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Policy Learning in Comparative Policy Analysis

Dunlop, CA; Radaelli, CM; (2020) Policy Learning in Comparative Policy Analysis. Journal of Comparative Policy Analysis: Research and Practice 10.1080/13876988.2020.1762077. (In press). Green open access

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Abstract

This article explores how policy learning can improve comparative policy analysis by focusing on causality in learning processes. After summarizing the comparative credentials of the policy learning literature, the article outlines a framework of four learning modes, relating it to three approaches of causality: deterministic, probabilistic, and set-theoretic. It then builds on this to explore different approaches to causation and learning in relation to: policy change, political contexts, and, finally, the temporal and spatial dimensions of comparative policy analysis. The article concludes by showing how these challenges are addressed and suggesting implications for further research.

Type: Article
Title: Policy Learning in Comparative Policy Analysis
Open access status: An open access version is available from UCL Discovery
DOI: 10.1080/13876988.2020.1762077
Publisher version: https://doi.org/10.1080/13876988.2020.1762077
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: causation, causal mechanisms, comparative policy analysis, policy change, policy learning
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL SLASH
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Political Science
URI: https://discovery.ucl.ac.uk/id/eprint/10100410
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