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Causality is good for practice: policy design and reverse engineering
Policy Sciences ( IF 5.121 ) Pub Date : 2023-02-01 , DOI: 10.1007/s11077-023-09493-7
Simone Busetti

Relevance to practice is an open issue for scholars in public policy and public administration. One major problem is the need to produce knowledge that can guide practitioners designing and implementing public interventions in specific contexts. This article claims that investigating the causal mechanisms of policy programs—i.e., modeling why and how they produce outcomes—can contribute to such knowledge. In this regard, mechanisms offer essential information to guide practitioners when replicating, adjusting, and designing interventions. Unfortunately, not all models of mechanisms can inform practice. The article proposes a strategy for design research and practice inspired by reverse engineering: selecting successful programs, causal modeling, assessing the target context, and designing. Scholars should model mechanisms by identifying the program and non-program elements that contribute to the outcome of interest and abstracting their causal powers. Practitioners can use these models, diagnose their target context, and adjust designs to deal with context-specific problems. The proposed research agenda may enhance orientation to practice and offer a middle ground between the search for abstract, general relationships, and single-case analyses.



中文翻译:

因果关系有利于实践:政策设计和逆向工程

对于公共政策和公共行政学者来说,与实践的相关性是一个悬而未决的问题。一个主要问题是需要产生能够指导从业者 在特定情况下设计和实施公共干预措施的知识。本文声称,研究政策计划的因果机制——即对它们产生结果的原因和方式进行建模——可以有助于获得这些知识。在这方面,机制提供了重要信息来指导从业者复制、调整和设计干预措施。不幸的是,并非所有机制模型都能指导实践。本文提出了一种受逆向工程启发的设计研究和实践策略:选择成功的程序、因果建模、评估目标环境和设计。学者们应该通过识别有助于产生感兴趣结果的程序和非程序要素并抽象出它们的因果力量来建立机制模型。从业者可以使用这些模型,诊断他们的目标环境,并调整设计以处理特定环境的问题。拟议的研究议程可以增强实践导向,并在寻找抽象、一般关系和单例分析之间提供中间立场。

更新日期:2023-02-01
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