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Evidence for policy-makers: A matter of timing and certainty?
Policy Sciences ( IF 5.121 ) Pub Date : 2024-03-06 , DOI: 10.1007/s11077-024-09526-9
Wouter Lammers , Valérie Pattyn , Sacha Ferrari , Sylvia Wenmackers , Steven Van de Walle

This article investigates how certainty and timing of evidence introduction impact the uptake of evidence by policy-makers in collective deliberations. Little is known about how experts or researchers should time the introduction of uncertain evidence for policy-makers. With a computational model based on the Hegselmann–Krause opinion dynamics model, we simulate how policy-makers update their opinions in light of new evidence. We illustrate the use of our model with two examples in which timing and certainty matter for policy-making: intelligence analysts scouting potential terrorist activity and food safety inspections of chicken meat. Our computations indicate that evidence should come early to convince policy-makers, regardless of how certain it is. Even if the evidence is quite certain, it will not convince all policy-makers. Next to its substantive contribution, the article also showcases the methodological innovation that agent-based models can bring for a better understanding of the science–policy nexus. The model can be endlessly adapted to generate hypotheses and simulate interactions that cannot be empirically tested.



中文翻译:

给政策制定者的证据:时间和确定性问题?

本文研究了证据引入的确定性和时机如何影响政策制定者在集体审议中对证据的采用。对于专家或研究人员应如何安排向政策制定者引入不确定证据的时间,人们知之甚少。通过基于 Hegselmann-Krause 意见动态模型的计算模型,我们模拟了政策制定者如何根据新证据更新他们的意见。我们用两个例子来说明我们的模型的使用,其中时机和确定性对于政策制定很重要:情报分析师侦察潜在的恐怖活动和鸡肉食品安全检查。我们的计算表明,证据应该尽早出现以说服政策制定者,无论其确定性如何。即使证据相当确定,也无法说服所有政策制定者。除了实质性贡献之外,本文还展示了基于主体的模型可以带来的方法创新,以更好地理解科学与政策的关系。该模型可以无限地适应以生成假设并模拟无法通过经验检验的相互作用。

更新日期:2024-03-06
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