Public Understanding of Science

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The cultural authority of science: Public trust and acceptance of organized science Gordon Gauchat Public Understanding of Science published online 27 May 2010 DOI: 10.1177/0963662510365246 The online version of this article can be found at: http://pus.sagepub.com/content/early/2010/05/11/0963662510365246

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Public Understanding of Science OnlineFirst, published on May 27, 2010 as doi:10.1177/0963662510365246 Sage Publications (www.sagepublications.com)

Public Understanding of Science

Public Understand. Sci. (2010) 1–20

The cultural authority of science: Public trust and acceptance of organized science Gordon Gauchat

Using the National Science Foundation’s 2006 Science Indicators Survey, this study explores three distinct explanations of public attitudes. First, the knowledge–attitudes model refers to a well tested relationship between public knowledge of science and more favorable attitudes toward science. Second, the alienation model hypothesizes that public disassociation with science is a symptom of a general disenchantment with late modernity, mainly, the limitations associated with codified expertise, rational bureaucracy, and institutional authority. A third approach emphasizes the cultural meaning of science: how various public beliefs about “what science is” relate to acceptance or reservations about science. The Science Indicators Survey shows that US adults view science (what it is or should be) in three distinct ways: 1) in terms of having a systematic method, 2) in terms of social location (i.e., takes place in a university or a laboratory), and 3) in terms of knowledge that should accord with commonsense and tradition. The findings in this study indicate that the knowledge–attitudes, alienation, and cultural meanings models are all valuable for understanding the cultural authority of science. However, the strength of these explanations depends on the type of attitude analyzed. Keywords: attitudes toward science, cultural authority of science, cultural meaning of science, legitimacy problem, public understanding of science 1. Introduction In 2009 the National Science Foundation (NSF) launched the “Year of Science,” a nationwide program to advance “public understanding of science” in the USA. The NSF’s interest in advancing “public understanding” elicits questions about the social boundaries between the public, expert knowledge, and organized science that researchers have yet to fully resolve. Certainly, modern institutions increasingly rely on scientific and expert knowledge to do work, to identify risk, to make decisions, and to establish legitimacy, all of which signify the cultural authority of science (Shapin, 2008). However, there is increasing doubt among many scholars and scientific organizations that the public is sufficiently engaged with scientists and scientific knowledge (Allum et al., 2008; Collins and Evans, 2007;

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ISSN 0963-6625 DOI: 10.1177/0963662510365246


2 Public Understanding of Science

Merton, 1973b; Miller, 2004; Moore, 2008; National Science Board, 2008; Shapin, 2008). In short, many scholars and policy makers fear that public trust in organized science has declined or remains inadequate. Recent public opinion data affirm a cultural gap between scientists and the public. A 2009 Pew Research Center report indicates that 49% of adults in the United States agree that human activity is producing global climate change compared to 84% of scientists.1 The report also shows similar public skepticism about human evolution. 31% of US adults feel that humans “existed in their present form since the beginning of time” whereas only 2% of scientists agree with this statement. This same report also indicates that 17% of the public believes that the US scientific achievements are the best in the world, compared to 49% of scientists. Only a decade ago 47% of adults identified science/medicine/technology as the greatest achievement of the last 50 years, in 2009 this dropped to 27%. Similarly, the NSF’s 2006–2008 Science Indicators Survey indicates that 47% of US adults feel that science “changes life too fast.” 38% of American adults believe that science “is too concerned with theory and speculation.” Moreover, less than a majority (48%) of American adults feel that the “benefits of science strongly outweigh the harms.” Although some of these trends are unique to the US, other advanced societies show similar levels of disenchantment with science. Yet, there is some doubt about the growth of this cultural distance over time. The General Social Survey (GSS) shows that in the ten-year period 1973–1983 62% of American adults had “hardly any” or “only some” confidence in the scientific community. In 1998–2008, 57% of respondents felt this way, indicating that confidence in science has increased slightly in the US but that less than half of adults express “a great deal” of confidence. In the US, science’s legitimacy problem has yet to penetrate sociology’s premier journals, and remains understudied and under-theorized. The legitimacy problem specifically refers to declining public trust in the political and cultural role of scientists and a general disenchantment with the potential of science and technology to identify and solve society’s fundamental challenges. That is, the public no longer looks to scientists and scientific knowledge to provide a set of values that would improve everyday life, enlighten political perspectives, or address moral issues (Collins and Evans, 2007; Moore, 2008). Public opinion research in Europe and the US has pointed to the relationship between knowledge of science or “science literacy” and attitudes toward organized science, arguing that public ignorance/ambivalence undermines public trust in organized science (Allum et al., 2008; Bauer et al., 2007; Evans and Durant, 1995; Hayes and Tariq, 2000; Miller, 2004). A second approach, drawing from social theorists such as Beck, Giddens and Habermas, proposes that public disassociation with science is a symptom of a general disenchantment with late modernity, mainly, the limitations associated with codified expertise, rational bureaucracy, and institutional authority (Beck, 1992; Giddens, 1991; Habermas, 1989; Yearley, 2000; see also Inglehart, 1990 for a similar thesis). A third explanation that has received far less theoretical and empirical attention relates to the “meaning of science” in society (Bauer et al., 2000, 2007). This approach, developed further in this paper, emphasizes cultural representations and public definitions of “science” (aside from their evaluative component), and how these various public meanings relate to acceptance or reservations about science. The analysis in this article indicates that US adults view science (what it is or should be) in three distinct ways: 1) in terms of having a systematic method, 2) in terms of social location (i.e., takes place in a university or a laboratory), and 3) in terms of knowledge that should accord with commonsense and tradition. Using the 2006 Science Indicators Survey, which was retooled and incorporated into the General Social Survey (GSS), this study explores these three explanations of the legitimacy


Gauchat: The cultural authority of science 3

problem alongside each other. The sections below describe each of the explanatory models in more detail. Knowledge–attitudes model As Allum et al. (2008: 35) argue: “There has been no fiercer debate in the public understanding of science (PUS) than the one that centers on the contested relationship between public opinion and public knowledge about science and technology.” Much of the research on this relationship builds on Jon D. Miller’s (1983, 1987, 1992, 1998, 2004) concept of scientific literacy— a cultural stock of knowledge that includes 1) knowledge of basic textbook science facts, 2) basic knowledge of scientific methods (e.g. experimental design and probability), 3) an appreciation of the social benefits that result from science and technology, and 4) the dismissal of superstition and folk mythologies such as astrology.2 Miller designed survey questions and scales to measure scientific literacy, and many of these instruments have become standard in largescale public opinion surveys in the US and United Kingdom. After 1979, the measurement of scientific literacy became a focal point of the NSF’s biannual Science Indicators Surveys. Research on scientific literacy has generally shown that the US population does not exhibit a high degree of scientific literacy: one estimate suggests that only 17% of the US population is “scientifically literate” (Miller, 2004). Growing out of the “literacy” studies, the PUS program shifted the focus to attitudes toward science and textbook knowledge became the leading explanatory factor (Bauer et al., 2007). Thus, the knowledge–attitudes model refers to a relationship between public knowledge of science (Miller’s scientific literacy) and more favorable attitudes toward science. Yet, the theoretical mechanism driving this empirical relationship remains somewhat unclear. One thesis, what critics have called the “deficit model,” is that an absence of knowledge about basic science facts and methods leads individuals (or social groups) to revert to pre-modern or anti-modern worldviews. These “anti-science” worldviews are characterized by superstition, conspiracy, fear and even hostility toward scientists and organized science (see Holton, 1993). Miller’s ambivalence thesis offers a somewhat more nuanced explanation. Essentially, Miller (1991: 175) argues that “it is likely that few individuals actually possess attitudes toward science.” Consequently, according to Miller’s position the public is not “anti-science” but ambivalent toward it, and the science literacy scale was used to identify those segments of the public who had developed concrete attitudes. Evans and Durant (1995) were among the first to hypothesize and test the association between public knowledge of science and positive attitudes toward science. Their study found weak support for the knowledge–attitudes model while also revealing that scientifically knowledgeable individuals were more likely to disagree with scientists about controversial issues. Sturgis and Allum (2004) also reported a weak relationship between knowledge of science and positive attitudes toward science after controlling for demographic factors. This study was critical of the “deficit model” and showed that knowledge of political issues strengthened the weak positive relationship between public knowledge and positive attitudes toward science. In a meta-analysis of over 200 nationally representative surveys conducted in 40 countries from 1989 to 2003, Allum et al. (2008) found a weak positive correlation between public knowledge of science and favorable attitudes. This sweeping study also showed that the relationship between knowledge and attitudes was limited to general attitudes toward science and did not necessarily extend to attitudes about specific science policies. Nonetheless, Allum et al. acknowledge the theoretical limitations of the knowledge–attitudes model and recommend: “Understanding the social and psychological mechanisms that generate



the associations we observe in this analysis must surely be an important future avenue of research in public understanding of science” (2008: 52). The knowledge–attitudes model has elicited sharp criticism from a number of scholars. The main objection has been that the knowledge–science model presumes organized science offers inherently privileged knowledge (Wynne, 1991, 1995; Yearley, 2000). That is, scientific knowledge is superior to whatever “nonscientific” or “local” knowledge the public may (also) possess. Additionally, there is an implicit assumption that “to know science is to love it,” which appears peculiar given the complexity that likely underlies the relationship (Bauer et al., 2007). An additional weakness relates to the fact that the positive relationship between knowledge and attitudes seems to hold only for “general” attitudes about science, such as science “changes life too fast,” or “is more beneficial than harmful,” but not for attitudes about particular scientific issues like biotechnology, nuclear energy, and stem cells (Allum et al., 2008; Evans and Durant, 1995). Another more deep-seated critique of survey research on PUS suggests that survey researchers have manufactured the “public” or what de Santos (2009) calls “fact-totems”—quantitative measurements that incite alarm and become salient social representations for segments of the population, eventually taking on a life of their own. For some, this viewpoint leads to the conclusion that the concept of the “general public” is irrevocably flawed and that public opinion surveys should be abandoned in favor of ethnographic or “local” approaches (Wynne, 1995). However, focusing on local interactions between scientists and various “publics” might produce the reverse problem of overemphasizing the significance of particular social worlds. Additionally, ethnographic accounts are subject to the performances of “Publics-in-Particular”—that is, activist groups often work carefully to construct their collective identities for various audiences, including ethnographers (see Michael, 2009). Altogether, this critique fails to clearly articulate why survey instruments that are carefully designed and interpreted as fallible are necessarily inferior to alternative methods. A more social psychological interpretation of the knowledge–attitudes model is that “textbook knowledge” of science signifies a cultural disposition or orientation toward science, similar to Bourdieu’s notions of cultural capital and habitus (Bourdieu, 1984).3 From this perspective, textbook knowledge represents a unique cultural experience and a form of cultivation that translates into an appreciation for organized science. This “science habitus” would emerge from exposure to “popular science” (e.g. college courses, popular science magazines, science museums, NOVA), which often presents simplified and professionally idealized representations of scientific work and its benefits (see Gauchat, 2010 for further elaboration of the science habitus). The science habitus would not translate into specialized expertise, but a sort of practical knowledge and/or cultural script for talking about science in everyday life and not knowledge that is applicable to specific scientific issues like biotechnology, climate change, nuclear energy, or stem cells (Collins and Evans, 2007). This interpretation of public understanding of science has some analytical appeal, because it refines the scope of the public knowledge concept and explicitly describes knowledge of science as a “cultural” phenomenon. This interpretation also implies a limit to the explanatory power of the knowledge–attitudes model and leaves theoretical space for other explanations.4 Future theoretical work and research should examine the “science habitus” interpretation in more detail than is possible in this study. Alienation model A far less researched explanation connects unfavorable attitudes toward science with a crisis of modernity and alienation from rational bureaucratic control. The alienation model draws



inspiration from the ideas of prominent social theorists such as Habermas (1989), Beck (1992), and Giddens (1991). To summarize, knowledge economies, complex bureaucracies, and accelerating technological innovation require increased dependence on experts and technocrats. These cultural elites—possessing the power to make “truth claims”—interpret social and cultural events, diagnose and manage risks, and recommend measures to sustain economic growth (Habermas, 1989). Yet, the public feels alienated from scientific experts and institutional authorities because they directly experience the consequences of expert knowledge in the form of risk and uncertainty, but at the same time, are detached from the formal deliberations of scientists and bureaucrats. Habermas concludes that technocratic authority undermines the democratization of modern institutions so that the public sphere becomes increasing alienated from these systems of authority. The key concept for this model is “institutional alienation,” which represents a disassociation, disenchantment or discontent with abstract bureaucratic systems among segments of society. To date, only a few studies have examined the relationship between social, institutional, and political trust and attitudes toward science (for exceptions see Bauer et al., 2000; Grove-White et al., 2000; Priest, 2001; Wynne, 2001). According to the alienation model, the structure and limitations of modernity shape the relationship between science, society and the public. As Merton (1973a) and Habermas (1989) observed, organized science has achieved a cultural and institutional monopoly on the production of credible knowledge, placing it structurally and ideologically at the center of contemporary society.5 Yet, the production of scientific knowledge and the deliberations of bureaucratic authorities remain largely undemocratic and disconnected from people’s lived experiences. This (possibly growing) gap between the influence of abstract bureaucratic systems and scientific experts and the capacity of the public to shape and control these systems engenders institutional alienation. Giddens writes: “Alienating, because the intrusion of abstract systems, especially expert systems, into all aspects of day-to-day life undermines pre-existing forms of local control” (1991: 137). These fairly complex ideas can be translated into the hypothesis that unfavorable attitudes toward science are symptoms of a broader institutional alienation or legitimacy crisis that involve public reservations about expert systems, bureaucratic authority, and political institutions. This association is not necessarily causal. Instead, it describes an interrelationship between institutional alienation and the cultural authority of science that is fundamental to late modern society. Meaning of science model One area that has received little or no attention in public opinion research relates to the public’s definitions of science, or more pointedly, the cultural meaning of science. This is unfortunate because the PUS program employs the “public understanding” terminology, which inevitably brings to mind evaluative attitudes (whether something is good or bad) as well as how the public culturally demarcates science (e.g. what makes something scientific). Yet, this distinction is rarely identified in survey research. One exception is the seminal work of Bauer, Petkova, and Boyadjieva (2000). Their study developed alternative measures of public understanding including “institutional knowledge” and attitudes about the “nature of science.” Institutional knowledge refers to the public image of how science operates and functions as an institution. The “nature of science” refers to public definitions of science and ideas about what demarcates science from other forms of knowledge. Building on the latter idea, the analysis in this study emphasizes the “cultural meanings of science.” This concept acknowledges that the public may have multiple understandings of “what science is” or “what makes something scientific.” For example, a portion of the public might define science as a



systematic and unbiased method. Other groups might distinguish between scientists and other social roles based on their social location and perceived interests—are scientists formally credentialed, are they employed at a university, for example. For the most part, social studies of science have addressed the issue of identifying “what science is” (and thus the cultural meaning of science) with the concept of boundary work. Gieryn (1999: 14) proposes that boundary work is a form of cultural cartography in which science is given “particular (but non-aligned) borders and territories, landmarks and labels, in order to enhance the credibility of one contestant’s claim over those of other authorities.” The concept of credibility has been especially important in post-Mertonian social studies of science. From the boundary work perspective, science is the cultural domain where credible “truth claims” can be made. Research on boundary work has shown that “credibility contests” often boil down to which groups can successfully claim disinterestedness, unbiased methods, and objective knowledge. These attributions of credibility or “disinterestedness”—being less narrowly self-interested than political, business, or religious leaders—are also likely to be salient components of cultural representations of science. Along with ideas about method and social location, these social representations about “what science is” are likely associated with “textbook” knowledge of science and may translate into favorable attitudes. However, these relationships have not been adequately tested nor has previous research adequately identified the cultural meanings of science in society. One limitation has been the lack of datasets that include items related to the “meaning of science” in society: questions that ask respondents about “what makes something scientific.” Thus, analyses of the meaning of science have come from qualitative studies, mostly in the form of case studies (see Wynne, 1995 for a review). As discussed above, one difficulty with drawing general conclusions about the meaning of science in society exclusively from case studies and ethnographies is that these studies often investigate atypical groups. For example, nuclear activists, citizens against genetically modified foods, and local sheep farmers all have unique and often remarkable interactions with organized science compared to the general public. Political science researchers have called these groups “issue publics,” groups or individuals who are directly engaged in a political issue, and have found that these groups are systematically different from the general public (Saris, 2004). Likewise, Michael (2009) develops a useful distinction between Publics-in-Particular (PiPs), localized groups that engage with organized science about a specific topic (e.g. HIV activism); and Publics-inGeneral (PiGs), which refer to larger amorphous groups (even whole societies) that are distinguishable from organized science on some key dimension (e.g. work in occupations unrelated to science). Michael argues that analyzing both PiGs and PiPs presents methodological challenges, but neither should be neglected. As Bauer, Petkova, and Boyadjieva propose, there are a number of issues that survey research could address relating to the cultural meaning of science in society. First, it is likely that there are various meanings of science in society. Public opinion studies could examine what beliefs are prevalent and if and how they overlap. Second, different beliefs about the “nature” of science in society are potentially associated with different attitudes (positive or negative) toward science. Third, central to the PUS research program would be whether there is direct or indirect relationship between the meaning of science and attitudes toward science, or conversely, whether general knowledge of science mediates this “effect.” The data analyzed in this study address each of these questions. Data reduction techniques, discussed below, show that there are three salient cultural meanings of science. The first relates specifically to the methods scientists use to produce knowledge. The second emphasizes the social location of scientists and scientific practices: having advanced credentials in their field, taking place in the university, and taking place in a laboratory. The third social



representation of science sees science as a means to affirm and reinforce traditional and commonsense knowledge. In summary, the literature related to the cultural authority of science emphasizes three models of public attitudes toward science that can be empirically addressed given the available data. The knowledge–attitudes model hypothesizes that public knowledge of science translates into favorable attitudes towards science. The alienation model indicates that significant segments of the public are institutionally alienated and feel detached from abstract bureaucratic systems such as organized science. The meaning of science model explores public views about “what makes something scientific” and examines the relationship between different cultural representations of science and attitudes toward science. The analysis that follows explores four main research questions. 1) Is there an association between textbook knowledge of basic science facts and attitudes toward science after controlling for demographic factors and other explanatory factors? 2) Is there evidence for a relationship between institutional alienation—alienation from modern institutions—and unfavorable attitudes toward science? 3) Does the “meaning of science” in society influence attitudes toward science after controlling for demographic variables and explanatory factors? 4) Based on findings in previous studies, do the explanatory models examined in this study apply to both general attitudes toward science and attitudes about the influence of science and scientists on public policies? 2. Data and measurement The data for this analysis come from the 2006 General Social Survey (GSS), a nationally representative sample of non-institutionalized adults aged 18 and older that is selected using multistage probability sampling. The GSS is funded by the NSF and conducted biannually by the National Opinion Research Center. The 2006 GSS is unique in that it incorporates for the first time many of the items from the NSF’s Science Indicators Survey as a special module in the GSS. Because the Science Indicators is nested within the GSS, it has many advantages over previous versions and includes extensive demographic, economic, and cultural variables along with comprehensive coverage of science-related issues. Attitudes toward science This study analyzes two types of public attitudes toward science: 1) a general attitude toward science and 2) attitudes about specific science controversies. The general attitude is used to approximate overall public trust in and support for organized science: it provides a basic measure of the cultural authority of science in the public sphere. The attitudes related to specific science controversies, on the other hand, capture public trust and support for science in the domain of public policy: these items measure the cultural authority of science in the political sphere. The “general” attitude toward science is measured using a Z-score standardized scale comprised of five questions. The items included in this scale have been used in previous studies to measure a general attitude toward science (Bak, 2001; Pardo and Calvo, 2002; Sturgis and Allum, 2004). For example, respondents were asked if they think science and technology will create “more opportunities for the next generation,” if it “changes life too fast,” and if “on balance, the benefits of scientific research have outweighed the harmful results.” The items in the scale are coded so that higher values represent greater trust in science. A factor analysis using a polychoric correlation matrix indicates that the questions correspond with a latent factor (eigenvalue = 2.11). This factor explains 42% of the total



variance. The Cronbach’s Alpha for the scale is .60, which is below conventional standards but consistent with prior research (see Pardo and Calvo, 2002). To measure public attitudes about specific issues, I examine attitudes about science research in two controversial areas: stem cells and global warming. To measure attitudes toward global warming, respondents were asked how well they think: “environmental scientists understand the causes of global warming” and how much influence “environmental scientists should have in deciding what to do about global warming.” Similarly, respondents were asked how well “medical researchers understand stem cell research” and how much influence “medical researchers should have in deciding about government funding of stem cell research.” Higher values on these items correspond with greater support for science. Knowledge of science To measure public respondents’ “textbook” knowledge of science, this study uses a Z-score standardized scale comprised of 14 factual quiz type questions. This measurement is commonly known as the “Oxford scale” and the items used to construct this scale have been employed in numerous public opinion surveys to measure equivalent concepts (Allum et al., 2008; Durant et al., 1989; Miller, 1998). Respondents are asked about a range of scientific topics and whether they think a statement is “true,” “false,” or that they “don’t know.” Following the standard of previous studies, “don’t know” responses are coded as incorrect answers. The Cronbach’s Alpha for this scale is .73, which is above conventional standards. Social and institutional alienation This study examines two measures of alienation: social alienation and institutional alienation. Social alienation captures respondents’ general disassociation from their social surroundings and discontent with the values of society (Weakliem and Borch, 2006). This measure is an index created from three questions about whether or not people are untrustworthy, unfair, and self-centered. Higher values on the scale correspond with greater alienation.6 The social alienation variable is included to distinguish between the effects of social and institutional alienation, described below. Institutional alienation represents an individual’s lack of confidence or faith in the central institutions of US society (Weakliem and Borch, 2006). The GSS asks respondents whether they have “a great deal,” “only some” or “hardly any” confidence in a range of prominent large bureaucratic institutions such as the branches of the government, financial institutions, and big businesses.7 Higher values on this index reflect higher levels of alienation from the central institutions of society. Factor solutions from a Principal Components Analysis show that the latent construct, “institutional alienation,” is strongly correlated with alienation from the executive branch of government, the army, and big business. This is consistent with Habermas’ (1989) and Giddens’ (1991) notion of alienation from political institutions and rational-legal bureaucracy. The Cronbach’s Alpha for this scale is .75. Meaning of science in society In the 2006 Science Indicators Survey, respondents were asked to say which factors they thought made something scientific. For example, they were asked if they thought it was important that science “is done by scientists employed in a university setting,” “is done by those with advanced degrees in their field,” “involves repeated experiments that find the same



result,” and “examines different interpretations of results.” A total of eight questions were included in the survey. Using a Principal Components Factor Analysis, three factors were obtained from the eight items. The three factors that emerged from the analysis correspond to different public beliefs about “what makes something scientific.” The first factor represents the idea that science is differentiated by its “method.” This belief is consistent with the idea that replication, unbiased interpretations, and solid evidence culturally demarcate science from other ways of knowing. The second factor captures the idea that science is differentiated by its “social location.” According to this factor, science is culturally defined by the credibility of the university setting and professional credentials (i.e. having advanced degrees in a scientific field). The third factor identifies that science should culturally “accord” with other forms of knowledge in society such as commonsense and religious tradition. In other words, some segments of the population believe that science should culturally reinforce other forms of knowledge; however, of the three factors this was the weakest. The three measurements used in this study, method, social location, and accord, were created based on the factor solutions discussed above. Each of the three factors explains 28.1%, 23.7%, and 19.3% of the total variance, respectively; their eigenvalues were each greater than one. An oblique rotation was used to test the null hypothesis of independence between the factors, and the null was rejected indicating that the extracted factors are interrelated (see appendix for results of the factor analysis). These correlations were all less than .30 and the variance inflation factors (VIF) indicated that collinearity was not an issue in the multivariate analysis.8 Respondents were also asked: “to what extent do you think [environmental scientists/ medical researchers/elected leaders/business leaders/religious leaders] would support what is best for the country as a whole versus what serves their own narrow interests?” Interviewers were told to clarify that “narrow interests” meant that “someone might gain financially if a certain policy were adopted or it might advance his or her career.” From these items, two Z-score standardized measures were created: a measure of the perceived disinterestedness of scientists and a measure of the perceived disinterestedness of other prominent social actors (elected officials, business leaders, religious leaders). Then, a measure was created that represents the difference between the disinterestedness of scientists and other social actors (disinterestedness of science - disinterestedness of other social actors). Thus, higher values on this scale indicate that respondents feel scientists are “uniquely disinterested” compared to other prominent social actors and lower values indicate that respondents feel scientists are less disinterested. This measure attempts to capture whether or not respondents feel scientists have “unique motives” compared to other social actors. Additionally, the “disinterested” measure represents the perceived “credibility” of scientists and organized science relative to other major social institutions. Accordingly, public belief in the “disinterestedness” of science should be associated with more favorable attitudes. Controls This study controls for various socio-demographic factors based on previous studies on attitudes toward science. Socio-demographic factors include gender, ethnicity (whether or not a respondent is nonwhite), years of schooling, region (south = 1), age, family income, political ideology (conservative = 1), and church attendance. Analytical strategy The goal of this analysis is to describe which variables are associated with public attitudes toward science and examine multiple explanations of these attitudes. The first set of models



estimates those variables associated with the general attitudes toward science scale. The second part of the analysis explores whether or not the three explanatory models mentioned above account for public attitudes related to global warming and stem cell research.9 It is important to note that these models are not theoretically unified nor reductionist explanations of attitudes toward science; they likely operate concurrently among different segments of society. Multivariate statistical techniques are especially useful for examining the independent effects of multiple explanations while controlling for the effects of other explanations, and thus, are ideal for this analysis. 3. Results Analysis of the general attitudes scale Table 1 reports the descriptive statistics and provides a brief description for all of the variables used in the analysis. Table 2 reports the results of four multivariate regression models predicting the general attitudes toward science scale. Model 1 shows the effects only for the sociodemographic factors. This baseline model shows that nonwhites have less favorable attitudes toward science than whites; that years of schooling and family income are associated with more favorable attitudes; and that church attendance is associated with less favorable attitudes.

Table 1. Descriptions of key variables, Science Indicators GSS 2006 Variable General attitudes toward science index Female Nonwhite Education South Age (in decades) Family Income Conservative Church Attendance Knowledge of Science Social Alienation Institutional Alienation Method Location Accord Disinterested

Mean

A general attitude toward science based on 0.036 five questions, Z-score. Range -2.955 to 1.376, a = .58 Whether R is female (yes = 1, no = 0) 0.566 Whether R is nonwhite (yes = 1, no = 0) 0.217 R’s years of schooling. Range 2 to 20 13.756 Whether R lives in the south (yes = 1, no = 0) 0.255 Age of R divided by 10. Range 1.8 to 8.9 4.692 R’s family income in real dollars (year 2000). 75.511 In $1000s. Range 0 to 500 “Think of self as liberal or conservative” 0.356 (conservative = 1) “How often do you attend religious services.” 3.524 Responses “never” (0) to “more than once a week” (8) R’s score on a “textbook” scientific facts quiz. 0.032 Range -1.206 to 0.860. a = .73 Index of three items that measure R’s trust in the -0.043 social values of others. Range –1.295 to 1.152, a = .64 R’s confidence in central social institutions. -0.018 Range -1.559 to 1.526, a = .75 R’s belief that “method” makes something scientific. 0.023 Range -5.189 to 1.019 R’s belief that a “social location” makes something scientific. 0.045 Range -2.943 to 1.398 R’s belief that science should conform with other forms 0.006 of cultural knowledge. Range -2.294 to 2.107 R’s belief that science is disinterested compared to -0.004 other social institutions. Range -2.257 to 3.465


SD 0.642

0.496 0.412 2.818 0.436 1.697 103.592 0.479 2.790 0.453 0.764 0.555 0.933 0.972 1.013 1.048

Gauchat: The cultural authority of science 11 Table 2. Regression models predicting general public trust in science, N =810

Model 1

Model 2

Model 3

Female 0.022 0.065 0.051 (0.017) (0.051) (0.040) Nonwhite -0.240*** -0.127* -0.117* (-0.155) (-0.082) (-0.075) Education 0.048*** 0.022** 0.018* (0.215) (0.098) (0.082) South -0.012 0.000 0.015 (-0.008) (0.000) (0.011) Age -0.013 0.007 0.014 (-0.035) (0.019) (0.037) Family Income 0.001** 0.000* 0.000 (0.091) (0.073) (0.060) Conservative -0.077 -0.076 -0.087* (-0.058) (-0.058) (-0.066) Church Attendance -0.023** -0.018* -0.022** (-0.100) (-0.078) (-0.096) Knowledge of Science 0.415*** 0.422*** (0.291) (0.296) Social Alienation -0.044 (-0.053) Institutional Alienation -0.226*** (-0.197) Method Social Location Accord Disinterested Constant -0.435 -0.251 –0.212 Adj. R2 0.107 0.162 0.204

Model 4 0.021 (0.017) -0.101 (-0.065) 0.013 (0.056) 0.026 (0.018) 0.007 (0.020) 0.000 (0.050) -0.040 (-0.030) -0.013 (-0.058) 0.316*** (0.222) -0.047 (-0.056) -0.229*** (-0.200) 0.117*** (0.171) 0.051* (0.078) -0.047* (-0.076) 0.085*** (0.137) -0.136 0.267

Note: XY-standardized coefficients reported in parentheses. *p < .05; **p < .01; ***p < .001.

This suggests that general attitudes toward science correspond with three salient cultural markers in the US: race, class, and religion. Interestingly, gender is not associated with general attitudes toward science after controlling for the other variables in the baseline model. The standardized coefficients, shown in parentheses, indicate that “class” (education and income), has the strongest influence. However, looking across Table 2 the effects for these variables weaken considerably as the explanatory models are introduced, and are no longer significant in the full model (model 4). This indicates that the predicted differences between the groups in the baseline models are largely explained by the main independent variables. Model 2 adds the knowledge of science variable. As the knowledge–attitudes model would predict, knowledge of science is positively associated with favorable attitudes toward science and this effect is statistically significant at p < .001. In addition, the standardized coefficients show that knowledge of science is the strongest predictor in the model. The addition of the knowledge of science variable reduces the effects of years of education by more than 50%; the effects for nonwhite, church attendance, and family income are also diminished. However, nonwhite, education, family income, and church attendance remain statistically



significant and in the same direction as the baseline model. Thus, the knowledge–attitudes model does not explain all of the observed differences based on race, class, and religion, but is a major factor in explaining “general” attitudes toward science. Model 3 adds the social alienation and institutional alienation measures. The effect for social alienation is negative, suggesting those who are alienated from “others” have negative views about science, but this effect is not statistically significant. The social alienation measure is statistically significant when the institutional alienation variable is not included in model 3 (analysis not shown here). Consistent with the alienation model, the effect of institutional alienation is negative and statistically significant at p < .001, even after controlling for sociodemographic factors and knowledge of science. This indicates that people reporting higher levels of alienation from major social institutions also report more negative attitudes towards science. The standardized coefficients indicate that institutional alienation is the second strongest predictor in the model next to knowledge of science. Also, the effect of knowledge of science is not diminished by the addition of institutional alienation and in fact increases. Thus, the alienation explanation does not detract from the knowledge of science explanation, suggesting that these variables operate largely independently of each other. The effect of family income is no longer significant, and the effects of nonwhite and years of schooling become weaker when the alienation variables are added. Interestingly, the effect for “conservative” becomes statistically significant in model 3 and is negatively associated with the general attitude scale. The effect of church attendance is also increased by the addition of the alienation variables. These results are consistent with literature on the politicizing of science in the US (Mooney, 2009; see also Hofstadter, 1970). However, the effect for conservative is quite small compared to other variables in the model. Model 3 shows that the knowledge–attitudes model and the alienation model together account for most of the differences based on class and race observed in the baseline model, but the differences based on church attendance and political identification are strengthened. Future research should examine the relationship between institutional alienation and general attitudes toward science in more detail.10 Model 4 adds the final set of variables that measure the meaning of science in society. All three of the “meaning of science” variables are significant in this model, even after controlling for knowledge of science and institutional alienation. Believing that science is defined by method, believing that science is defined by social location, and believing that scientists are uniquely disinterested all have positive effects on the general attitude scale. In contrast, believing that science should “accord” with other forms of knowledge such as commonsense and religious authority has a negative effect. Once these beliefs about science variables are included in the model, none of the socio-demographic variables are statistically significant. Focusing on the standardized coefficients, including the “meanings of science” variables in the model reduces the effect of knowledge of science by approximately 16%. The correlations between the knowledge of science measure and the method, social location, accord, and disinterested measures are as follows: 0.300, -0.187, -.412, and .147, respectively. These correlations indicate that knowledge is positively associated with some beliefs about science but antithetical to others. The standardized coefficients also show that, among the meaning of science variables, the effects for the method and disinterested variables have the strongest association with the general attitude scale, while the effects for the social location and accord measures are relatively weak. These results suggest that cultural beliefs about what demarcates science have independent effects on the general attitudes scale net of knowledge. In addition to the models shown here, various interaction effects were tested between knowledge of science and the meanings of science variables (results not shown). Only the interaction effect between knowledge of science and the method variable was statistically significant (p < .001) and the direction of the effect was positive. The interaction effect shows


Gauchat: The cultural authority of science 13 Table 3. Relative frequencies for attitudes about global warming and stem cells

Frequency

Percent

Understand global warming Not at all 38 2 41 3 171 4 191 Very well 365 Total 806

4.60 5.09 21.24 23.73 45.34 100.00

Influence global warming None at all 21 A little 67 A fair amount 317 A great deal 404 Total 809

2.60 8.28 39.18 49.94 100.00

Understand stem cells Not at all 24 2 20 3 117 4 216 Very well 419 Total 796

3.02 2.51 14.70 27.14 52.64 100.00

Influence stem cells None at all 30 A little 90 A fair amount 353 A great deal 328 Total 801

3.75 11.24 44.07 40.95 100.00

that the association between the method orientation and favorable attitudes is strengthened for those with greater knowledge of science. This may suggest a general disposition toward science that consists of both basic knowledge but also beliefs about what “culturally demarcates” organized science. Overall, the results in Table 2 provide strong evidence for each of the explanatory models examined in this study. Theoretically, the strongest model should be the final model with all three explanations (it should have the largest adjusted R2).11 This is confirmed in Table 2; and the adjusted R2 in model 4 represents a 31% increase compared to model 3 and a 150% increase compared to the baseline model. Thus, the knowledge–science model, alienation model, and meaning of science model each contribute to the explanation of general attitudes toward science. According to the standardized coefficients, the knowledge of science and institutional alienation variables have the strongest individual effects on the general attitudes scale. Analysis of attitudes about global warming and stem cell research Table 3 reports the frequency distributions for the four outcome variables relating to global warming and stem cell research. The first outcome measures how well respondents feel that scientists understand global warming, and the second outcome measures how much influence respondents feel scientists should have over global warming policy. Table 3 shows that a majority of Americans feel that environmental scientists understand global warming well,



with 45.3% feeling that the scientists understand it very well. Just under a majority of Americans (49.9%) believe scientists should have a “great deal of influence” over global warming policy. The question wording for the two stem cell items is nearly identical to that about global warming. Table 3 shows that a slight majority of Americans (52.6%) feel that scientists understand stem cells very well. Yet, only 41.0% feel that scientists should have a great deal of influence over stem cell policy and 15.0% of adults feel that science should have little or no influence. The bivariate (polychoric) correlation between the global warming variables is .424, and for the two stem cell variables, it is .382. These positive but relatively weak correlations indicate that the public distinguishes between scientific understanding of a controversy and how much scientists should influence policy decisions related to the controversy. This provides some evidence for the idea the public is “reflexive” about scientific expertise— the public understands that science provides cultural knowledge and understanding vital to public policy decisions, but that this knowledge should not translate directly into political power (Giddens, 1991; Wynne, 1995). Table 4 presents the results of four ordinal logit regression models predicting policy items discussed above. Overall, the results show that the effects of socio-demographic background on the two controversies are very different, but the effects for the explanatory variables are fairly consistent. First, note the politicization of the science issues, especially for global warming attitudes. The effect of being conservative is statistically significant and negative in three of the models in Table 4. This provides further evidence of a strained relationship between political conservatives and organized science (Mooney, 2009). Yet, a broader range of science issues should be examined before drawing strong conclusions. For example, conservatives might have positive attitudes about other science controversies such as nuclear power and genetically modified foods, issues liberals and progressives have opposed. Being female is associated with greater support for science related to global warming, but it does not have significant effect on attitudes about stem cell research. In addition, older respondents are more critical of scientific understanding of global warming; however, the effect of age is not statistically significant in any other models in Table 4. Surprisingly, church attendance is not a particularly strong predictor of attitudes about stem cell research and is only statistically significant for scientists’ understanding of stem cells, although the effect for this variable is negative in three of the four models. Focusing on the main explanatory factors, there are discernable patterns across the different policy issue models. First, knowledge of science is not statistically significant in any of the policy issue models predicting either the global warming or the stem cell research. Additionally, the effect of knowledge of science is negative in the model predicting support for scientific influence on stem cell research policy. This is consistent with other studies of attitudes toward science that have shown that the positive relationship between knowledge of science and positive attitudes toward science is limited to general attitudes (Allum et al., 2008). Institutional alienation has a consistent negative effect on support for organized science related to policy issues. The effect of institutional alienation is statistically significant in three of the four models and is especially pronounced for the stem cell research outcomes. This provides some evidence that the alienation model applies to both general and specific attitudes toward science; however, future research should more rigorously test this hypothesis using a larger number of policy issues. The effects for the meaning of science variables are also fairly consistent. First, the method variable is positive and statistically significant in three of the four policy issue models; however, the standardized coefficients indicate that the effect for this variable is small relative


Gauchat: The cultural authority of science 15 Table 4. Ordinal logit models predicting attitudes about global warming and stem cells

Understand global warming

Influence global warming

Understand stem cells

Influence stem cells

Female Nonwhite Education South Age Family Income Conservative Church Attendance Knowledge of Science Social Alienation Institutional Alienation Method Social Location Accord Disinterested

0.463** (0.113) -0.270 (-0.054) 0.033 (0.045) -0.001 (-0.000) -0.134** (-0.111) 0.001 (0.044) -0.568*** (-0.133) 0.006 (0.008) 0.297 (0.064) -0.109 (-0.041) -0.061 (-0.016) 0.189* (0.085) 0.276*** (0.130) -0.024 (-0.012) 0.547*** (0.270)

0.451** (0.108) -0.087 (-0.017) 0.043 (0.058) -0.092 (-0.019) -0.064 (-0.052) 0.000 (0.010) -0.451** (-0.104) -0.000 (-0.001) 0.068 (0.015) 0.076 (0.028) -0.303* (-0.080) 0.227** (0.101) 0.445*** (0.207) -0.029 (-0.014) 0.608*** (0.297)

0.080 (0.020) -0.195 (-0.039) 0.003 (0.004) -0.071 (-0.015) 0.062 (0.051) 0.001 (0.028) -0.197 (-0.046) -0.060* (-0.082) 0.389 (0.085) 0.137 (0.052) -0.371** (-0.100) 0.181* (0.082) 0.372*** (0.177) -0.164 (-0.082) 0.516*** (0.259)

0.159 (0.038) 0.034 (0.007) 0.028 (0.037) 0.199 (0.042) 0.049 (0.040) -0.000 (-0.012) -0.396* (-0.092) -0.040 (-0.053) -0.344 (-0.074) 0.125 (0.046) -0.468*** (-0.124) 0.077 (0.034) 0.425*** (0.197) -0.042 (-0.021) 0.687*** (0.337)

N Cox and Snell pseudo R2

805 .189

809 .192

796 .170

801 .199

Note: XY-standardized coefficients reported in parentheses. Brant and Wald tests indicate that the parallel regression/proportional odds assumptions are met making ordinal logit an appropriate method for this analysis (Long, 1997). *p < .05; **p < .01; ***p < .001.

to other explanatory variables. In contrast, the social location variable is consistently positive and statistically significant for each of the policy issue outcomes. In addition, the standardized coefficients indicate that this variable has a relatively strong effect for support for organized science in relation to policy issues. This finding is illuminating because it suggests that segments of the public look for salient markers of credibility such as the “university” and credentials rather than call upon their individual stock of knowledge when accessing their support for science on policy issues. The disinterested variable is also positive and statistically significant. The standardized coefficients suggest that this variable has the strongest effect on each of the policy issue attitudes. Similar to the result for social location, the strong effect for the disinterested variable provides further indication that public attributions of scientists, whether they are perceived to be exceptionally “credible” among institutional authorities, are the main factors that explain their support for the influence of organized science on public policies.



To summarize, the results in this study show that there are discernable differences between public attitudes toward science in general and attitudes about policy issues. Yet, there is also some consistency across these attitude types. First, this study adds to a growing body of evidence that the knowledge–attitudes model is only applicable to “general” attitudes toward science, and does not explain attitudes about particular science policies. Second, the findings in this study indicate that the alienation and meaning of science models are actually more robust explanations across the two types of attitudes. One interpretation of these results is that general attitudes toward science are components of a broader cultural disposition toward organized science—a distinctive “worldview” shaped by lived experiences, social interactions, socialization, and cultivation. In contrast, attitudes about specific policy issues related to science have more to do with public perceptions about where credible experts are located in society and the attributes that they are thought to exhibit. As the results above show, concrete ideas and knowledge about where to culturally locate expertise, such as the idea that science takes place in universities, is practiced by those with advanced degrees in their field, and is relatively disinterested, seem to capture elements of cultural “credibility.” According to the results of this study, these are important factors independent of what survey research has commonly conceived of as “understanding” (i.e., textbook knowledge of science facts and methods). Additional empirical studies of the US adult population and other advanced capitalist societies are needed to confirm these conclusions before strong claims can be made. The NSF Science Indicators Survey should, therefore, continue to develop its questionnaire and include a battery of questions relating to public acceptance of science’s influence on social policies as well as questions related to the meaning of science in society. Furthermore, future survey research on public understanding should incorporate and expand the alienation and meaning of science models. 4. Discussion This study offers two important contributions: 1) it incorporates sociological and social psychological explanations of the cultural authority of science, and 2) it illuminates how public opinion research can address a broad set of theoretical questions relating to public trust in organized science. One necessary caveat is that these results are specific to the US; however, it is likely that the main conclusions can be generalized to similar advanced democracies. One key difference may relate to the findings for the policy issues. Given that stem cell research is far less controversial in Europe, it is likely that other policies such as genetically modified foods and nuclear energy are more salient outside of the US. Additionally, higher levels of church attendance and religiosity in the US are likely influencing the results reported here, even if indirectly. Future research should examine the alienation and meanings of science models cross-nationally to assess whether these models depend on the cultural and structural context of the society. Previous research on PUS has frequently framed the relationship between knowledge and attitudes to imply that textbook knowledge is concomitant with certain “cultural representations” or “meanings” that in turn facilitate positive attitudes toward science (Allum et al., 2008; Bauer et al., 2007). This paper shows that cultural representations of organized science are independently associated with favorable attitudes net of knowledge. Yet, it is important to reflect on the larger theoretical and public policy implications of these empirical relationships. First, it is necessary to acknowledge the contentious character of survey research on PUS and that it is improbable that this study will change the strong partisan dynamics surrounding this



issue. Nonetheless, one interpretation of the results of this study is that the knowledge–attitudes debate is outmoded and that future survey research on PUS should explore the idea that textbook knowledge (the Oxford scale), general attitudes, formal experience with organized science, and certain beliefs about the nature of science in society are components of a general cultural disposition or “worldview.” That is, rather than examining the relationships between these variables in multivariate models, it is important to explore data reduction techniques that could identify distinct cultural dispositions toward science using a multidimensional instrument (see Inglehart, 1990). The next step would be to examine the consequences of these various dispositions on economic, political, and life-style variables. Simply, do “public understandings” matter outside of the realm of science policies? An excellent illustration of how this might proceed is Bourdieu’s classic analysis of literary and artistic fields in Distinction. This study made extensive use of survey items similar to those collected in the Science Indicators Survey and related national and international surveys. This perspective would encourage future studies to explore not only the range of general dispositions toward science (e.g. science habitus), but how these dispositions/practices become privileged and imbued with social rewards (e.g. scientific cultural capital). Here the question becomes: do meaningful groups emerge based on dispositions toward science, are these groups socially unequal, and do they correspond to political divisions and distinct life-styles? Given the above discussion, it is important to reflect on the policy implications of this study, and conceptually, to reflect on the idea that public understanding is a salient dimension of social inequality and difference in modern society. First, if we acknowledge that distinct and enduring cultural dispositions toward science are present in modern society, it is essential to explore whether these dispositions reflect other dimensions of social difference such as social class, acculturation, race, ethnicity, religion, and gender. Enduring groups and dispositions would indicate that expanding formal education alone would unlikely fundamentally transform the boundary between organized science and the public and, more importantly, the boundaries between segments of the public. For instance, alienated and underprivileged groups have limited access to formal education, and would possibly resist (adult) education programs if offered. Furthermore, it is unlikely that those in possession of privileged cultural resources relating to science would willingly support, politically or financially, broad based social programs that substantially undermine their advantage. Thus, advanced nations would have to use existing public institutions to ameliorate the social divisions that produce distinct and potentially conflicting cultural representations of science. This would undoubtedly include science education, but in modified form. This alternative approach would have to emphasize the civic, political, and institutional context of science in society. Put another way, public science education should incorporate a pragmatic curriculum informed by social studies of science and PUS research. This would include public education about “where science is culturally located,” “its cultural significance,” and “its consequences (good and bad) for everyday life.” Yet, if the broader social inequalities and institutional arrangements that reproduce and reinforce alienation from organized science remain unaddressed, then public education in any form is unlikely to resolve science’s legitimacy problem. Acknowledgements Special thanks to Tom Gieryn, Harry M. Collins, David Weakliem, and Michael Wallace for their comments and suggestions for this article. I would also like to thank Martin Bauer and the reviewers for their assistance in improving this article.



Notes 1 Gallup polls also report that public doubt about the influence of human activity on climate change is growing (Saad, 2009). 2 Most research on scientific literacy has examined only the first two aspects. 3 Habitus is a complex concept that few social scientists have attempted to measure. However, in its simplest usage habitus refers to a set of acquired patterns of thought, behavior, and taste. These habits or “dispositions” result from the internalization of culture or objective social structures through the experiences of an individual or group. According to Bourdieu, the habitus provides the practical skills and dispositions necessary to navigate different social spaces or fields (such as professional life, art, science, popular science) and guides the choices of the individual without ever being strictly reducible to prescribed/formal rules, beliefs, or values. Emphasis on science habitus would constitute a substantial reorientation of the PUS program. Briefly, a Bourdieuian analysis would presume that public understanding of science was a unique social resource and source of power. Possession of favorable attitudes toward organized science, access to college level science courses, and textbook knowledge of science would represent a form of cultural capital that individuals and groups could convert into social status. This would transform research on PUS into studies of social stratification. Yet, this new program would not necessarily resemble the qualitative research that is currently dominant in the sociology of science; rather, it would also involve quantitative analyses similar to those found in Bourdieu’s own research (see Bourdieu, 1984). 4 There are likely subcultures where alternative habitus develop that are not pro-science. This is consistent with Berger and Luckmann’s (1967) proposal that subculture knowledge, or “worldviews,” are often hostile to competing worldviews. This hostility helps to maintain group specific definitions of reality and the stability of everyday life. 5 Therefore, Habermas emphasizes that science and technology represents an ideology in advanced capitalist society: one that legitimates technocratic welfare-state intervention and abstract bureaucratic control. 6 The social alienation scale is comprised of the following questions. 1) Would you say that most of the time people try to be helpful, or that they are mostly just looking out for themselves? 2) Do you think most people would try to take advantage of you if they got a chance, or would they try to be fair? 3) Generally speaking, would you say that most people can be trusted or that you can’t be too careful in life? A Principal Components Factor Analysis based on a tetrachoric correlation matrix (appropriate for binary variables that approximate a continuous construct) indicates a strong correlation among these three items and that they correlate with a latent variable. 7 On the basis of theoretical and empirical considerations, I selected 10 of the 13 items and created a Z-score standardized index of institutional alienation. A question about the scientific community was removed because of its potentially strong correlation with the outcome variables. Results of a Principal Components Factor Analysis indicated that confidence in television and organized religion did not correspond with the latent factor; these items were removed from the index. Respondents were given the following statement: “I am going to name some institutions in this country. As far as the people running these institutions are concerned, would you say you have a great deal of confidence, only some confidence, or hardly any confidence at all in them?” The following institutions were included in the scale: Banks and financial institutions, Major companies, Education, Executive branch of the federal government, Organized labor, Press, Medicine, US Supreme Court, Congress, Military. 8 For supplementary analysis relating to the meaning of science items contact the author. 9 The models predicting the general science attitudes are estimated using Ordinary Least Squares (OLS) regression. The Ramsey RESET test fails to reject the null hypothesis that the full model in Table 2 has no omitted variables, and the Breusch–Pagan / Cook–Weisberg test also indicates that heteroskedasticity is not a problem in these models. The models predicting attitudes about global warming and stems cells are estimated using Ordinal Logit regression, appropriate for ordinal outcome variables (Long, 1997). 10 For example, in an analysis not shown here I examined the influence of working in large establishments (more than 100 employees) on the general attitude scale and found a weak positive relationship, suggesting that those who work in large bureaucracies have greater trust in science (p < .05). In addition, in a separate analysis limited to employed respondents only, negative workplace attitudes about management and bureaucratic authority were associated with less trust in science (p < .05), suggesting that people’s everyday experiences within bureaucracies influence their general trust in scientific experts. Supplementary analyses are available upon request. The negative workplace attitude scale measures attitudes toward management and workplace authorities and was constructed from six items, a = .85. 11 The adjusted R2 is a model fit statistic that examines the efficiency of each model relative to the other models reported in the table while also penalizing the model that has more parameters (variables).

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Author Gordon Gauchat is a Ph.D. candidate in the Department of Sociology at the University of Connecticut. His primary research areas are in the sociology of science, public understanding of science, and social inequality. His dissertation examines the cultural authority of science in the public sphere. Building on the ideas of Pierre Bourdieu, this project develops the idea of “science habitus,” which refers to a unique and privileged cultural disposition toward science in advanced societies. The project then examines whether “science counts” for a variety of social phenomena such as economic well-being, work conditions and attitudes, life-style, and political values. Preliminary empirical findings suggest that in the US public dispositions toward science represent a key dimension of social inequality and political differentiation. Correspondence: Department of Sociology, University of Connecticut at Storrs, Manchester Hall, 344 Mansfield Road Unit 2068, Storrs, CT 06269-2068, USA; e-mail: [email protected]


Public Understanding of Science

Public Understanding of Science

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