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Collaborative Governance Assessment×Realist Evaluation×
Lĩnh vựcPublic AdministrationPublic Policy
HọProcess / pipelineProcess / pipeline
Năm ra đời20081997
Người khởi xướngChris Ansell & Alison GashRay Pawson & Nick Tilley
LoạiProcess-based governance assessment frameworkTheory-driven, generative evaluation approach
Công trình gốcAnsell, C., & Gash, A. (2008). Collaborative Governance in Theory and Practice. Journal of Public Administration Research and Theory, 18(4), 543–571. DOI ↗Pawson, R., & Tilley, N. (1997). Realistic Evaluation. London: SAGE Publications. ISBN: 9780761950097
Tên gọi khácCollaborative Governance Analysis, Ansell-Gash Governance Framework, Multi-Stakeholder Governance AssessmentRealistic Evaluation, Theory-Driven Realist Evaluation, CMO Configuration Analysis, Pawson-Tilley Evaluation
Liên quan44
Tóm tắtCollaborative governance assessment is a framework for analysing arrangements in which public agencies and non-state stakeholders deliberate together to make or implement public policy by consensus. Synthesised by Chris Ansell and Alison Gash in their 2008 article from a meta-analysis of over a hundred cases, it identifies the starting conditions, institutional design and facilitative leadership that feed into an iterative collaborative process and ultimately shape outcomes. The framework treats collaboration not as a single event but as a cycle of face-to-face dialogue, trust-building, shared understanding and intermediate commitments. Its purpose is to explain why some multi-stakeholder partnerships succeed while others stall or collapse.Realist evaluation is a theory-driven approach to evaluating programs and policies that asks not simply 'does it work?' but 'what works, for whom, in what circumstances, and why?'. Developed by Ray Pawson and Nick Tilley in their 1997 book Realistic Evaluation, it treats interventions as theories incarnate: programs offer resources or opportunities that trigger underlying mechanisms of reasoning and response in participants, and those mechanisms only fire in particular contexts. The unit of analysis is the Context-Mechanism-Outcome (CMO) configuration, and the goal is to build and refine middle-range theory that explains differential outcomes across settings.
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