The Politics of Modelling Numbers Between Science and Policy 1st Edition Andrea Saltelli – Ebook Instant Download/Delivery ISBN(s): 9780198872429,0198872429
Product details:
- ISBN 10:0198872429
- ISBN 13: 9780198872429
- Author: Andrea Saltelli , Monica Di Fiore
Chapter 2, ‘Pay no attention to the model behind the curtain’, Chapter 4, ‘Mind the hubris: Complexity can misfire’, and Chapter 8, ‘ Sensitivity auditing: A practical checklist for auditing decision-relevant models’ are published open access and free to read or download from Oxford Academic The widespread use of mathematical models for policy-making and its social and political impact are at the core of this book. While the discussion of mathematical modelling generally centres around technical features, use, and type of model, the literature is increasingly acknowledging that the social nature of modelling, its biases and responsibilities, are equally worth investigating. This book tackles these emerging questions by adopting a multidisciplinary approach to investigate how current modelling practices address contemporary challenges, and fills a gap in the field, which has historically focused on statistical and algorithmic modes of producing numbers. Thanks to its multidisciplinary appeal, this book will be essential reading for modellers, public officials, policymakers, and scholars alike.
Table contents:
Part I – Meeting models
1:Introduction
2:Pay no attention to the model behind the curtain
Part II – The rules
3:Mind the framing: Match purpose and context
4:Mind the hubris: Complexity can misfire
5:Mind the assumptions: Quantify uncertainty and assess sensitivity
6:Mind the consequences: Quantification in economic and public policy
7:Mind the unknowns: Exploring the politics of ignorance in mathematical models
Part III – The rules in practice
8:Sensitivity auditing: A practical checklist for auditing decision-relevant models
9:Mathematical modelling: Lessons from composite indicators
10:Mathematical modelling, rulemaking, and the COVID-19 pandemic
11:In the twilight of probability: COVID-19 and the dilemma of the decision-maker
12:Models as metaphors
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