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Submission declined on 29 January 2024 by
Asilvering (
talk). This draft's references do not show that the subject
qualifies for a Wikipedia article. In summary, the draft needs multiple published sources that are:
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This draft has been resubmitted and is currently awaiting re-review. |
Submission declined on 12 December 2023 by
MicrobiologyMarcus (
talk). This submission's references do not show that the subject
qualifies for a Wikipedia article—that is, they do not show significant coverage (not just passing mentions) about the subject in published,
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Submission declined on 12 September 2023 by
Utopes (
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Submission declined on 5 September 2023 by
Edward-Woodrow (
talk). This submission is not adequately supported by
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verified. If you need help with referencing, please see
Referencing for beginners and
Citing sources. |
Editors |
Andrea Saltelli Monica Di Fiore |
---|---|
Language | English |
Subjects |
Mathematical modelling Social statistics Politics |
Publisher | Oxford University press |
Publication date | August 2023 |
Pages | 272 |
ISBN | 978-0198872412 |
The Politics of Modelling, Numbers Between Science and Policy is a multi-authors book edited by Andrea Saltelli and Monica Di Fiore and published in August 2023 by Oxford University Press.
The Politics of Modelling elaborates and expands on themes of responsible modelling from a manifesto published in the journal Nature in 2020. [1]. The text is structured into three main sections: Meeting Models, The Rules, and The Rules in Practice. [2] [3] The combination of theory with policy relevant examples makes the book accessible to modellers, researchers of modelling, and policy makers. [3]
The volume comes with a foreword of Wendy Nelson Espeland] and a preface of Daniel Sarewitz], with chapters from Andy Stirling, Wolfgang Drechsler, Philip B. Stark, Ting Xu, Paolo Vineis, Andrea Saltelli, and other scholars (Table).
Chapter | Essay title | Contributor(s) |
---|---|---|
Preliminary | Foreword. Mathematical modelling as a critical cultural enterprise | Wendy Nelson Espeland |
Preface. The sciences of modelling through | Daniel Sarewitz | |
Meeting the Models | Introduction | Monica Di Fiore and Andrea Saltelli |
Pay no attention to the model behind the curtain | Philip B. Stark | |
The Rules | Mind the framings: Match purpose and context | Monica Di Fiore, Marta Kuc-Czarnecka, Samuele Lo Piano, Arnald Puy, and Andrea Saltelli |
Mind the hubris: Complexity can misfire | Arnald Puy and Andrea Saltelli | |
Mind the assumptions: Quantify uncertainty and assess sensitivity | Emanuele Borgonovo | |
Mind the consequences: Quantification in economic and public policy | Wolfgang Drechsler and Lukas Fuchs | |
Mind the unknowns: Exploring the politics of ignorance in mathematical models | Andy Stirling | |
The Rules in Practice | Sensitivity auditing: A practical checklist for auditing decision-relevant models | Samuele Lo Piano, Razi Sheikholeslami, Arnald Puy, and Andrea Saltelli |
Mathematical modelling: Lessons from composite indicators | Marta Kuc-Czarnecka and Andrea Saltelli | |
Mathematical modelling, rule-making, and the COVID-19 pandemic | Ting Xu | |
In the twilight of probability: COVID-19 and the dilemma of the decision maker | Paolo Vineis and Luca Savarino | |
Models as metaphors | Jerome R. Ravetz | |
Epilogue: Those special models: A political economy of mathematical modelling | Andrea Saltelli and Monica Di Fiore |
The book argues that models live in a “state of exception” provided by their access to a wealth of methodology of analysis, and by their epistemic authority borrowed from mathematics. This state allows models to better defend an appearance of neutrality that is appreciated by policymakers in search of a justification. [4] A review published in the journal Science (journal) notes that the volume incorporated insights from science and technology studies to explore modeling beyond its technical aspects [2] A second review [3] in the journal Minerva (Springer journal) notes the book’s reference to the works of historians Margaret Morrison and Mary S. Morgan in considering models as mediators whereby models are simultaneously a tool, an interpretation, and a representation of the system. [5] : 205 . Does this encourage cynicism as to the utility of models?
Underexplored and overinterpreted as they are, models indeed have ’a state of exception’ (Epilogue). The cynical question would be: Is there any use in models at all? Or, to cite Stirling in Ch. 7. ”does the modelling baby need to be thrown out with the justificatory bathwater?” [3]
The book contrasts the danger of cynicism with suggestions to make models serve society, based on theory, examples, and a call for participatory modelling linked to Post-normal science, sensitivity auditing and the concept of extended peer community. [3] On the critical side, [3] the book ignores other ongoing efforts in enhancing or formalizing modelling practices such as the framework proposed van Voorn [6], and the Good Modelling Practice handbook developed for water management purposes in the Netherlands. [7] Also not treated is the ‘fit-for purpose’ [8] movement in modelling. [2] The book could say more on the challenge of participatory modelling, related to gaming and power relations – for example, Arnsteinds’ ladder of participation is not treated in the volume. [3]
If politicians on your news throw the ‘our modelling work shows’ line, then you are an audience who will benefit from this book. [9]
A review in Mathematics_Magazine [10] notes the book’s attention to sensitivity analysis:
They [the authors] stress the importance of sensitivity analysis, with a highly-illustrative and illuminating example that analyzes the EOQ (economic order quantity) formula.
Category:Mathematical terminology
Category:Mathematical and quantitative methods (economics)
Review waiting, please be patient.
This may take 3 months or more, since drafts are reviewed in no specific order. There are 2,540 pending submissions waiting for review.
Where to get help
How to improve a draft
You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article. Improving your odds of a speedy review To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags. Editor resources
Reviewer tools
|
Submission declined on 29 January 2024 by
Asilvering (
talk). This draft's references do not show that the subject
qualifies for a Wikipedia article. In summary, the draft needs multiple published sources that are:
Where to get help
How to improve a draft
You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article. Improving your odds of a speedy review To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags. Editor resources
This draft has been resubmitted and is currently awaiting re-review. |
Submission declined on 12 December 2023 by
MicrobiologyMarcus (
talk). This submission's references do not show that the subject
qualifies for a Wikipedia article—that is, they do not show significant coverage (not just passing mentions) about the subject in published,
reliable,
secondary sources that are
independent of the subject (see the
guidelines on the notability of books). Before any resubmission, additional references meeting these criteria should be added (see
technical help and learn about
mistakes to avoid when addressing this issue). If no additional references exist, the subject is not suitable for Wikipedia. |
Submission declined on 12 September 2023 by
Utopes (
talk). This draft's references do not show that the subject
qualifies for a Wikipedia article. In summary, the draft needs multiple published sources that are:
|
Submission declined on 5 September 2023 by
Edward-Woodrow (
talk). This submission is not adequately supported by
reliable sources. Reliable sources are required so that information can be
verified. If you need help with referencing, please see
Referencing for beginners and
Citing sources. |
Editors |
Andrea Saltelli Monica Di Fiore |
---|---|
Language | English |
Subjects |
Mathematical modelling Social statistics Politics |
Publisher | Oxford University press |
Publication date | August 2023 |
Pages | 272 |
ISBN | 978-0198872412 |
The Politics of Modelling, Numbers Between Science and Policy is a multi-authors book edited by Andrea Saltelli and Monica Di Fiore and published in August 2023 by Oxford University Press.
The Politics of Modelling elaborates and expands on themes of responsible modelling from a manifesto published in the journal Nature in 2020. [1]. The text is structured into three main sections: Meeting Models, The Rules, and The Rules in Practice. [2] [3] The combination of theory with policy relevant examples makes the book accessible to modellers, researchers of modelling, and policy makers. [3]
The volume comes with a foreword of Wendy Nelson Espeland] and a preface of Daniel Sarewitz], with chapters from Andy Stirling, Wolfgang Drechsler, Philip B. Stark, Ting Xu, Paolo Vineis, Andrea Saltelli, and other scholars (Table).
Chapter | Essay title | Contributor(s) |
---|---|---|
Preliminary | Foreword. Mathematical modelling as a critical cultural enterprise | Wendy Nelson Espeland |
Preface. The sciences of modelling through | Daniel Sarewitz | |
Meeting the Models | Introduction | Monica Di Fiore and Andrea Saltelli |
Pay no attention to the model behind the curtain | Philip B. Stark | |
The Rules | Mind the framings: Match purpose and context | Monica Di Fiore, Marta Kuc-Czarnecka, Samuele Lo Piano, Arnald Puy, and Andrea Saltelli |
Mind the hubris: Complexity can misfire | Arnald Puy and Andrea Saltelli | |
Mind the assumptions: Quantify uncertainty and assess sensitivity | Emanuele Borgonovo | |
Mind the consequences: Quantification in economic and public policy | Wolfgang Drechsler and Lukas Fuchs | |
Mind the unknowns: Exploring the politics of ignorance in mathematical models | Andy Stirling | |
The Rules in Practice | Sensitivity auditing: A practical checklist for auditing decision-relevant models | Samuele Lo Piano, Razi Sheikholeslami, Arnald Puy, and Andrea Saltelli |
Mathematical modelling: Lessons from composite indicators | Marta Kuc-Czarnecka and Andrea Saltelli | |
Mathematical modelling, rule-making, and the COVID-19 pandemic | Ting Xu | |
In the twilight of probability: COVID-19 and the dilemma of the decision maker | Paolo Vineis and Luca Savarino | |
Models as metaphors | Jerome R. Ravetz | |
Epilogue: Those special models: A political economy of mathematical modelling | Andrea Saltelli and Monica Di Fiore |
The book argues that models live in a “state of exception” provided by their access to a wealth of methodology of analysis, and by their epistemic authority borrowed from mathematics. This state allows models to better defend an appearance of neutrality that is appreciated by policymakers in search of a justification. [4] A review published in the journal Science (journal) notes that the volume incorporated insights from science and technology studies to explore modeling beyond its technical aspects [2] A second review [3] in the journal Minerva (Springer journal) notes the book’s reference to the works of historians Margaret Morrison and Mary S. Morgan in considering models as mediators whereby models are simultaneously a tool, an interpretation, and a representation of the system. [5] : 205 . Does this encourage cynicism as to the utility of models?
Underexplored and overinterpreted as they are, models indeed have ’a state of exception’ (Epilogue). The cynical question would be: Is there any use in models at all? Or, to cite Stirling in Ch. 7. ”does the modelling baby need to be thrown out with the justificatory bathwater?” [3]
The book contrasts the danger of cynicism with suggestions to make models serve society, based on theory, examples, and a call for participatory modelling linked to Post-normal science, sensitivity auditing and the concept of extended peer community. [3] On the critical side, [3] the book ignores other ongoing efforts in enhancing or formalizing modelling practices such as the framework proposed van Voorn [6], and the Good Modelling Practice handbook developed for water management purposes in the Netherlands. [7] Also not treated is the ‘fit-for purpose’ [8] movement in modelling. [2] The book could say more on the challenge of participatory modelling, related to gaming and power relations – for example, Arnsteinds’ ladder of participation is not treated in the volume. [3]
If politicians on your news throw the ‘our modelling work shows’ line, then you are an audience who will benefit from this book. [9]
A review in Mathematics_Magazine [10] notes the book’s attention to sensitivity analysis:
They [the authors] stress the importance of sensitivity analysis, with a highly-illustrative and illuminating example that analyzes the EOQ (economic order quantity) formula.
Category:Mathematical terminology
Category:Mathematical and quantitative methods (economics)