge aboutfarming and thus a greater willingness to see the potentialbenefits of GMOs.

As measures of a farmer’s position in the market, weincluded two dichotomous variables that reflectedwhether the farmer managed or was about to beginmanaging any land under organic production andwhether the farmer engaged in any direct marketingactivities. Just over 21% of the farmers in our sampledid any organic farming, whereas more than 12% usedone or more direct marketing strategies for makingmore than half of their commodity sales. Organicfarming and direct marketing are two increasinglypopular strategies, especially for smaller farmers whoare finding it difficult to sustain their farms economi-cally in increasingly industrialized agri-food systems.These two variables also can be viewed as reflectingfarmer networks, as one attraction of these strategies isthat they offer farmers increased opportunities to inter-act directly with consumers and to respond moreeffectively to consumer demands. Regardless of thereason, we hypothesized that these two variables wouldbe associated with a greater unwillingness to use GMOsbecause consumers in these networks are more likely toview GMO foods as being unacceptably risky and toconvey these views to producers.

We also utilized measures of whether there had re-cently been any direct contact between the farmer andcooperative extension personnel (34% of the respon-dents) and between the respondent and other farmers(75% of the respondents). We believed these variableswould be associated with a greater willingness to useGMOs because farmers would be exposed to greaterknowledge about biotechnology through contacts withother farmers and representatives of the university wherebiotechnology research takes place. Such contacts alsomight reflect a structural means for promoting GMO use.Finally, we utilized a variable that reflected whetherfarmers had ever had a non-farm job experience. This, weassumed, served as an important avenue for exposingfarmers to non-farm social networks and experiences.Nearly 76% of the farmers in our sample had had aprevious, non-farm job experience, which, we assumed,would be associated with a greater reluctance to useGMOs. We assumed that non-farm work experiencesmeant that these individuals had comparatively moreexposure to non-agricultural social networks whose

members were more likely to have concerns about theuse of biotechnology in agricultural production.

Analysis

To assess which of these variables were most instru-mental in explaining differences between farmers in theirexpressed willingness to try GMO technology, we per-formed an ordinal logistic regression analysis with thewillingness to try GMOs as the dependent variable. Theresults of this analysis indicated that four of the ninevariables we had selected were significantly associatedwith the variation in willingness to try GMOs. These fourvariables were (1) whether a respondent had farm gatereceipts of more than $99,999 in the previous year; (2)whether the respondent had completed 4 years of post-secondary education; (3) whether the respondent had anynon-farm work experiences; and (4) whether therespondent managed any organic production.4

Before analyzing the relationship between these vari-ables and the willingness to try GMOs in more detail, wewould like to emphasize that our two measures of whe-ther farmers obtain information about farming practicesfrom other farmers and/or from extension personnel werenot associated with differences in farmers’ attitudes aboutGMOs. While some researchers have noted that socialnetworks influence the decisions of group members toadopt an innovation (Valente, 1995; Strang and Soule,1998), we found that where Washington farmers obtainedinformation – from other farmers or from cooperativeextension – did not explain variations in their interest inusing GMO technology. We do not interpret this result asan indication that these networks are not important butrather that there may be a diversity of opinion with re-gards to the advisability of using GMOs among otherfarmers and cooperative extension personnel, just asthere is among those who participated in our survey.

The variable we used to measure whether an operatorever had a non-farm work experience prior to farmingwas significantly associated with interest in GMOs. Thedata in Table 1 show that farmers with non-farm workexperiences were less likely than farmers with high grossreceipts or a college degree to express a willingness touse GMOs. This supports the results of French researchthat showed previous non-farm work experiences asso-ciated with untraditional farm decision-making (Gilg andBattershill, 1999). Also, research in the United States hasindicated that operators who adopt organic farming haveless farming experience and are more likely to have ur-ban backgrounds (Duram, 1990; Lockeretz, 1997). Inother words, exposure to non-farm experiences and lifein an urban environment may expose farmers to differentpeople and ideas as well as give them insights into urbanfood consumption patterns. Thus, farmers who have hadnon-farm work experience may not be more likely than


other farmers to see the use of GMOs as risky but may beconcerned about how consumers will perceive the use ofGMOs in agricultural products.

The variable that best explained a reluctance to useGMOs was whether the respondent was using, or plannedto use, organic farming practices. The data show thatnearly half of all the organic farmers were unwilling to tryGMOs, with another one-third being unsure. This is notsurprising given that organic producers are resisting at-tempts to allow the use of GMO technology in organicproduction systems, though their reasons for doing so mayhave more to do with concern over consumer acceptancethan with any opposition to the GMO technology itself.

The two variables that were associated with a greaterwillingness to try GMOs were whether the respondenthad a college degree and whether the farm operationgrossed more than $100,000 per year in sales, with overhalf of these large farm operators expressing a willingnessto try this technology on their farms. Such results fit theconventional argument for explaining farmer attitudestowards new technologies – farmers who operate largefarms and who have advanced formal education are morelikely to have a progressive attitude toward new tech-nologies because they have a better understanding of howthey will benefit economically from such technologies.

As we noted above, level of educational achievementcan be interpreted as a reflection of how a person hasbeen socialized as well as an indicator of the knowledgea person may have about science and technology. Wealso recognized that farmers in our sample who hadcompleted college were more likely to try GMOs thannot. However, it is important to note that nearly one-thirdof the college graduates expressed a neutral position andthat less than half of the college educated farmers saidthat they would be willing to try GMOs. For these rea-sons, we examined the relationship between educationand willingness to use GMOs in further detail by con-trolling for whether the respondent engaged in organicfarming (Table 2). We chose to use organic farming be-cause it was the variable most strongly associated with anunwillingness to use GMOs. The data presented in Ta-ble 2 reveal that the relationship between education andwillingness to use GMOs is flipped depending on whe-ther the farmer engages in organic production. More thanhalf of all Washington farmers who do not engage in any

organic farming and who have completed a collegeeducation expressed an interest in trying GMOs, whilenearly half of organic farmers with a college educationwould not try GMOs.

Analysis of our data indicated that a far greater per-centage of organic farmers in our survey engaged in di-rect marketing than other farmers (28% vs. 16%).Anecdotes that we collected from our interaction with avariety of farmers from across the state further suggeststhat small-scale, organic farmers who engage in directmarketing are often college graduates but not in tradi-tional agricultural disciplines. Given that a strong cor-relation between these two variables may have masked arelationship between direct marketing and interest inGMOs in our multivariate analysis, we decided to con-struct an additional three-way table of the relationshipbetween education and interest in using GMOs, this timecontrolling for use of direct marketing for more than halfof the farm’s retail sales (Table 3). Among farmers whodo not engage in direct marketing, approximately halfwith college degrees expressed an interest in tryingGMOs, while less than 40% of those with less than acollege education were willing to do so. This relationshipbetween education and willingness to try GMOs forthose who do not engage in direct marketing was stillsignificant even after weighting the sample. However,among respondents who utilize a direct marketing strat-egy the relationship no longer exists, with a little morethan one-third of those who graduated from collegeexpressing an interest in trying GMOs. In other words,the relationship between formal education and interest inGMOs is different for farmers who do not engage indirect marketing than for those who do. Clearly theinfluence of education in helping farmers make decisionsabout new technologies varies depending on how they fitwithin the agri-food system.

The association between level of formal educationand farmer interest in using GMOs clearly is not linear.In the case of more conventional farmers who do notuse direct marketing and who do not farm organically, acollege education is associated with a greater willing-ness to try GMO technology. However, among farmerswho are trying alternative marketing strategies andproduction practices, having more formal educationis not associated with a greater interest in trying

Table 1. Willingness to adopt GMOs by key variables.

Strongly

agree (%)

Disagree

(%)

Neither

(%)

Agree

(%)

Strongly

agree (%)

Had a non-farm job experience (N = 686) 16.47 11.22 33.24 24.34 14.72

Engages in some organic farming (N = 192) 27.08 13.02 29.69 19.27 10.94Has college degree or higher (N = 429) 15.62 9.09 29.60 27.04 18.65Had receipts>$100 K Previous year (N = 316) 10.76 6.33 28.80 31.65 22.47

All survey respondents (N = 904) 15.27 10.18 32.74 25.33 16.48


Table 2. Interest in trying GMOs by education and use of organic farming practices.

No College Degree College or Higher Degree

Farmers who do not engage in anyorganic farmingWould try GMOs 153 167Column percentage (39.5%) (51.4%)

Adjusted column percentage {43.7%} {53.4%}Undecided about GMOs 146 93Column percentage (37.7%) (28.6%)

Adjusted column percentage {33.9%} {28.5%}Would not try GMOs 88 65Column percentage (22.7%) (20.0%)

Adjusted column percentage {22.3%} {18.1%}Total observed N = 717{Weighted v2 = 6.6196}{P = 0.0837}

Farmers who do engage in anyorganic farmingWould try GMOs 29 41Column percentage (33.0%) (27.9%)

Adjusted column percentage {32.0%} {27.6%}Undecided about GMOs 23 34Column percentage (26.1%) (32.7%)

Adjusted column percentage {26.9%} {39.5%}Would not try GMOs 36 41Column Percentage (40.9%) (39.4%)

Adjusted Column Percentage {41.1%} {33.0%}Total Observed N = 192{Weighted v2 = 3.3825} {P = 0.3036}

Table 3. Interest in trying GMOs by education and use of direct marketing.

No College Degree College or Higher Degree

Farmers who do not engage primarily in directmarketingWould try GMOs 161 174Column percentage (37.0%) (49.0%)Adjusted column percentage {40.8%} {50.5%}

Undecided about GMOs 160 106

Column percentage (36.8%) (29.9%)Adjusted column percentage {33.6%} {31.3%}

Would not try GMOs 114 75


Total Observed N = 790

{Weighted v2 = 9.2653} {P = 0.0325}Farmers who do engage primarily in directmarketingWould try GMOs 21 22


Undecided about GMOs 9 21


Would not try GMOs 10 31


Total Observed N = 114

{Weighted v2 = 9.1963} {P = 0.0284}


genetically modified organisms. While we do not haveany further empirical evidence to explain this relation-ship, we now believe that our analysis could have beenimproved had we asked respondents where and howthey were educated after high school. We wouldhypothesize that conventional farmers with a collegeeducation are not only more likely to be willing to tryGMOs, but also more likely to have graduated from atraditional course of agricultural study at the state’sland-grant university, while by contrast, farmers with acollege education who sell organic produce directly toconsumers are more likely to be trained in non-tradi-tional majors, including agro-ecology.

Of course, it is important to remember that the use oforganic farming practices is associated with a greaterunwillingness to try GMO technology, independent oflevel of education. This confirms for us the importance ofincorporating an awareness of the structural position offarmers in the agri-food system when interpreting theirinterest in controversial technologies. Farmers who areutilizing alternative marketing strategies may be morehesitant to use GMOs, not simply because of a lack ofknowledge or unique values but because of a concernover losing customers who do express such concerns. Inaddition, we presume that farmers’ values are shapedthrough their interaction with people in various networksand institutions.

Conclusions and implications

Agricultural social scientists are becoming more cogni-zant of the need to evaluate how individual assessmentsof new technologies can be affected by structural con-ditions and participation in social networks as well as byfarmer assessments of the potential risks and benefitsassociated with using a technology on their farms. Ourstudy has sought to contribute to this by investigating afew of the factors that may be influencing farmers’interest in GMO technology in Washington State. Ofcourse, for a variety of reasons, generalizations based onour findings should be made with caution. One reason isthat the GMO option is not yet available to most of thefarmers we surveyed. Their evaluation of the potentialvalue of a GMO option could change if the technologybecomes available. Second, we do not claim to haveisolated all of the possible factors that could be influ-encing our farmers’ thinking about the possible use ofGMOs. We recognize that the situation is undoubtedlymore complex than our analysis suggests. Finally, ourdependent variable measured interest in using GMOs, notthe respondent’s knowledge of the technology or theethics associated with GMO use. Thus, we can onlyclaim to have dissected one aspect of farmer thinkingabout a very complex issue.

Nonetheless, our analysis of farmers’ interest inincorporating GMOs into their farm operations can yielduseful insights into the heterogeneity of farmer thinkingabout controversial agricultural technologies. Ourbreakdown of Washington farmers’ perceived willing-ness or unwillingness to use GMOs indicates that farmerinterest in a specific technology cannot be understoodsimply by differentiating farmers along a continuumbased either on their personal characteristics or theirposition within political-economic structures. We havediscovered that farmer interest in trying GMOs is a resultof complex thought processes wherein farmers weightheir personal assessment of the technology against theassessments of other actors in networks in which theyparticipate. Thus, farmers who have had advanced, for-mal academic training and who are innovators in terms ofdirect marketing or organic production strategies are lessenamored with the idea of using GMO technology thanother highly educated farmers. This means that farmersconstruct shared attitudes about technologies and farmmanagement practices as a result of their interactionswith other social actors. Future research should investi-gate in greater depth how social networks and marketstructures can create a context within which farmers re-ceive knowledge about and evaluate new technologiesand farming practices.

Indeed, as farmer backgrounds and consumer demandsbecome more diversified, the number and influence ofsocial networks will probably grow. Although we did notdirectly assess the effects of social networks in our study,it could be that the influence of these networks in influ-encing farmers’ interest in new technologies is growingand may be helping to shape the formation of otherattitudes as well. Certainly, research in the Actor-Net-work tradition supports the contention that consumers arehaving an increasingly important impact on the way inwhich agri-food systems are evolving (Goodman, 2002).Thus, despite the debate about whether agricultural bio-technology has the potential for promoting more envi-ronmentally and economically sustainable agriculturalproduction systems (Pretty, 2002), the organic farmingmovement remains opposed to the on-farm use of GMOtechnology. It is likely that this opposition is due in partto a fear of alienating consumers and other actors in theorganic sector. It is also likely that the concerns con-sumers and other actors in agri-food networks have aboutagricultural biotechnology will continue to influencefarmer options for adopting such innovations.

Certainly, further research also will need to investigatehow conflicting evaluations of agricultural biotechnologywill be negotiated by agro-food system actors and how thisprocesswill affect research and development trajectories inthe public and private sectors. A study of the networkingprocesses surrounding technologies like GMOs, similar tothat conducted by Coughenour and Chamala (2000) on


conservation practices, would be beneficial if it examinedtheways inwhich conflicting interests and critical attitudestoward technology become expressed in particular groupswithin these networks. Such approaches could be partic-ularly fruitful if they were applied to key social events suchasMonsanto’s recent decision to pull GMOwheat from theregulatory process.

From a practical standpoint, our study suggests thatinstitutions that have had a tendency to view themselvesas promoters of social change such as land grant uni-versities need to become more aware of the diversity ofopinions regarding new technologies. Certainly, manyindividuals in agencies like cooperative extension havebegun to move beyond the simplistic educational modelsassociated with traditional extension programs – modelsthat emphasize the dissemination of new technologiesdeveloped by experts. There is a growing recognition thatconsumers, much like the farmers in our study, filter theknowledge they receive through their many perceptionsof self, risk, and potential cost and benefit (Gordon,2002), perceptions that are undoubtedly shaped by socialnetworks and structures. Consequently, consumersincreasingly wish to be considered partners in thelearning process and share in the goal of improving thequality of life of rural communities (Kelsey, 2002). Notonly are farmers one of the interest groups of the agri-food system, but our research shows that farmers rec-ognize the importance of understanding the views ofother actors in the system – including consumers – asthey contemplate which new technologies to use on theirfarms. Policy makers, scientists, and business leaders inthe agri-food system should consider taking a similarapproach, adopting models for collaborating with andincorporating diverse public input into strategic planningin the area of science and technology development.

Acknowledgements

The authors wish to acknowledge the funding contribu-tions of the W. K. Kellogg Foundation, the Farming andthe Environment Project and the USDA-NRI.

Notes

1. Actor-Network Theory was originally developed in the early1980s by John Law (1987), Michel Callon (1986), andBruno Latour (1987). It attempts to understand the complexprocess of technological development and innovation byanalyzing actor-networks constituted by both human andnon-human actors. For more detailed information see Law(1994).

2. The Tailored Design Method is based on Social ExchangeTheory and recommends that surveys be designed in such a

way as to spark interest in respondents and make it easy forrespondents to participate. Thus, for example, this methodrecommends multiple contacts with the potential respon-dents to improve the response rates, the design of arespondent-friendly questionnaire, and the personalization ofcorrespondence.

3. The gender composition of the survey respondents was:84.1% male (N = 990) and 15.9% female (N = 187).

4. These four variables were significant at a level of P> .05 orbetter. Readers interested in viewing the complete results ofthis analysis should contact the authors at [email protected].

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