Science to the people: A 32-nation survey

Abstract

In this article, we analyze Special Eurobarometer (2010) data via multilevel regression modeling and answer two questions: (a) How a country’s democratization level is related to the rate of public engagement with science and (b) who are those citizens who participate in science policy-shaping and express their approval for democratic governance of science? Reflexive modernization and institutional alienation perspectives are used to examine those issues. It has been shown that more democratic societies on average have higher rates of public participation in science and support for democratic control of it. Moreover, those well educated and knowledgeable in the topic of science are more likely to engage with science, which supports the reflexive modernization perspective. However, distrust in scientists being considered as an indicator of institutional alienation from science is also crucial in both predicting actual engagement and support for public control over it.

Keywords

institutional alienation multilevel modeling public engagement with science reflexive modernization

1. Introduction

Modern post-industrial societies are characterized by a skeptical and suspicious attitude toward science (Allum et al., 2008: 37; Leiserowitz et al., 2012; Price and Peterson, 2016). This may be regarded as an outcome of constant oppression by global technological and environmental risks that are mainly considered as a logical and inevitable outcome of human-made and human-governed activities (Beck, 1992).

Those risks provoke public demand to review the canonical way of how science should be governed (Scheufele, 2014; Todt, 2011). Traditionally, the “deficit model” of science communication prevailed, where a one-way, top-down flow of knowledge dominated and where lay people used to play a passive role as scientific information recipients (Bucchi, 2008: 57–76). However, the modern world prompts the lay public to reconsider “automatic deference” (Fuller, 2011: 24) to the authority of science in order to make this previously opaque institution more transparent, accountable, and attentive to public opinion on controversial issues.

The recent major increase in the public’s role in scientific agenda shaping and knowledge co-production is well documented (Jasanoff, 2003; Stilgoe et al., 2014). This turn emerged into the concept of “scientific citizenship” which is grounded in the idea of “understanding of citizenship as a dynamic and provisional feature of social and political identity” (Blue and Medlock, 2014: 563). The characteristic feature of scientific citizenship is public participation which is defined by Rowe (2005) as “the practice of involving members of the public in the agenda-setting, decision-making and policy-forming activities of organizations/institutions responsible for policy development” (p. 253). Some researchers also distinguish between horizontal participation, which basically implies awareness of the topic and vertical participation, which accentuates the performative (proactive) aspect of participation (Mejlgaard and Stares, 2013: 662).

The idea of engaging the public in discussions of scientific issues echoes a number of political theories that consider the reasons for including lay citizens in the governance of complex social institutions and making deliberations (Abelson et al., 2003: 241) as a primary mechanism for approaching societal issues that require collective actions.

One of those theories is developed by Barber (2003), who proposed a concept of strong democracy, underscoring the importance of civic engagement into politics as a necessary condition for the community to prosper and opposing it to a thin or classical liberal democracy. Tormey’s (2014, 2015) idea of post-representative democracy develops this discourse of participatory democratic governance. He argues that representative democracy undergoing a legitimacy crisis is now substituted by post-representative mode of governance, in which “disaffiliated activism” (Tormey, 2015), such as horizontally organized protests and demonstrations, plays a crucial role in forming political climate of the state. Moreover, Keane’s (2009a; see also 2009b) concept of monitory democracy also attempts to shed some light on the world of post-representative politics, focusing particularly on how media-saturation of modern societies reshapes such intrinsic aspects of politics as representation, accountability, and participation.

This trend of integration of public opinion into not only political but also scientific agenda-setting and decision-making processes has some indicative evidence. For instance, a Dutch campaign called “Dutch National Research Agenda,” which started in 2015 and continues to date, sets an aim to consolidate research efforts in order to shed light on scientific questions that provoke acute public concern. Those questions cover a wide range of topics starting from human–environment relations and ending up with fundamentals of human existence.¹ Another recent case of public engagement with science is anti-nuclear demonstrations in Switzerland, France, and Germany in 2011, attracting thousands of people and forcing governments yet again to reconsider nuclear policy of the states.² Even closer intertwining of public experience and scientific activity may be found in those projects, where lay people take part in the very production of scientific knowledge. Among those, the most notable examples are SETI@home (Search for Extraterrestrial Intelligence), the University of California, Berkeley initiative utilizing citizens’ personal computers to detect intelligent life outside Earth,³ and the Einstein@home project which is supported by US National Science Foundation using the same principle of distributed computing to detect gravitational waves.⁴

If the trend toward proliferation of a science–public dialogue is hardly refutable, the question What kind of society is more encouraging in developing and maintaining this type of dialogue? We reason, arguing after Welzel et al. (2003), that civic activism in the realm of science, just like any other type of civic activism, should be more widespread in democratic societies where emancipative values prevail, thus proclaiming the supremacy of human choice and a skeptical attitude toward “traditional conformity values” (p. 342).

The second matter still remaining unclear and requiring empirical exploration concerns the characteristics of those individuals engaging with science. We propose to look at this issue under the light of two explanatory mechanisms: one comes from reflexive modernization theory (Beck, 1992; Gauchat, 2011) and argues that those highly educated and familiar with the topic of science and new technologies will constitute the group of individuals who oppose the authority of scientists and thus require more democratic control over science institution. The second mechanism dwells on the concept of institutional alienation (Gauchat, 2008). It stipulates that socially disintegrated people are more likely to possess an anti-science attitude and therefore require personal control over what scientists are doing.

2. Theoretical framework and hypotheses

That the democratization of science seems to be more prevalent in more advanced, democratized countries seems almost tautological. Indeed, in many countries, science policy is moving to a new phase in which “the extended peer community” is demanding a role in the evaluation and the validation of scientific findings (Marres, 2011: 215, see also Lahsen, 2008), and serious efforts are undertaken to democratize science altogether (Fischer, 1993; Jasanoff, 2003; Kleinman, 2000; Middendorf and Busch, 1997). Our first expectation, therefore, is that in countries with higher levels of democratization, levels of public participation in science (A) and levels of public support for democratic control of science (B) are higher (Hypothesis 1).

Yet, finding confirmation for this hypothesis does not answer the question of which social groups actually carry support for this phenomenon in particular. Two sets of diametrically opposing expectations can be put forward.

Public engagement and institutional alienation

The first set of expectations focuses on the lower educated and those in low-skilled professions and their support for democratization of science. This expectation is inspired by theorizing on modernity-induced feelings of cultural malaise or cultural discontents. Building on Srole’s (1956) seminal conceptualization, these feelings of discontents are understood here as feelings threatened by the complexities of the contemporary social and cultural order, which is considered to be fickle, unpredictable, disorderly, and devoid of meaning. It has been demonstrated time and again that the less educated in particular are affected by this type of thinking; they show higher levels of anomie (Achterberg and Houtman, 2009; Lutterman and Middleton, 1970; Roberts and Rokeach, 1956), higher levels of alienation (Blank, 2003), and higher levels of institutional distrust (Achterberg, 2015; De Keere, 2010) than the higher educated.

These feelings of cultural discontents are likely to be accompanied by support for democratization of science. This resonates with Gauchat’s (2011: 755) suggestion that people who suffer from modernity-induced maladies like anomie experience a mismatch between the influence of abstract bureaucratic systems and experts, on one hand, and their own capacity to shape and control these systems, on the other (cf. Achterberg, 2006; Zijderveld, 2000), which leads to them distrusting these institutions. These lower levels of trust in scientific institutions have been suggested to be associated with unconventional scientific activism, namely, efforts among the public at large to engage in knowledge production (Nowotny et al., 2013; Wilson and Willis, 2004).

Indeed, various observations on groups that are commonly understood to be “adversaries of science” suggest that distrust in scientific institutions does actually lead such groups to participate in “scientific efforts” themselves and does not necessarily go together with low trust in scientific principles and methods. Recent research on the so-called conspiracy culture—in which the authority of scientific knowledge as produced by scientific actors is fiercely rejected—demonstrates that conspiracists actively express scientific ambitions: “It is considered a calling to unravel […] mysteries through rational enquiry, by critically looking into every detail that may lead one to the ultimate truth ‘out there’” (Aupers, 2012: 30; cf. Harambam and Aupers, 2015). Similarly, Locke (1999) indicates that “so-called ‘anti-scientists’,” such as creationists,

present descriptions of the world which they attempt to invest with factual status through the use of the rhetoric and practice of empiricism with its passive voice formulations, its emphasis on data, and even, at times, its appeal to laboratory tests and experiment. (p. 86)

And, finally, in a study of ufologists, Eghigian (2017) notes that

It is not the case, however, that most ufologists have been anti-science. On the contrary, their parallel ways of collecting, analyzing, and distributing information were inspired by academic precedents and can be seen as expressions of fondness and respect for science … by and large, their disdain has be reserved for scientists, not science. (p. 622)

In short, if this perspective is correct, we expect that people with low educational levels (A) and those distrusting of science institutions (B) will, on average, have higher levels of public participation in science and levels of public support for democratic control of science (Hypothesis 2). Moreover, this is especially so in the more advanced, fully democratized countries. Hence, we also expect that people living in more democratic nations with low educational levels (A) and those distrusting of science institutions (B) will, on average, have higher levels of public participation in science and levels of public support for democratic control of science (Hypothesis 3).

Public engagement and reflexive modernization

The second set of expectations is derived from reflexive modernization theory (Beck et al., 1994; Makarovs and Achterberg, 2017; Price and Peterson, 2016) and suggests that support for democratization can be found among the higher educated in particular. Whereas non-reflexive accounts of modernization suggest that support for democratic control of science will not increase at all, as trust in science is all encompassing (Inglehart and Welzel, 2005; Lahsen, 2008: 27; cf. Bauer et al., 2007), in the literature on the democratization of science, it is often suggested reflexive-modern motives are underlying support for democratization. It is, for instance, suggested that science needs “acknowledgement with broader contextual, economic, political and other non-technical factors, fundamentally altering the relationship of science to politics and broader society …” (Healy, 1997: 515). Moreover, Hind (2010) argues that

Given the past track record of the patrons of science it is surely time to consider an alternative. If we are serious about science as a public good, we should give the public control over the ways in which some—and I stress “some”—of its money is spent. (pp. 26–27)

It is, hence, because of reflexively modern reasons that people will start to support a democratization of science.

More specifically, reflexive modernization theory provides ample reasons for expecting that the more educated will have more support for democratic control of science in modern, Western countries. The higher educated are arguably better able than their less well-educated counterparts to reflexively approach science and note the failures of the scientific project. As Beck (1992) observes, some members of the public in the most modern countries may have grown to believe that science and technology cannot fully protect people from the various risks they face. In contrast, scientific and technological failures are even held responsible for increased risks (Beck, 1992; cf. Beck et al., 1994).

Moreover, this type of reflexive thinking requires well-developed cognitive abilities, access to scientific information, and a so-called reflexive mind-set (De Keere, 2010), which are also more likely to be found among the better educated. Reflexive modernization theory implies that those high levels of knowledge and cognitive skills found among the more educated (Achterberg et al., 2017; Allum et al., 2008; Norris, 2011) are translated into more debate on science and technology and a stronger support for the democratization of science, which has been proven by recent scholarship (Nisbet et al., 2014).

In short, as the more educated are better informed about scientific institutions than their less educated counterparts, the former might be more supportive of democratic control of scientific research and technological innovations in the first place, and this strongly resonates with political-sociological works on support for democracy and democratic rights, which have, repeatedly, been found among the higher educated (cf. Achterberg and Houtman, 2006; Inglehart, 1997).

Therefore, if this perspective is correct, we expect to find that people with higher educational levels (A) and knowledgeability in the topic of science and technologies (B) will, on average, have higher levels of public participation in science and levels of public support for democratic control of science (Hypothesis 4). And that people living in more democratic nations with higher educational levels (A) and who are more knowledgeable (B) will, on average, have higher levels of public participation in science and levels of public support for democratic control of science (Hypothesis 5).

3. Data, method, and measurements

Data

Special Eurobarometer 73.1/Wave 73.1 (2010)⁵ devoted to the topic of Science and Technology serves as data source for this project. It provides representative information on the 15+-year-old population of 28 countries of the European Union as well as on Turkey, Switzerland, Iceland, and Norway. The data were gathered between 29 January and 25 February 2010, and multi-stage random (probability) sampling was applied. The interviews took place face-to-face in people’s home and in the national language. The data on Great Britain and Northern Ireland are united into the United Kingdom, and Germany East and Germany West into Germany. Initial database contains 31,238 observations, but due to omitting missing analysis is performed on fewer observations.

Method

In order to test our hypotheses, we implement two sets of multilevel logistic regression models with a binary response (Hox, 2002). This allows for testing how both country- and individual-level factors affect the level of actual and expected public engagement with science. Moreover, since Hypotheses 3 and 5 are aimed at testing how the effect of particular first-level predictors on engagement varies across the levels of country’s democratization, we use cross-level interaction to reveal this type of relation (Brambor et al., 2005; Golder, 2003).

Six multilevel regression models are presented in Table 1. Three of them (models 1, 2, and 3) have public engagement with science as a dependent variable and other three (models 4, 5, and 6) deal with support for democratic control of science. Models 1 and 4 are those where only second-level predictor and first-level control variables are included (support for democratic control of science serves as an additional control in models on engagement with science). In models 2 and 5, we add predictors that are derived from our theoretical expectations; interaction terms and random slopes for according first-level variables are added in models 3 and 6, respectively.

Table 1.

Parameter estimates for models on public engagement with science (N = 28,108) and support for democratic control of science (N = 28,262).

Dependent variables
	Engagement with science (binary)			Support for democratic control of science (binary)
	(1)	(2)	(3)	(4)	(5)	(6)
Level 2 variables
Democratization index	0.394***	0.303***	0.438***	0.109**	0.111**	0.062
	(0.077)	(0.079)	(0.113)	(0.052)	(0.049)	(0.060)
Level 1 variables
Controls
Support for democratic control of science (base = little)	0.267***	0.268***	0.269***
	(0.026)	(0.027)	(0.027)
Gender: female	−0.067**	0.072**	0.072**	0.034	0.041	0.045*
	(0.027)	(0.028)	(0.029)	(0.025)	(0.026)	(0.026)
Age	0.003	0.066***	0.070***	−0.045**	−0.046**	−0.045**
	(0.022)	(0.022)	(0.022)	(0.020)	(0.020)	(0.020)
Occupation: Managers (base = self-employed)	0.459***	0.269***	0.255***	0.095*	0.107*	0.107*
	(0.061)	(0.063)	(0.063)	(0.058)	(0.058)	(0.058)
Occupation: other white collars	−0.014	0.032	0.022	0.076	0.082	0.085
	(0.060)	(0.062)	(0.063)	(0.057)	(0.058)	(0.058)
Occupation: manual workers	−0.365***	−0.181***	−0.181***	0.079	0.078	0.078
	(0.056)	(0.058)	(0.058)	(0.052)	(0.053)	(0.053)
Occupation: house persons	−0.521***	−0.310***	−0.317***	−0.082	−0.090	−0.099
	(0.071)	(0.074)	(0.074)	(0.065)	(0.066)	(0.066)
Occupation: unemployed	−0.404***	−0.250***	−0.240***	0.009	−0.005	−0.008
	(0.069)	(0.071)	(0.071)	(0.063)	(0.064)	(0.064)
Occupation: retired	−0.428***	−0.326***	−0.329***	0.005	−0.006	−0.006
	(0.059)	(0.062)	(0.062)	(0.056)	(0.056)	(0.056)
Occupation: students	−0.042	−0.233***	−0.254***	0.033	0.032	0.051
	(0.069)	(0.072)	(0.072)	(0.065)	(0.066)	(0.067)
Parents’ scientific background: no (base = yes)	−0.620***	−0.467***	−0.452***	0.001	0.004	0.007
	(0.032)	(0.033)	(0.033)	(0.030)	(0.030)	(0.030)
Personal scientific background: yes (base = no)	0.517***	0.280***	0.279***	0.020	0.024	0.017
	(0.030)	(0.032)	(0.032)	(0.028)	(0.029)	(0.029)
Independent variables of interest
Years of education		0.083***	0.087***		−0.001	−0.002
		(0.005)	(0.008)		(0.004)	(0.004)
Knowledgeability		0.448***	0.455***		0.032**	0.040**
		(0.015)	(0.019)		(0.013)	(0.018)
Trust in scientists: distrusting (base = trusting)		0.078***	0.079		0.345***	0.352***
		(0.030)	(0.058)		(0.027)	(0.039)
Interaction terms
Democratization level × Years of education			−0.008			0.011***
			(0.007)			(0.004)
Democratization level × Trust in scientists: distrusting			−0.153***			−0.124***
			(0.057)			(0.039)
Democratization level × Knowledgeability			−0.045**			0.014
			(0.018)			(0.017)
Model specifications
Constant	−0.150	−0.948***	−0.998***	−0.086	−0.192**	−0.201**
	(0.097)	(0.106)	(0.131)	(0.074)	(0.080)	(0.082)
Log likelihood	−17,048.680	−16,341.560	−16,278.260	−19,270.670	−19,186.010	−19,156.420
Akaike’s information criterion	34,127.370	32,719.120	32,616.510	38,569.350	38,406.030	38,370.850
Bayesian information criterion	34,251.030	32,867.510	32,863.830	38,684.840	38,546.270	38,610.080
Marginal R² (fixed effects)	.13	.19	.2	.01	.01	.01
Conditional R² (fixed and random effects)^a	.18	.24	.26	.03	.03	.04

Standard errors reported in parentheses.

R² for the mixed models is calculated with Nakagawa and Schielzeth’s (2012) formulas.

p < .1; **p < .05; ***p < .01.

Measures

Public engagement with science

This binary variable indicates whether respondent somehow influenced the decision-making process in the realm of science and new technologies or not. This variable is constituted from the question about the fact of participation in several relevant activities. The question phrasing: “And now, there will be a few questions on how you engage with science and technology. Do you …?” Answer categories: “Attending public meetings or debates about science and technology”; “Signing petitions or joining street demonstrations on matters of nuclear power, biotechnology or the environment”; “Participating in the activities of a non-governmental organization dealing with science- and technology related issues.”

In the dependent variable, “0” stands for those who have not engaged in any form of those three activities presented and “1” for those who have engaged at least in one of them. Non-engaged respondents answered “No, never” for each of the activity presented; on the contrary, engaged respondents answered “Yes, regularly,” “Yes, occasionally,” or “No, hardly ever” for each of them (M = 0.4, standard deviation (SD) = 0.49.

There was also one additional type of activity presented in the question—“Donating money to fundraising campaigns for medical research such as research into cancer.” It was decided to exclude it because of the Cronbach’s alpha value, which measures the consistency of statements. For four of them (on the whole sample), the value was .64, but without this statement it was .71, indicating better fit.

Support for democratic control of science

This variable shows to to what extent respondents consider the public should be involved in the decision-making process in the realm of science and new technologies. This is an ordinal variable with five levels. The question is, “Which of the following public involvement do you think is appropriate when it comes to decisions about science and technology?” The possible answers are as follows:

The public does not need to be involved in decisions about science and technology.

Decisions about science and technology should be made by scientists, engineers, and politicians, and the public should be informed about these decisions.

The public should be consulted and public opinion should only be considered when making decisions about science and technology.

Public opinion should be binding when making decisions about science and technology.

Non-governmental organizations (NGOs) should be partners in scientific and technological research.

This ordinal variable is converted into a dichotomous one, where “0” represents the least support for democratic control of science and “1” strong support for democratic control of science. The “0” category is assigned if the individual picked the first or second category and “1” if any other was chosen (M = 0.50, SD = 0.50).

Education level

The question on education in the Eurobarometer is “How old were you when you stopped full-time education”? At the same time, this variable includes such answers as “Still studying,” indicating current students. That is why, for sake of not losing information about students, we decided to assign value “23” for all of them, implying that, on average, in Europe people finish university education at the age of 23 (12 years of school starting at 7 years + 4 years of higher education). And then the categories were recoded. “0” now is assigned to those having no full-time education, “1” to those who have finished their full-time education at the age of 13 or lesser, “2” to those who have finished their full-time education at the age of 14 years, […], and “14” to those who have finished their full-time education at the age of 26 or later (M = 7.32, SD = 3.77).

Knowledgeability

This indicator is constituted from the level of interest and the level of awareness in the topic of science and technologies. The initial question on interest is as follows:

In everyday life, we have to deal with many different problems and situations, where we feel more or less interested and confident. I am going to read you a number of statements. For each of them, please tell me whether you are … New scientific discoveries and technological developments.

The possible answers are “Very interested” (30.8%), “Moderately interested” (50%), and “Not at all interested” (19.2%).

Awareness is measured in the same fashion. The respondents were asked the question “I would like you to tell me for each of the following issues in the news if you feel very well informed, moderately informed or poorly informed about it—New scientific discoveries and technological developments.” Answer categories are “Very well informed” (10.5%), “Moderately well informed” (50.1%), and “Poorly informed” (39.3%).

These variables were combined into one factor (Cronbach’s alpha = .7, Kaiser–Meyer–Olkin (KMO) = .5, Bartlett’s sphericity test p < .05, 77% of variance explained) and then standardized.

Distrust in scientists

This predictor shows whether respondents think scientists are those who can explain the aftermath of scientific discoveries on the society or not. The question is, “Among the following categories of people and organizations working in (OUR COUNTRY), which are the best qualified to explain the impact of scientific and technological developments on society?—Scientists working at a university or governmental laboratories.” Among other categories, there were journalists, politicians, consumer organizations, and so on. A respondent was asked to pick a maximum of three variants. This variable thus returns “1” if the category of interest was not picked and “0” if it was picked (M = 0.31, SD = 0.46).

Level of democratization

We measure democratization level through the Democracy Index which is developed by the Economist Intelligence Unit.⁶ This index is measured on the scale of 1–10 and consists of several subindicators: “Electoral Process and Pluralism,” “Functioning of Government,” “Political Participation,” “Political Culture,” and “Civil Liberties.” The range for countries which are covered by the Eurobarometer dataset is from 5.73 (Turkey—Hybrid Regime) to 9.8 (Norway—Full Democracy). This indicator is then standardized.

Several indicators are used as control measures, among them:

Occupational status

It is a 7-point nominal variable measuring the occupational status of the respondent. The question is, “Did you do any paid work in the past? What was your last occupation?” Initially this question had 18 categories, but Eurobarometer database also provides a compressed variable with seven categories, which is used in this study. The levels are self-employed (farmer, fisherman, professional, owner of a shop, craftsmen, business proprietor; 7.5%), managers (employed professional, general management, middle management; 11.3%), other white collars (employed position at desk, employed position traveling; 11.3%), manual workers (employed position, service job, supervisor, skilled manual worker, unskilled manual worker; 19.3%), house persons (7.5%), unemployed (7.5%), retired (26.3%), and students (9.2%).

Scientific background of parents

The question is, “Does/did any of your family have a job or university qualification in natural science, technology, or engineering (for instance, physics, chemistry, biology, medicine)?—No, no one in your family.” It returned “1” if no one in the family had or has university qualification in those realms and “0” otherwise (M = 0.45, SD = 0.5).

Personal scientific background

The question is, “Have you ever studied natural science, technology, or engineering: at school, in college, in the university, or anywhere else?” We treat this variable as binary where “0” stands for no background (“No, you have never studied any of these”) and “1” presupposes some background (“Yes, at the university,” “Yes, at the college,” “Yes, at school,” or “Yes, elsewhere”) (M = 0.77, SD = 0.42).

This study also controls for respondent’s gender (female = 1, M = 0.53, SD = 0.49)⁷ and age (standardized; range: 1.78–2.83).

4. Results

Democratization and public engagement

Table 2 provides the topline of variables measuring public engagement with science and support for democratic control of science broken down by country. All countries are sorted according to their value of the standardized democratization index. Overall, it is noticeable that more democratic nations tend to have higher levels of both dependent variables. The more democratic a nation is, the more people engage with science and the more they support democratic control of science.

Table 2.

Topline of dependent variables broken down by country.

	Democratization index	Engagement with science (binary)			Support for democratic control of science (binary)
		Mean	SD	N	Mean	SD	N
Norway	1.87	0.61	0.49	1035	0.39	0.49	998
Iceland	1.71	0.61	0.49	498	0.48	0.5	475
Denmark	1.58	0.53	0.5	1004	0.6	0.49	983
Sweden	1.55	0.59	0.49	1001	0.45	0.5	976
Finland	1.23	0.52	0.5	1000	0.59	0.49	985
Switzerland	1.13	0.61	0.49	1018	0.63	0.48	966
The Netherlands	1.02	0.46	0.5	1013	0.47	0.5	988
Luxembourg	0.91	0.46	0.5	502	0.53	0.5	486
Ireland	0.81	0.31	0.46	978	0.44	0.5	906
Austria	0.50	0.62	0.49	994	0.61	0.49	957
Germany	0.38	0.44	0.5	1526	0.64	0.48	1468
Malta	0.28	0.21	0.41	489	0.46	0.5	456
Czech Republic	0.19	0.33	0.47	1039	0.44	0.5	1013
Spain	0.15	0.30	0.46	1003	0.49	0.5	923
United Kingdom	0.15	0.33	0.47	1299	0.57	0.5	1191
Belgium	0.04	0.46	0.5	1009	0.52	0.5	960
Portugal	0.01	0.26	0.44	1014	0.49	0.5	899
Greece	−0.10	0.48	0.5	985	0.42	0.49	982
Italy	−0.19	0.44	0.5	1002	0.48	0.5	945
France	−0.25	0.28	0.45	1017	0.65	0.48	954
Slovenia	−0.34	0.23	0.42	1003	0.51	0.5	955
Estonia	−0.35	0.27	0.44	994	0.47	0.5	936
Slovakia	−0.69	0.45	0.5	1028	0.40	0.49	998
Cyprus	−0.75	0.19	0.39	499	0.37	0.48	476
Lithuania	−0.81	0.26	0.44	1022	0.51	0.5	944
Hungary	−0.84	0.35	0.48	1014	0.49	0.5	980
Poland	−1.01	0.22	0.41	994	0.54	0.5	875
Latvia	−1.01	0.25	0.43	1003	0.44	0.5	959
Bulgaria	−1.22	0.22	0.41	979	0.46	0.5	935
Croatia	−1.26	0.38	0.49	990	0.45	0.5	934
Romania	−1.48	0.20	0.4	1038	0.38	0.49	886
Turkey	−2.38	0.26	0.44	951	0.40	0.49	890

Figure 1a and b presents this relation more clearly. On the Y-axis, there is mean level of public engagement (Figure1a) and support for democratization of science (Figure1b) and on the X-axis there is the standardized coefficient of nation-level democratization. More democratic countries indeed tend to have more people engaging with science. The estimate for the coefficient in the simple one-predictor regression model is .09 (t-value = 6.24, p < .05). Democratization level explains approximately 55% of variance in the level of public engagement with science across countries (multiple R² = .56; adjusted R² = .55).

Figure 1b shows that there is a considerable variance in the share of supporters of democratic control across countries. The regression model shows borderline significance of the effect of national-level democratization on the level of support for democratic control of science (estimate = 0.03, t-value = 2.02, p = .053, multiple R² = .12, adjusted R² = .09). Partially, it may be attributed to the low level of support for democratic control of science in three highly democratic European nations—Norway, Sweden, and Iceland.

Explaining public engagement with science

Multi-level modeling shows that the democratization level is positively associated with chances of people to engage with science (p < .01), but its effect decreases when individual-level explanatory variables are added. Females as well as those having high-skilled jobs (self-employed, managers, other white collars) are more likely to participate. People having a personal scientific background or whose parents have some, as well as those who expect the public to engage with science are more likely to participate themselves. Moreover, the empirical analysis supports the idea that more educated (p < .01), knowledgeable individuals (p < .01), and those distrusting scientists (p < .01) have higher chances to engage.

Figure 2a and b provides plots for the two significant interaction terms from model 3. It shows that the effects of distrust in scientists and knowledgeability on public engagement with science tend to diminish in more democratic nations. While the effect of knowledgeability is significant across all the countries, the effect of distrust in scientists is significant only in countries where democratization level is below the average.

Explaining public support for democratic control of science

The rest of Table 1 provides results of the analysis where support for democratic control of science serves as a dependent variable. Similar to the models on public engagement with science, the indicator for national democratization appears to be positively associated with support for democratic control (p < .05). Among the control variables, only age shows a significant effect (p < .05). Older people are less likely to expect the public to participate in science policy-shaping. Education level does not have any explanatory power, but knowledgeability and distrust in scientists do have: knowledgeable and distrusting individuals are more likely to support democratic control of science.

The table also shows that interactions between the national democratization level and education and distrust in scientists are significant. Figure 3a and b provides interaction term graphs. It is noticeable that the direction of the effect of education on support for democratic control of science changes across levels of democratization. In less democratic countries, more-educated people are less likely to expect public to engage, while in more advanced democracies, more-educated people become those who demand engagement most fiercely. The effect of distrust in scientists is positive across almost all the spectrum of countries, but its magnitude tends to decrease in more democratic nations.

Summary of the results

To sum up the results, a country’s democratization level is positively associated with both public engagement with science and support for democratic control (H1 A, B—confirmed). Moreover, our findings indicate that individual-level variables have more power in explaining public engagement in science and less so for support for democratization of science.

We found that people with a higher level of education tend to be more likely to engage with science, which supports reflexive modernization theory. However, there is no effect of education on support for democratic control of science (H2 A—rejected, H4 A—partially confirmed). Knowledgeable people are more likely both to participate and to expect public to participate in science policy-shaping (H4 B—confirmed). People distrusting scientists are more likely both to participate and to expect citizens to participate in science–public dialogue (H2 B—confirmed), which speaks in favor of the institutional alienation perspective. The effect of education on public engagement with science does not change across countries with different levels of democratization, but its effect on support for democratic control of science becomes positive in more democratic nations, compared to less democratic ones, where the effect of education is negative (H3 A—rejected, H5 A—partially confirmed). The effect of distrust in scientists on both dependent variables diminishes in more democratic societies (H3 B—rejected) perhaps indicating that in those countries people see less reason to engage in science as they observe more overall democratic control. We will take this issue up in the next section. The effect of knowledgeability on actual participation decreases in more democratic nations, but its impact on support for democratic control of science remains unchanged (H5 B—rejected).

5. Discussion

This article provides empirical insight into the phenomenon of public engagement in science governance, the topic around which there has been a great deal of controversy among social scientists, policymakers, and stakeholders from the public (Stilgoe et al., 2014; Sturgis, 2014). Unlike the contribution of Mejlgaard and Stares (2013), in which the authors classified citizens according to their level of preferred and performed participation, our goal was somewhat different, attempting to shed light on (a) the relation between country’s level of democratization and the rate of actual and expected public engagement with science, and (b) the characteristics of individuals who are more likely to engage themselves and to support public control of science institution.

Our findings indicate that democratic nations harbor publics, which demand more control over scientific institutions, and who are also more willing to put science into practice. As for the case of science, bringing lay agency into decision-making and demonopolizing scientific expertise (Beck et al., 1994; Nowotny et al., 2013) seems to have become an urgent matter, since half of the European population believes people’s opinions in this realm should be taken into account, and 4 out of 10 reported having some personal experience of engaging with science. In this light, finding a positive relation between nation’s level of democratization and the level of both actual public engagement with science and support for democratic control of science tends to be reassuring: more democratic nations provide people claiming their voice (Welzel et al., 2003) with necessary mechanisms and institutions for translating participatory intentions into meaningful and effective actions.

Our results confirm a tentative idea that the “democratic deficit” (Bucchi, 2008: 57–77), as the inability of establishing proper communication between lay citizens and institutional representatives, is apparently less acute in democratic countries than in less developed nations. However, no matter how straightforward this result may seem, even in highly democratic countries this promising idea of “extended peer review” (Jasanoff, 2003: 232), in which the public is as welcome as scientists and responsible officials to propose and defend their viewpoint, faces a number of shortcomings that appear as a result of the transition from “high theory to complex and messy practice” (Sturgis, 2014: 38). One shortcoming is that while those protest activities do actually enable dialogue between the public and the scientists, each designating their standpoints, protesters are seldom allowed to discuss the issue of concern with scientists on an equal level. If their participation is just a manifestation of their views, then the very idea of two-way deliberations (Einsiedel, 2008: 173–184) as an essence of public engagement and a cornerstone of every theory of post-representative politics remains unmet. However, the (in)ability of engagement procedures and participatory governance as a whole to ensure that the opinion delivered by a small group of activists indeed represents the view of the “ordinary citizen” should be taken into account (Powell et al., 2011).

The proponents of participatory democracy advocate that those more committed and concerned people should eventually be granted more decisional capacity than their counterparts who are less inclined to express their opinion (Della Porta, 2013). However, this logic should be taken with caution when discussing such subtle topics as governance of science and emerging technologies, where many people may still express their trust to scientists and see claims made by non-professionals in this field as redundant and not worth taking into account.

In this study, we focused on the question of who are the main supporters of the democratization of science. We used two theoretical perspectives, that of institutional alienation and that of reflexive modernization. Both perspectives helped us understand who actually engages in scientific activities and who is supportive of democratic control of science. Yet, our findings were not totally in line with both theoretical perspectives.

The first perspective predicted that those who are distrustful of scientific institutions will, on average, be more inclined to favor democratic control and to engage in scientific activities. This is logical, in a way: those who distrust scientific institutions will have to do it themselves. As Gauchat (2011) notes, the state of “disassociation, disenchantment or discontent with abstract bureaucratic systems among segments of society” (p. 755) which is referred to as institutional alienation has a significant negative effect on public trust in science, and in line with this argument, distrusting scientists leads people to be more proactive in controlling science rather than relying on the officials and their viewpoint. Yet, this perspective also predicted that such institutional distrust would increasingly affect support for democratic control and actual levels of scientific engagement in more democratic nations. We found the exact opposite, which requires a speculative explanation. There are multiple possible interpretations of these findings.

That distrust in science less strongly affects support for democratic control and public engagement in science in democratic countries could be the effect of the success of democratization itself. In countries with high levels of democratization, those who are highly critical of science institutions might feel assured by the idea that in these countries there is actually more democratic control of scientific activities and people are more directly engaged in science, which, in turn, yields a less strong demand for even more democratization of science. Another interpretation could be that as in democratic nations the level of public involvement of science is so high, it cannot be any higher. It, hence, could mean that there is a ceiling effect, which hinders increasing public involvement in the most democratic nations. Future research should be able to shed light on the empirical tenability of these expectations.

The second theoretical perspective, emphasizing reflexivity, predicted that it will be the more knowledgeable and highly educated who will be the carriers of more democratization of science. Finding positive effects of education and knowledgeability on engagement clearly supports the reflexive modernization thesis and depicts those informed, reflexive, and concerned individuals as a driving force of participatory governance. As Beck (1992) notes, “education and attentiveness to information open up new possibilities of dealing with and avoiding risks,” (p. 35) and this is the reason why those “reflexivity winners” (Beck et al., 1994: 121) become the first to acknowledge possible risks of scientific projects and to seek means to minimize them, conveying their standpoint to the officials and ultimately altering the way scientific and environmental policy is being conducted in the state. Yet, we also found a similar pattern as discussed above for the institutional alienation perspective. Knowledgeability affects democratization more strongly in less democratic nations and not as expected in the more advanced democracies.

Similar to the speculative interpretation offered above, it could well be that the effect of knowledge diminishes in more democratic nations as a result of a ceiling effect—public engagement with science simply cannot rise above certain levels. It may also be that the more knowledgeable will decline their enthusiasm for engaging with science as a result of increased democratization of science. Reflexive as they may be, they witness lay audiences engaging in science—engaging in debates about food, vaccinations, or climate change—and may conclude that democratization of science has simply gone too far. Not the successes of democratization but its failure might cause them to refrain from supporting more public involvement. More research, as always, is needed to ascertain whether or not these interpretations are empirically tenable.

Our findings also prompt research about the role of cultural capital for the democratization of science. The results obtained in this study are consistent with Bourdieu’s (1984, 1986) notion of cultural capital and the role it plays in shaping individual’s predispositions to a particular behavior, including their preferable response to the societal summons. The strong and positive relationship between public participation in science and personal or parental scientific background suggests that people indoctrinated with scientific worldviews are more susceptible to the discussion and political standoff that arises around certain controversial topics. Moreover, the effects of occupation and education may be also interpreted from this viewpoint. It appears that active citizens are primarily those who possess sufficient economic and cultural capital and thus are able and willing to devote some of their time and energy to societal and environmental concerns. Unlike their counterparts with lower social status, who perhaps are more focused on their own living, these people with more economic and cultural capital aim to tackle the global challenges.

It is noticeable from the analysis that people supporting democratic control of science are not completely alike in their characteristics with those who are carrying out the control by means of actual participation. This discrepancy should be scrutinized in further studies via socio-psychological theories dealing with the translation of personal beliefs into behavioral patterns. Ajzen’s (1985, 1987) theory of planned behavior and its derivatives may be an appropriate framework as it aims at clarifying how the resulting actions (in our case, individual’s participation in science governance) are predicted by the overall attitude toward this type of behavior, the perceived social pressure to act in a particular way, and behavioral control which refers to the “perceived ease or difficulty of performing the behavior” (p. 44).

There are certain limitations of this study that should be acknowledged and that provide an avenue for further research. First, from a methodological point of view, the quality of the data might be a cause of concern. The documentation about the data is far from complete and there is no information about the response rates per each country, begging the question about whether the results might be biased. Second, one might notice that the measure of knowledgeability used in this study takes into consideration respondents’ subjective opinion about their level of interest and awareness in such topics as new scientific discoveries and technological developments. It would be promising to look at how public engagement is associated with certain sources of scientific information consumption (television, Internet, newspapers, etc.), as well as to see how the overall level of scientific literacy (Miller, 2004) and the way the public perceives organized science and its cultural meaning (Gauchat, 2011) might predict people’s attitudes to science governance.

Third, our measure of distrust in scientists might provoke some discussion. One might argue that the question we are using measures not the extent to which citizens trust or distrust scientists as actors who are capable of maintaining the effect of emerging technologies on society but rather as actors able to convey possible pros and cons to the public. To unravel this issue, further research taking into account the multidimensionality of public trust into science (Achterberg et al., 2017) and the role of scientists as science communicators (Bucchi, 1996) should be carried out.

Finally, another limitation is the type of activities that the main dependent variable is formed from. The mechanisms of public engagement that are analyzed in this study—attending public meetings, joining street demonstrations, signing petitions, working in NGOs—are rather limited to those that may be broadly defined as untraditional political activism (Inglehart and Norris, 2003: 111) and definitely do not cover all the institutional arrangements of public–science dialogue that are used around the globe (e.g. Rowe and Frewer, 2000: 8–9). Analyzing them altogether would provide a better understanding of the public engagement process. However, scrutinizing each way of participation separately would also be of use, revealing how and why individuals with different sociodemographic characteristics engage with science in their own particular ways.

Footnotes

Acknowledgements

This study was conducted within the framework of the Basic Research Program at the National Research University Higher School of Economics (HSE) and supported within the framework of implementation of the HSE 5-100 Program Roadmap.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

Author biographies

Kirils Makarovs received his Master’s degree at the Faculty of Social Sciences, National Research University Higher School of Economics, Russia, and now is doing his PhD at the University of Essex. His research interests lie in the field of sociology of science, science governance, and quantitative methodology.

Peter Achterberg is a professor of Sociology at the Department of Sociology, Tilburg School of Social and Behavioral Sciences, Tilburg University, The Netherlands. He is a cultural sociologist with a general interest in studying cultural, political, and religious change in the west. For more information, see

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