This article examines the relationship between the general public’s understanding of science and the attitude towards public funding of scientific research. It applies a multivariate and discriminant analysis (Wilks’ Lambda), in addition to a more commonly used bivariate analysis (Cramer’s V), to data compiled from the Third National Survey on the Social Perception of Science and Technology in Spain (FECYT, 2006). The general conclusion is that the multivariate analysis produces information complementary to the bivariate analysis, and that the variables commonly applied in public perception studies have limited predictive value with respect to the attitude towards public funding of scientific research.

This paper analyzes the study of the public perception of biotechnology, comparing different studies made on the European and the Spanish national levels. It aims at testing the applicability of these kinds of studies, and describes some of their limits. The analysis shows clear ambivalence in the public response to distinct applications of this technology, pointing out the crucial differences between general moral valuation and attitude towards specific products. Taking into account this difference appears fundamental for the design of future perception studies able to more accurately reflect public understanding.

In this article we argue that the precautionary principle, as applied to the regulation of science and technology, cannot be considered in any general manner inconsistent with the norms and methods of scientific knowledge generation and justification. Moreover, it does not necessarily curtail scientific-technological innovation. Our argument flows from a differentiated view of what precaution in regulation means. We first characterize several of the most relevant interpretations given to the precautionary principle in academic debate and regulatory practice. We then use examples of actual precaution-based regulation to show that, even though science can have varying functions in different circumstances and frames, all of those interpretations recur to scientific method and knowledge, and tend to imply innovation in methods, products, and processes. In fact, the interplay of regulation and innovation in precautionary policy, at least in the case of the interpretations of precaution that our analysis takes into account, could be understood as a way of reconciling the two fundamental science and technology policy functions of promotion and control.

This article presents the results of a study of public perception recently completed in Spain which questioned citizens about their views on the precautionary principle, the role of science in policy making, as well as their level of trust in science. The results show that Spanish citizens, by a significant margin, consider that scientists may be influenced by economic interests, that values play a key role in policy making, and that policy should be guided by precaution. Two groups were identified, one with a moderate and the other one with a more stringent interpretation of precaution. The results indicate that public policies that do not sufficiently take into account precaution and exclude values from decision making are likely to encounter resistance among many citizens.

This paper proposes a typology of two fundamentally opposing conceptualizations of managing technology under uncertainty: 'technology governability' and 'technology selection'. A wide variety of different versions of these idealized conceptualizations can be shown to underlie the controversies about scientifictechnological development. The example of genetic engineering indicates that such points of view are reconstructed over time in different forms and diverse settings, not only by the scientific community or during regulatory decision making, but by a rather wide-reaching spectrum of social actors. Thus, the current efforts to open up science and technology decision making to a wider range of participants is interpreted here as an effort of generating a new social contract for technology management, by way of bridging the differences between the two opposing conceptualizations.

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This article analyzes the debate about data acquisition and assessment in health claims regulation by identifying the underlying controversies on methodological choice. Regulation in the European Union imposes the need for a scientific substantiation of all health claims (claims about a relationship between consumption of certain food ingredients and positive health effects). Randomized controlled trials (RCTs) are the method that generally is considered to provide the highest quality data for decision making in claims regulation because they allow for establishing cause-effect relationships. The latter are demanded in European regulatory practice for authorization of a claim. This requirement has contributed to a debate about the advantages and limitations of the RCT methodology in nutrition research and regulation. Our analysis identifies five types of tensions that underlie the controversy, with respect to evidence, cognitive values, standards of proof, future lines of research, as well as expert judgment. We conclude that there is a direct and mutual interaction between methodological decisions in nutrition science, and different strategies in health claims regulation. The latter have social and public health consequences because not only may they affect the European market for functional foods, as well as concomitant consumption patterns, but also the generation of future regulation-relevant evidence in nutrition.

In this paper we argue for a naturalistic solution to some of the methodological controversies in regulatory science, on the basis of two case studies: toxicology (risk assessment) and health claim regulation (benefit assessment). We analyze the debates related to the scientific evidence that is considered necessary for regulatory decision making in each of those two fields, with a particular attention to the interactions between scientific and regulatory aspects. This analysis allows us to identify two general stances in the debate: a) one that argues for more permissive standards of evidence and for methodological pluralism, and b) an opposing one that not only defends strict evidence requirements but also stipulates the use of one particular (or at most a few) scientific methodologies for data generation. We argue that the real-world outcomes produced by alternative regulatory options are a vital piece of information that allows for the empirical assessment of these two stances. In particular, this information on outcomes makes it possible to analyze which standards of evidence and scientific methods generate the most useful knowledge as input for regulatory decision making. Our conclusion is that instead of an a priori selection of methodologies and standards, such decisions ought to be based on empirical evidence related to real-world outcomes.