
The Politics of Modelling
Numbers Between Science and Policy
Oxford University Press
Published on 25. August 2023
Book
Hardback
272 pages
978-0-19-887241-2 (ISBN)
Description
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.
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.
Reviews / Votes
The strong principle for the real world is: never use a model if you don't know its limitations and side effects. In fact, you must know what it can't do for you better than what it can do. I am glad this project is taking place: a long-awaited examination of the role-and obligation-of modeling. * Nassim Nicholas Taleb, Distinguished Professor of Risk Engineering, NYU Tandon School of Engineering. Author of the five-volume Incerto series (The Black Swan) * The Politics of Modelling: Numbers between Science and Policy is a breath of fresh air and a much-needed cautionary view of the ever-increasing dependence on mathematical modelling in ever-widening directions. The five aspects of modelling that should be 'minded' are a sensitive summary of factors that should be considered when evaluating any mathematical model. * Orrin H. Pilkey, Professor, Duke University's Nicholas School of the Environment, Co-author, with Linda Pilkey-Jarvis, of Useless Arithmetic: Why Environmental Scientists Can't Predict the Future, Columbia University Press, Washington, DC, 2009 * The methods by which power insinuates itself into models, and facilitates their portability and amendments, are diverse and sometimes insidious. And that's one reason why the range of cases explored in The Politics of Modelling are so illuminating and why we need to pay attention to its authors. [...] Good scholarly books usually do one of two things. They dig into the details of something so that we understand it better, see it in a new light. We often call this depth. Or they bring things together in some creative amalgamation that allows us to make new comparisons, to see patterns we hadn't before seen. This we call breadth. It is rare when a book does both things well. This one does. * Wendy N. Espeland, Professor of Sociology, Northwestern University. * A modern Rip Van Winkle, awaking from a century of scientific slumbers, would be dismayed to find so much emphasis on models and so little talk of scientific laws and facts. Although Rip's dyspeptic view of models now seems misguided, a call for caution is very much in order. Modelling tools have consequences both for science and for a larger public, taking in historical, sociological, and moral perspectives as well as technical, scientific ones. * Theodore M. Porter, Department of History, UCLA, author of Trust in Numbers, Princeton University Press, Princeton, NJ, 1995 * My decades of modeling operation and interpretation of results have been greatly expanded by the terrific perspective proffered in The Politics of Modelling. * Anthony J. Sadar, Washington Times * The book provides inspiration, has a reflective but constructive tone, and exemplifies the politics of modelling in a clear way. * Lieke A. Melsen, Minerva * ...this book stands as a pioneering work in a field that has historically focused on statistical and algorithmic methods for generating numbers. * Ehsan Nabavi and Saman Razavi, Science * Recommended. Advanced undergraduates through faculty; professionals. * Choice * Accompanied by numerous references, the essays offer examples of models, their interpretations, and uses that have gone astray. * P.J. Campbell, Mathematics Magazine * 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. * Sondoss Elsawah, Environmental Modelling & Software, ScienceDirect * Accompanied by numerous references, the essays offer examples of models, their interpretations, and uses that have gone astray. * P.J. Campbell, Mathematics Magazine * 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. * Sondoss Elsawah, Environmental Modelling & Software, ScienceDirect *More details
Language
English
Place of publication
Oxford
United Kingdom
Target group
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 238 mm
Width: 156 mm
Thickness: 20 mm
Weight
598 gr
ISBN-13
978-0-19-887241-2 (9780198872412)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

E-Book
08/2023
1st Edition
OUP eBook
€91.49
Available for download
Persons
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.
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.
Editor
Academic CounsellorAcademic Counsellor, Universitat Pompeu Fabra (UPF), Barcelona School of Management
ResearcherResearcher, National Research Council of Italy, Institute for Cognitive Sciences and Technologies
Content
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
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