Abstract
Generative experimentation is increasingly used in public policymaking, especially in response to wicked policy problems. A policy solution is refined within its context and informed by feedback from its users. Studies reporting on these approaches, however, rarely consider the role of evaluation and the nature and goals of knowledge produced. This article addresses evaluation in such contexts. We present a case study of a living lab that combined theory-driven and developmental evaluation, and, responding to contradictory pressures, aimed to generate both actionable and academic knowledge to improve asylum seeker reception. We describe how we addressed these diverging demands and the resulting tensions in a politically charged and substantively insecure policy context. We conclude that evaluation should be an explicit part of the broader design concept, and while generative experimenting can produce actionable learning, evaluation should also aim for academic learning, in a manner that is both democratic and robust.
Original language | English |
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Pages (from-to) | 347-363 |
Number of pages | 17 |
Journal | Evaluation |
Volume | 27 |
Issue number | 3 |
DOIs | |
Publication status | Published - Jul 2021 |
Bibliographical note
Funding Information:The authors would like to thank the partners, stakeholders and users of the Utrecht Refugee Launch Pad for their openness during the evaluation. They thank their colleague Yousra Rahmouni Elidrissi for helping out with the French translation of the abstract. They also thank the anonymous reviewers of Evaluation. Their feedback has made all the difference. The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: This work was supported by the European Regional Development Fund through the Urban Innovative Actions Initiative (grant number UIA-01-131-URLP).
Publisher Copyright:
© The Author(s) 2021.
Keywords
- developmental evaluation
- generative experimenting
- living lab
- policy design
- theory-driven evaluation