Literature DB >> 24919396

Is risk analysis scientific?

Sven Ove Hansson1, Terje Aven.   

Abstract

This article discusses to what extent risk analysis is scientific in view of a set of commonly used definitions and criteria. We consider scientific knowledge to be characterized by its subject matter, its success in developing the best available knowledge in its fields of study, and the epistemic norms and values that guide scientific investigations. We proceed to assess the field of risk analysis according to these criteria. For this purpose, we use a model for risk analysis in which science is used as a base for decision making on risks, which covers the five elements evidence, knowledge base, broad risk evaluation, managerial review and judgment, and the decision; and that relates these elements to the domains experts and decisionmakers, and to the domains fact-based or value-based. We conclude that risk analysis is a scientific field of study, when understood as consisting primarily of (i) knowledge about risk-related phenomena, processes, events, etc., and (ii) concepts, theories, frameworks, approaches, principles, methods and models to understand, assess, characterize, communicate, and manage risk, in general and for specific applications (the instrumental part).
© 2014 Society for Risk Analysis.

Keywords:  Consensus; knowledge; norms; objectivity; probability; risk; science; uncertainty; values

Year:  2014        PMID: 24919396     DOI: 10.1111/risa.12230

Source DB:  PubMed          Journal:  Risk Anal        ISSN: 0272-4332            Impact factor:   4.000


  7 in total

1.  How normative interpretations of climate risk assessment affect local decision-making: an exploratory study at the city scale in Cork, Ireland.

Authors:  T K J McDermott; S Surminski
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2018-06-13       Impact factor: 4.226

2.  Reasoning and Knowledge Acquisition Framework for 5G Network Analytics.

Authors:  Marco Antonio Sotelo Monge; Jorge Maestre Vidal; Luis Javier García Villalba
Journal:  Sensors (Basel)       Date:  2017-10-21       Impact factor: 3.576

3.  Null Hypothesis Testing ≠ Scientific Inference: A Critique of the Shaky Premise at the Heart of the Science and Values Debate, and a Defense of Value-Neutral Risk Assessment.

Authors:  Brian H MacGillivray
Journal:  Risk Anal       Date:  2019-02-11       Impact factor: 4.000

4.  Psychological underpinnings of pandemic denial - patterns of disagreement with scientific experts in the German public during the COVID-19 pandemic.

Authors:  Tobias Rothmund; Fahima Farkhari; Carolin-Theresa Ziemer; Flávio Azevedo
Journal:  Public Underst Sci       Date:  2022-02-08

5.  Comparative analysis of the labelling of nanotechnologies across four stakeholder groups.

Authors:  Adam Capon; James Gillespie; Margaret Rolfe; Wayne Smith
Journal:  J Nanopart Res       Date:  2015-07-29       Impact factor: 2.253

6.  The Landscape of Risk Communication Research: A Scientometric Analysis.

Authors:  Floris Goerlandt; Jie Li; Genserik Reniers
Journal:  Int J Environ Res Public Health       Date:  2020-05-07       Impact factor: 3.390

7.  Handling Uncertainty in Models of Seismic and Postseismic Hazards: Toward Robust Methods and Resilient Societies.

Authors:  Brian H MacGillivray
Journal:  Risk Anal       Date:  2020-12-24       Impact factor: 4.000

  7 in total

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