The Politics of Modelling (PDF)
Numbers Between Science and Policy
(Sprache: Englisch)
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...
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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.
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.
Autoren-Porträt
Andrea Saltelli is based at Pompeu Fabra University in Barcelona. His most recent papers have tackled sensitivity analysis and auditing, the ecological footprint, the future of statistics, the rationale of evidence-based policy, the crisis of science and the post-truth discussion. Andrea gives courses in sensitivity analysis, sensitivity auditing, science integrity, and the ethics of quantification. He has recently published on the role of science in processes of regulatory capture.Monica Di Fiore is a researcher at the Institute for Cognitive Sciences and Technologies of the Italian National Research Council (CNR) of Rome. She has dealt with innovation and social acceptance of technologies.
Her most recent work focuses on open science and responsible research and innovation, the reproducibility crisis, science-based normative capture, and the sociology and ethics of quantification. She recently contributed to a manifesto published by Nature on the quality of mathematical models.
Bibliographische Angaben
- 2023, 272 Seiten, Englisch
- Herausgegeben: Andrea Saltelli, Monica Di Fiore
- Verlag: Oxford University Press
- ISBN-10: 0198872429
- ISBN-13: 9780198872429
- Erscheinungsdatum: 10.08.2023
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