Mechanistic information is used in the field of risk assessment in order to clarify two controversial methodological issues, the selection of inference guides and the definition of standards of evidence. In this paper we present an analysis of the concept of mechanistic information in risk assessment by recurring to previous philosophical analyses of mechanistic explanation. Our conclusion is that the conceptual analysis of mechanistic explanation facilitates a better characterization of the concept of mechanistic information. However, it also shows that the (...) use of this kind of information in risk assessment is heavily influenced by pragmatic factors, which have not been sufficiently taken into account in philosophical analysis. Mechanistic models are like hypothesis that have to be validated empirically. Due to their dependence on the standards of evidence, they are subject to the same pragmatic factors. Therefore, recurring to mechanistic information does not lead to closure of the methodological controversies in risk assessment. (shrink)

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 and health claim regulation. 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 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. (shrink)

The relevance of scientific knowledge for science and technology policy and regulation has led to a growing debate about the role of values. This article contributes to the clarification of what specific functions cognitive and noncognitive values adopt in knowledge generation and decisions, and what consequences the operation of values has for policy making and regulation. For our analysis, we differentiate between three different types of decision approaches, each of which shows a particular constellation of cognitive and noncognitive values. Our (...) objectives are to present a structured analysis of the varying functions that different kinds of values can adopt, as well as the value-related tensions and trade-offs they give rise to. We argue that the operation of noncognitive values in scientific knowledge generation, policy, and regulatory decision making can be understood as an enabling factor, rather than a limiting one. (shrink)

In ordinary circumstances, we can assess the worth of evidence well enough without benefit of any theory; but when evidence is especially complex, ambiguous, or emotionally disturbing—as it often is in legal contexts—epistemological theory may be helpful. A legal fact-finder is asked to determine whether the proposition that the defendant is guilty, or is liable, is established to the required degree of proof by the [admissible] evidence presented; i.e., to make an epistemological appraisal. The foundherentist theory developed in Evidence and (...) Inquiry can help us understand what this means; and reveals that degrees of proof cannot be construed as mathematical probabilities: a point illustrated by comparing the advantages of a foundherentist analysis with the disadvantages of probabilistic analyses of the evidence in the Sacco and Vanzetti case (1921), and of the role of the statistical evidence in Collins (1968). (shrink)

This paper argues that the crossword puzzle analogy is great for scientific rationality, but not scientific warrant. It provides a critical analysis of foundherentist conceptions of scientific warrant, especially that of Susan Haack, and closely related positions, such as non-doxastic coherentism. Foundherentism takes the middle ground between foundationalism and coherentism. The main idea is that warrant, including that of scientific theories, is like warrant of crossword entries: the degree to which a theory is warranted depends on one’s observations, the extent (...) to which it coheres with one’s other scientific theories and whether one’s evidence includes a sufficiently large portion of the relevant evidence. I identify three problems for a foundherentist conception of scientific warrant, two of which are also problems for the image of science as a crossword puzzle. First, Haack’s conceptions of personal and social warrant of scientific theories are incompatible. Second, the notion of warrant defe.. (shrink)

Le débat sur le rôle des valeurs en science survient également dans les sciences appliquées, en particulier dans les sciences régulatives. Nous proposons une analyse, sous l’angle des valeurs, des controverses récentes sur le rôle de la connaissance scientifique dans la régulation des risques technologiques. Nous distinguons trois perspectives sur les valeurs cognitives et non-cognitives, dans le contexte de l’évaluation et de la gestion du risque. Notre analyse montre que les deux types de valeurs interagissent au sein du processus de (...) génération de connaissances dans les sciences régulatives, et que des propositions de changements méthodologiques dépendent de la reconnaissance explicite du rôle opérant des valeurs. Notre contribution indique que l’analyse philosophique des valeurs peut aider à clarifier les controverses actuelles sur les risques technologiques. (shrink)

Economists reason causally. Like many other scientists, they aim at formulating justified causal claims about their object of study. This thesis contributes to our understanding of how causal reasoning proceeds in economics. By using the research on the causes of unemployment as a case study, three questions are adressed. What are the meanings of causal claims? How can a causal claim be adequately supported by evidence? How are causal beliefs affected by incoming facts? In the process of answering these semantic, (...) epistemic and dynamical questions, the richness of causal reasoning in economics is brought to the foreground. In the part on semantics, it is argued that the meaning of causal generalizations in policy-oriented economics is best captured by using the concept of ‘inferential relation’ rather than the one of ‘referential relation’. This part contributes to develop an inferentialist semantics by distinguishing among types of inferential relations. In the part on epistemology, it is argued that justification in sciences like economics often relies, and ought to rely, on evidential variety―i.e. the combination of evidence from multiple sources. An interpretation of independence among evidential sources is offered: two evidential sources are fully independent if and only if the reasons why they would be unreliable do not overlap. It is then shown that the variety-of-evidence thesis does not hold under extreme circumstances. The part on dynamics focuses on deviant-case study. A storyline is provided for what deviant-case study aims at and how it proceeds in what is characterized as an ‘eclectic science’. (shrink)