Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Heuristics structure and pervade formal risk assessment

MacGillivray, Brian H. ORCID: https://orcid.org/0000-0001-9065-4451 2014. Heuristics structure and pervade formal risk assessment. Risk Analysis 34 (4) , pp. 771-787. 10.1111/risa.12136

[thumbnail of MacGillivray%2C Risk Analysis.pdf]
Preview
PDF - Accepted Post-Print Version
Download (596kB) | Preview

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: 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
ISSN: 0272-4332
Funders: Mellon Sawyer Fellowship
Date of First Compliant Deposit: 12 July 2016
Last Modified: 07 Nov 2023 00:29
URI: https://orca.cardiff.ac.uk/id/eprint/57271

Citation Data

Cited 9 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics