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Rationality in Context: Regulatory Science and the Best Scientific Method

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Abstract

Is there such a thing as a “best scientific methodology” in regulatory (decision-oriented) science? By examining cases from varying regulatory processes, we argue that there is no best scientific method for generating decision-relevant data. In addition, in regulatory science, the most suitable methodologies often differ from what is considered best practice in knowledge-oriented (academic) science. In data generation for regulatory purposes, we are faced with a wide spectrum of preferred methodologies as well as controversy as to methodological choice. What goes by the most adequate scientific method can and will—justifiably and rationally—vary significantly according to context and use. In order to make this argument, we analyze four case studies, two from risk assessment and two from benefit assessment. Our analysis shows that it is the noncognitive objectives of a particular regulatory process that determine what counts as the most appropriate scientific method. We use the concept of bounded rationality to indicate that those methodological choices, despite being context-dependent, can be interpreted as rational.

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... Proving the health benefits of consuming foods is, however, often challenging for various reasons: nutrition is known to result in multiple, but subtle, effects; the biomarkers that are used may be more appropriate for reflecting a state of disease rather than health processes; and it may require a long timeframe to establish the actual impact of nutrients (Blumberg et al., 2010;De Boer et al., 2014;Stroeve et al., 2015;Weseler and Bast, 2012;Witkamp, 2021). The low number of authorised health claims has therefore also been (partially) explained in the literature to be due to the reliance on RCTs to establish health effects of nutrition (De Boer, 2021;Lenssen et al., 2018;Todt and Luján, 2021). Trials, or human intervention studies, are considered the type of experimental study design that has the best ability to establish causal relationships between the intake of substances and biomarkers of health. ...
Chapter
This chapter chronicles emerging evidence-based disciplines which can directly support research integrity—translational science, regulatory science, and meta-science. Movement toward precision of scientific standards is uneven, perhaps in part because there has been little accountability and few consequences for poor quality science. There has also been little investment in well-validated measurement instruments and methods for studying research integrity decisions themselves. Research ethics, which preceded the broader notion of research integrity, developed largely without an evidence base, in part because it was broadly assumed that scientific institutions were operating honestly, precluding the need for documenting that they were, indeed, doing so.KeywordsScientific standardsResearch synthesisScientific recordTranslational scienceRegulatory scienceMeta-scienceEvidence-based policyMeasurement relevant to research integrityIntegrity of research evidence
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During the last decade, approaches to evidence-based medicine, with its heavy reliance on the randomized clinical trial (RCT), have been adapted to nutrition science and policy. However, there are distinct differences between the evidence that can be obtained for the testing of drugs using RCTs and those needed for the development of nutrient requirements or dietary guidelines. Although RCTs present one approach toward understanding the efficacy of nutrient interventions, the innate complexities of nutrient actions and interactions cannot always be adequately addressed through any single research design. Because of the limitations inherent in RCTs, particularly of nutrients, it is suggested that nutrient policy decisions will have to be made using the totality of the available evidence. This may mean action at a level of certainty that is different from what would be needed in the evaluation of drug efficacy. Similarly, it is judged that the level of confidence needed in defining nutrient requirements or dietary recommendations to prevent disease can be different from that needed to make recommendations to treat disease. In brief, advancing evidence-based nutrition will depend upon research approaches that include RCTs but go beyond them. Also necessary to this advance is the assessing, in future human studies, of covariates such as biomarkers of exposure and response, and the archiving of samples for future evaluation by emerging technologies.
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Functional foods are closely associated with claims on foods. There are two categories of claims on foods: nutrition claims and health claims. Health claims on (functional) foods must be scientifically substantiated. In December 2006, the European Union published its Regulation 1924/2006 on nutrition and health claims made on foods. As concerns scientific evaluation, the EU-project PASSCLAIM resulted in a set of criteria for the scientific substantiation of health claims on foods. The European Food Safety Authority provides the scientific advise to the European Commission for health claims submitted under Regulation 1924/2006 and has hitherto published several hundreds of opinions on health claims, part of which are positive, part which are negative and a few with insufficient evidence. Antioxidant claims have been approved for the general function of vitamins but not for direct health effects in humans. Another issue with claims is consumer understanding. Consumers can hardly distinguish between graded levels of evidence, and they do make only little or no distinction between nutrition and health claims. Consumers understand nutrition and health claims different from scientists and regulators. Therefore, innovation in industry can readily proceed via approved nutrition claims and approved health claims. The market and the shelves in the stores will not be empty; rather they will look different in the years to come.
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The role of science in policymaking has gained unprecedented stature in the United States, raising questions about the place of science and scientific expertise in the democratic process. Some scientists have been given considerable epistemic authority in shaping policy on issues of great moral and cultural significance, and the politicizing of these issues has become highly contentious. Since World War II, most philosophers of science have purported the concept that science should be “value-free.” In Science, Policy and the Value-Free Ideal, Heather E. Douglas argues that such an ideal is neither adequate nor desirable for science. She contends that the moral responsibilities of scientists require the consideration of values even at the heart of science. She lobbies for a new ideal in which values serve an essential function throughout scientific inquiry, but where the role values play is constrained at key points, thus protecting the integrity and objectivity of science. In this vein, Douglas outlines a system for the application of values to guide scientists through points of uncertainty fraught with moral valence. Following a philosophical analysis of the historical background of science advising and the value-free ideal, Douglas defines how values should-and should not-function in science. She discusses the distinctive direct and indirect roles for values in reasoning, and outlines seven senses of objectivity, showing how each can be employed to determine the reliability of scientific claims. Douglas then uses these philosophical insights to clarify the distinction between junk science and sound science to be used in policymaking. In conclusion, she calls for greater openness on the values utilized in policymaking, and more public participation in the policymaking process, by suggesting various models for effective use of both the public and experts in key risk assessments.
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When an activity raises threats of harm to human health or the environment, precautionary measures should be taken even if some cause and effect relationships are not fully established scientifically. This idea, known as the "Precautionary Principle," is seen by environmentalists and public health experts as the key to protecting ecological and human health.In January 1998, the Science and Environmmental Health Network convened an international group of scientists, researchers, environmentalists, academics, and labor representatives to discuss ways of incorporating the precautionary approach into environmental and public health decision-making. Known as the Wingspread Conference on Implementing the Precautionary Principle, the workshop focused on understanding the contexts under which the principle developed, its basis, and how it could be implemented. Protecting Public Health and the Environment is an outgrowth of that conference. The book: describes the history, specific content, and scientific and philosophical foundations of the principle of precautionary action explains the functions of the principle in activities as diverse as agriculture and manufacturing explains how to know when precautionary action is needed and who decides what action will (or will not) be taken attempts to show how the burden of proof of environmental harm can be shifted to proponents of a potentially hazardous activity provides specific structures and mechanisms for implementing the precautionary principl. Throughout, contributors focus on the difficult questions of implementation and fundamental change required to support a more precautionary approach to environmental and public health hazards. Among the contributors are David Ozonoff, Nicholas Ashford, Ted Schettler, Robert Costanza, Ken Geiser, and Anderw Jordan.Public health professionals and academics, policymakers, environmental lawyers, sustainable agriculture proponents, economists, and environmental activists will find the book an enlightening and thought-provoking guide to a new way of thinking about ecosystem and public health protection.
Article
"This volume presents an attempt to construct a unified cognitive theory of science in relatively short compass. It confronts the strong program in sociology of science and the positions of various postpositivist philosophers of science, developing significant alternatives to each in a reeadily comprehensible sytle. It draws loosely on recent developments in cognitive science, without burdening the argument with detailed results from that source. . . . The book is thus a provocative one. Perhaps that is a measure of its value: it will lead scholars and serious student from a number of science studies disciplines into continued and sharpened debate over fundamental questions."—Richard Burian, Isis "The writing is delightfully clear and accessible. On balance, few books advance our subject as well."—Paul Teller, Philosophy of Science
Article
In this paper I have attempted to identify some of the structural characteristics that are typical of the "psychological' environments of organisms. We have seen that an organism in an environment with these characteristics requires only very simple perceptual and choice mechanisms to satisfy its several needs and to assure a high probability of its survival over extended periods of time. In particular, no "utility function' needs to be postulated for the organism, nor does it require any elaborate procedure for calculating marginal rates of substitution among different wants.
Article
Two epistemological claims underwrite the randomized clinical trial (RCT). 1 The first, associated with Austin Bradford Hill, asserts that randomization prevents biased estimates of the value of new therapies. The second, associated with RA Fisher, maintains that randomization is necessary for the valid interpretation of statistical significance. This paper places Fisher’s views on randomization in the larger context of his views on statistical inference and the nature of science. Fisher’s life-long interest in the problem of induction, how to draw valid empirical conclusions about the world, led him to emphasize the provisional character of knowledge. The statistical methods he developed—randomization, likelihood—were aimed at producing what Fisher termed ‘rigorously specified uncertainty’. Fisher’s highly technical arguments about the nature of probability and likelihood are rooted in his more general concerns about the evolutionary and political importance of intellectual autonomy—concerns rooted in his early eugenical views but strongly reinforced by his ideological critique of Soviet science during the Cold War. Notwithstanding the esoteric origins of some of his arguments, Fisher’s ideas have great relevance for contemporary debates within evidence-based medicine. How we best distinguish what is known from what is not known, how we can emphasize the uncertainty of existing knowledge, and how we can best capture that uncertainty—all these Fisherian concerns are crucial in a time when the passage from the journal article to the press conference is increasingly swift.
Article
"Weight of evidence" (WOE) is a common term in the published scientific and policy-making literature, most often seen in the context of risk assessment (RA). Its definition, however, is unclear. A systematic review of the scientific literature was undertaken to characterize the concept. For the years 1994 through 2004, PubMed was searched for publications in which "weight of evidence" appeared in the abstract and/or title. Of the 276 papers that met these criteria, 92 were selected for review: 71 papers published in 2003 and 2004 (WOE appeared in abstract/title) and 21 from 1994 through 2002 (WOE appeared in title). WOE has three characteristic uses in this literature: (1) metaphorical, where WOE refers to a collection of studies or to an unspecified methodological approach; (2) methodological, where WOE points to established interpretative methodologies (e.g., systematic narrative review, meta-analysis, causal criteria, and/or quality criteria for toxicological studies) or where WOE means that "all" rather than some subset of the evidence is examined, or rarely, where WOE points to methods using quantitative weights for evidence; and (3) theoretical, where WOE serves as a label for a conceptual framework. Several problems are identified: the frequent lack of definition of the term "weight of evidence," multiple uses of the term and a lack of consensus about its meaning, and the many different kinds of weights, both qualitative and quantitative, which can be used in RA. A practical recommendation emerges: the WOE concept and its associated methods should be fully described when used. A research agenda should examine the advantages of quantitative versus qualitative weighting schemes, how best to improve existing methods, and how best to combine those methods (e.g., epidemiology's causal criteria with toxicology's quality criteria).
Regulating Toxic Substances
  • C Cranor
Cranor, C. 1993. Regulating Toxic Substances. New York: Oxford University Press.
General Guidance for Stakeholders on Health Claim Applications
EFSA (European Food Safety Authority). 2016. "General Guidance for Stakeholders on Health Claim Applications." EFSA Journal 14 (4367): 1-38.
Scientific and Technical Guidance for the Preparation and Presentation of a Health Claim Application
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