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Rationality in Context

Regulatory Science and the Best Scientific Method

Bibliographic Data

ID5409478
AuthorsOliver Todt (0000-0001-9363-0543, Universitat de les Illes Balears, corresponding author), José Luis Luján (0000-0002-8829-0609, Universitat de les Illes Balears)
Year2022
Volume47
Issue5
Pages1086-1108
Publication date2022-09-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueScience Technology & Human Values (JOURNAL)
Journal identifiersISSN: 0162-2439 • E-ISSN: 1552-8251
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/01622439211027639
OpenAlexW3182152840
LanguageEN
Citations received5
References cited31

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

Best practice · Bounded rationality · Economics · Epistemology · Management science · Political science · Rationality · Regulatory science · Computer Science · Health Systems, Economic Evaluations, Quality of Life · Law · Pharmaceutical industry and healthcare · Regulation and Compliance Studies · Artificial Intelligence

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Unique citing works5
Citations per year1,67
Citation span2023 - 2026 (4)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 5
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