Systematizing Policy Learning: From Monolith to Dimensions
Dunlop, Claire A.
Radaelli, Claudio M.
The field of policy learning is characterised by concept stretching and lack of systematic findings. To systematize them, we combine the classic Sartorian approach to classification with the more recent insights on explanatory typologies. At the outset, we classify per genus et differentiam – distinguishing between the genus and the different species within it. By drawing on the technique of explanatory typologies to introduce a basic model of policy learning, we identify four major genera in the literature. We then generate variation within each cell by using rigorous concepts drawn from adult education research. Specifically, we conceptualize learning as control over the contents and goals of knowledge. By looking at learning through the lenses of knowledge utilization, we show that the basic model can be expanded to reveal sixteen different species. These types are all conceptually possible, but are not all empirically established in the literature. Up until now the scope conditions and connections among types have not been clarified. Our reconstruction of the field sheds light on mechanisms and relations associated with alternatives operationalizations of learning and the role of actors in the process of knowledge construction and utilization. By providing a comprehensive typology, we mitigate concept stretching problems and aim to lay the foundations for the systematic comparison across and within cases of policy learning.
European Research Council, grant no 230267 on Analysis of Learning in Regulatory Governance, ALREG.
notes: The authors wish to express their gratitude to the Norwegian Political Science Association Annual Conference, 6 January 2010, University of Agder, Kristiansand, participants of the ‘Establishing Causality in Policy Learning’ panel at the American Political Science Association (APSA) annual meeting,2–5 September 2010,Washington DC, and the European Consortium of Political Research (ECPR) Joint Sessions, St Gallen, 12–17 April 2011, workshop 2. Dunlop and Radaelli gratefully acknowledge the support of the European Research Council, grant on Analysis of Learning in Regulatory Governance, ALREG, http://centres.exeter.ac.uk/ceg/research/ALREG/index.php.
The definitive version is available at www.blackwell-synergy.com and also from DOI: 10.1111/j.1467-9248.2012.00982.x
Place of publication