The Politics of Modelling

If the road to change starts with recognition and self-awareness, then the book has done a significant service to the modelling community by naming the biases and calling out some of the dilemmas and risks deeply rooted in the modelling institution....I strongly recommend you take this book and embrace it for an intellectually stimulating learning and critical reflection experience where you will find yourself often nodding in agreement, and sometimes challenged by the depth and breadth of ideas.

Auteur

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.

Texte du rabat

Adopting a multidisciplinary approach, this edited volume brings together a diverse range of contributions to look beyond the strictly mathematical view of modelling and instead examine the social nature of models, their biases and responsibilities.

Résumé
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. Part of this title is published open access. This part is available to read and download as a PDF on Oxford Academic and is made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 International licence.

Contenu

• Foreword: Mathematically modelling as a critical cultural enterprise

• Wendy Espeland

• Preface: The sciences of modelling through

• Dan Sarewitz

• Part I - Meeting models

• 1: Introduction

• Monica Di Fiore and Andrea Saltelli

• 2: Pay no attention to the model behind the curtain

• Philip Stark

• Part II - The rules

• 3: Mind the framing: Match purpose and context

• Monica Di Fiore, Marta Kuc-Czarnecka, Samuele Lo Piano, Arnald Puy, and Andrea Saltelli

• 4: Mind the hubris: Complexity can misfire

• Arnald Puy and Andrea Saltelli

• 5: Mind the assumptions: Quantify uncertainty and assess sensitivity

• Emanuele Borgonovo

• 6: Mind the consequences: Quantification in economic and public policy

• Wolfgang Drechsler and Lukas Fuchs

• 7: Mind the unknowns: Exploring the politics of ignorance in mathematical models

• Andy Stirling

• Part III - The rules in practice

• 8: Sensitivity auditing: A practical checklist for auditing decision-relevant models

• Samuele Lo Piano, Razi Sheikholeslami, Arnald Puy, and Andrea Saltelli

• 9: Mathematical modelling: Lessons from composite indicators

• Marta Kuc-Czarnecka and Andrea Saltelli

• 10: Mathematical modelling, rulemaking, and the COVID-19 pandemic

• Ting Xu

• 11: In the twilight of probability: COVID-19 and the dilemma of the decision-maker

• Paolo Vineis and Luca Savarino

• 12: Models as metaphors

• Jerome R. Ravetz

• Epilogue: Those special models: A political economy of mathematical modelling

• Andrea Saltelli and Monica Di Fiore