A model of faulty and faultless disagreement for post-hoc assessments of knowledge utilization in evidence-based policymaking

When evidence-based policymaking is so often mired in disagreement and controversy, how can we know if the process is meeting its stated goals? We develop a novel mathematical model to study disagreements about adequate knowledge utilization, like those regarding wild horse culling, shark drumlines and facemask policies during pandemics. We find that, when stakeholders disagree, it is frequently impossible to tell whether any party is at fault. We demonstrate the need for a distinctive kind of transparency in evidence-based policymaking, which we call transparency of reasoning. Such transparency is critical to the success of the evidence-based policy movement, as without it, we will be unable to tell whether in any instance a policy was in fact based on evidence.

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Publication Details

Journal
Scientific Reports
Published
2024-08-09
DOI
https://doi.org/10.1038/s41598-024-69012-3
Citations
2
Primary Topic
Evaluation and Performance Assessment
Type
article
Field-Weighted Citation Impact
0.98

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article

A model of faulty and faultless disagreement for post-hoc assessments of knowledge utilization in evidence-based policymaking

Hannah Rubin, Chad L. Hewitt, Katie Woolaston, Remco Heesen et al.
2 citations
Scientific Reports
Evaluation and Performance Assessment
0.98
article

A model of faulty and faultless disagreement for post-hoc assessments of knowledge utilization in evidence-based policymaking

Hannah Rubin, Chad L. Hewitt, Katie Woolaston, Remco Heesen, Emelda E. Chukwu, Anne Schwenkenbecher, Evangelina Schwindt, Veli Mitova, Mike D. Schneider, Alejandro Bortolus, Temitope O. Sogbanmu, Ricardo Kaufer, Helena Slanickova
article en
2 citations

Abstract

When evidence-based policymaking is so often mired in disagreement and controversy, how can we know if the process is meeting its stated goals? We develop a novel mathematical model to study disagreements about adequate knowledge utilization, like those regarding wild horse culling, shark drumlines and facemask policies during pandemics. We find that, when stakeholders disagree, it is frequently impossible to tell whether any party is at fault. We demonstrate the need for a distinctive kind of transparency in evidence-based policymaking, which we call transparency of reasoning. Such transparency is critical to the success of the evidence-based policy movement, as without it, we will be unable to tell whether in any instance a policy was in fact based on evidence.

Scientific ReportsVol. 14(1)
Consejo Nacional de Investigaciones Científicas y Técnicas (AR), Queensland University of Technology (AU), University of Groningen (NL), Murdoch University (AU), Lincoln University (NZ), University of Lagos (NG), Bielefeld University (DE), University of Johannesburg (ZA), ARL – Academy for Territorial Development in the Leibniz Association (DE), Centro Científico Tecnológico Patagónico (AR), Instituto de Biología Subtropical (AR), Nigerian Institute of Medical Research (NG), University of Missouri (US), London School of Economics and Political Science (GB)
National Science Foundation, Volkswagen Foundation, Consejo Nacional de Investigaciones Científicas y Técnicas, Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Universität Bielefeld, Directorate for Social, Behavioral and Economic Sciences, Zentrum für interdisziplinäre Forschung, Universität Bielefeld
Reduced inequalities
Openalex Percentile: Top 22%
Evaluation and Performance Assessment
0.98
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