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)

Regulatory science, which generates knowledge relevant for regulatory decision?making, is different from standard academic science in that it is oriented mainly towards the attainment of non?epistemic (practical) aims. The role of uncertainty and the limits to the relevance of academic science are being recognized more and more explicitly in regulatory decision?making. This has led to the introduction of regulation?specific scientific methodologies in order to generate decision?relevant data. However, recent practical experience with such non?standard methodologies indicates that they, too, may be (...) subject to important limitations. We argue that the attainment of non?epistemic values and aims (like the protection of human health and the environment) requires not only control of the quality of the data and the methodologies, but also the selection of the level of regulation deemed adequate in each specific case (including a decision about which of the two, under?regulation or over?regulation, would be more acceptable). (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)

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)

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)

The function and legitimacy of values in decision making is a critically important issue in the contemporary analysis of science. It is particularly relevant for some of the more application-oriented areas of science, specifically decision-oriented science in the field of regulation of technological risks. Our main objective in this paper is to assess the diversity of roles that non-cognitive values related to decision making can adopt in the kinds of scientific activity that underlie risk regulation. We start out, first, by (...) analyzing the issue of values with the help of a framework taken from the wider philosophical debate on science and values. Second, we study the principal conceptualizations used by scholars who have applied them to numerous case studies. Third, we appraise the links between those conceptualizations and learning processes in decision-oriented science. In this, we recur to the concept of methodological learning, i.e., learning about the best methodologies for generating knowledge that is useful for science-based regulatory decisions. The main result of our analysis is that non-cognitive values can contribute to methodological improvements in science in three principal ways: as basis for critical analysis, for contextualizing methodologies, and for establishing the burden of proof. (shrink)

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)

This paper argues for the theoretical and practical validity of similarity as a useful epistemological tool in scientific knowledge generation, specifically in chemistry. Classical analyses of similarity in philosophy of science do not account for the concept’s practical significance in scientific activities. We recur to examples from chemistry to counter the claim of authors like Quine or Goodman to the effect that similarity must be excluded from scientific practices . In conclusion we argue that more recent conceptualizations of the notion (...) of similarity, particularly Giere’s one, are appropriate for a philosophical analysis that considers scientific practices on equal terms with scientific theory. (shrink)

En este trabajo analizamos una de las propuestas recientes que defienden modificaciones metodológicas en la evaluación de riesgos respecto a los estándares de prueba: el enfoque basado en el peso de las pruebas (weight of evidence). Este enfoque puede interpretarse como un caso de ciencia precautoria en la investigación sobre riesgos. Esto es, se trata de una metodología que pretende proporcionar resultados más protectores de la salud pública y del entorno que las metodologías usuales en la evaluación de riesgos. Sin (...) embargo, existe la posibilidad de que quienes se muestran en contra de la regulación de ciertas aplicaciones tecnológicas introduzcan artificialmente incertidumbre en el cuerpo de la evidencia. En consecuencia, la metodología del peso de las pruebas no conduce de manera automática a una mayor protección de la salud pública y del ambiente. Por ello es necesario analizar cada innovación valorando los posibles riesgos y los posibles beneficios sociales, y decidir en cada caso cuál de las dos posibilidades, la subregulación o la sobrerregulación, es más aceptable. El conocimiento científico es un elemento necesario para llevar a cabo esta valoración, pero no la determina.This paper analyzes one recent proposal for modifying the metodologies used in risk assessment: the Weight-Of-Evidence (WOE) approach. This approach is an example of precautionary science in risk research, i.e. a methodology which aims at a better protection of human health and the environment. However, some groups opposed to the regulation of certain technologies have started artificially introducing uncertainties into the body of evidence. This means that the WOE approach does not automatically lead to a higher level of health or environmental protection. It is therefore necessary to analyze each innovation on a case-by-case basis in order to evaluate its risks and benefits, and decide if to accept lower or, on the contrary, higher standards for its regulation. Scientific knowledge is a necessary element in this assessment, but not the decisive one. (shrink)

Is there such a thing as a “best scientific methodology” in regulatory 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 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. (shrink)

The issue of internalism and externalism in historiography of science was intensely debated two decades ago. The conclusions of such debate on the ‘context of science’ appear to be a reinstatement of the positivist view of the ‘content of science’ as comprising only ideas and concepts uninfluenced by extra-scientific factors. The description of the roles of politics, economy, and socio-cultural factors in science was limited only within the ‘context of science’. This article seeks to resituate the ‘content of science’ debate (...) within the historical accounts of the Scientific Revolution to illustrate that their resort to historicism indicates that such content does not emerge from the void. It argues that, though some historicist accounts like Alexandre Koyré’s reinstate the positivist argument on the nature of the ‘content of science’, such historicist internalism greatly differs from positivist internalism, largely due to its acceptance of metaphysics in science. Therefore, as long as historicism is relied on to describe the content of science, a clear-cut distinction of the historicist internalism and externalism will be difficult to establish. (shrink)

En el primer capítulo de su libro Duchesneau aborda la cuestión de lo que es una especie, algo de difícil solución porque el de especie es un concepto de una potencia heurística inmensa y, a la vez, está lleno de agujeros que se hacen patentes en cuanto se pretende hilar fino para definirlo. Las alternativas entre la especie como grupo reproductivo -la "especie biológica"- y como secuencia evolutiva -la "especie filogenética"-, con sus respectivas precisiones internas, están bien planteadas por el (...) autor. También lo está la más reciente "especie ecológica", de talante adaptacionista. Duchesneau no pretende argumentar en favor de uno u otro concepto, sino indicar que existen, y de su postura aséptica se deduce que, probablemente, es imposible reducir ninguno de esos conceptos al otro. Pero esa conclusión tropieza de inmediato con el asunto que aborda Duchesneau en el epígrafe siguiente de su libro: la taxonomía. Porque en algo coinciden al menos quienes emplean especies biológicas, filogenéticas y ecológicas: en darles un nombre. No es raro, pues, que la sistemática sea en estos momentos una de las disciplinas que tenga más interrogantes por resolver. (shrink)