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Heuristics structure and pervade formal risk assessment

MacGillivray, Brian H. 2014. Heuristics structure and pervade formal risk assessment. Risk Analysis 34 (4) , pp. 771-787. 10.1111/risa.12136

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Abstract

Lay perceptions of risk appear rooted more in heuristics than in reason. A major concern of the risk regulation literature is that such “error-strewn” perceptions may be replicated in policy, as governments respond to the (mis)fears of the citizenry. This has led many to advocate a relatively technocratic approach to regulating risk, characterized by high reliance on formal risk and cost-benefit analysis. However, through two studies of chemicals regulation, we show that the formal assessment of risk is pervaded by its own set of heuristics. These include rules to categorize potential threats, define what constitutes valid data, guide causal inference, and to select and apply formal models. Some of these heuristics lay claim to theoretical or empirical justifications, others are more back-of-the-envelope calculations, while still more purport not to reflect some truth but simply to constrain discretion or perform a desk-clearing function. These heuristics can be understood as a way of authenticating or formalizing risk assessment as a scientific practice, representing a series of rules for bounding problems, collecting data, and interpreting evidence (a methodology). Heuristics are indispensable elements of induction. And so they are not problematic per se, but they can become so when treated as laws rather than as contingent and provisional rules. Pitfalls include the potential for systematic error, masking uncertainties, strategic manipulation, and entrenchment. Our central claim is that by studying the rules of risk assessment qua rules, we develop a novel representation of the methods, conventions, and biases of the prior art.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Sustainable Places Research Institute (PLACES)
Psychology
Subjects: B Philosophy. Psychology. Religion > BF Psychology
H Social Sciences > HD Industries. Land use. Labor > HD61 Risk Management
Uncontrolled Keywords: Governance; inference rules; model evaluation; risk regulation; science policy
Additional Information: Online publication date: 23 October 2013.
Publisher: Wiley-Blackwell
ISSN: 0272-4332
Funders: Mellon Sawyer Fellowship
Date of First Compliant Deposit: 12 July 2016
Last Modified: 05 Jun 2017 02:03
URI: http://orca.cf.ac.uk/id/eprint/57271

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