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Policy Failures and Achievements in the Knowledge Domain

Policy Analysis
Public Policy
Knowledge
P306
Meng-Hsuan Chou
University of Helsinki
Pauline Ravinet
Institut d'Études Politiques de Lille

Building: Faculty of Arts, Floor: 1, Room: FA131

Friday 11:00 - 12:40 CEST (09/09/2016)

Abstract

Higher education, research, and innovation policy domains have undergone dramatic changes in recent decades. Embedded in these changes are assumptions about failure and learning, and the belief that the ‘new and novel’ would ‘right’ the ‘wrongs’. Yet our understanding of the failure-learning mechanism remains under-developed. Indeed, social scientists often conflate three distinct types of failure—politics, policy, and instruments—in their analyses. The consequences of failure also remain an on-going question. Do all failures lead to sizeable policy change or to less dramatic reforms or tinkering? Or to no actions at all? While spectacular policy failures are historically memorable, the subtle failures that trigger incremental changes, or indeed the acknowledgement of their very existence, are less examined. For instance, what are the modes of institutional change? To what extent do these changes lead to reform? The above observations raise several questions about failures and learning, as well as achievements, in knowledge policymaking which scholars of public policy, comparative politics, international relations, and social sciences in general have only begun to address. These include, but are not limited to: why do some policy failures lead to institutional collapse or abandonment of policy ideas, while others do not? Indeed, why are some policy ideas more sticky than others? To what extent do policy failures shape the institutional design of international, regional, and national, and sub-national decision-making? Is there a cycle of failure and learning involved in the everyday functioning of political and knowledge institutions (e.g. universities and research institutes)? And, if so, how do we first detect and then determine which ‘failure-learning’ mechanism is weak and which one is robust?

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