手法を比較

	Citizen Participation Assessment	Realist Evaluation
分野	Public Administration	Public Policy
系統	Process / pipeline	Process / pipeline
提唱年	1969	1997
提唱者	Sherry R. Arnstein	Ray Pawson & Nick Tilley
種類	Survey- and rubric-based participation assessment	Theory-driven, generative evaluation approach
原典	Arnstein, S. R. (1969). A Ladder of Citizen Participation. Journal of the American Institute of Planners, 35(4), 216–224.	Pawson, R., & Tilley, N. (1997). Realistic Evaluation. London: SAGE Publications. ISBN: 9780761950097
別名	Public Participation Assessment, Ladder of Participation Analysis, Citizen Engagement Measurement, Participatory Governance Assessment	Realistic Evaluation, Theory-Driven Realist Evaluation, CMO Configuration Analysis, Pawson-Tilley Evaluation
関連	4	4
概要	Citizen participation assessment is a method for evaluating how, and how genuinely, members of the public are involved in government decisions that affect them. Its conceptual backbone is Sherry Arnstein's 1969 'ladder of citizen participation,' which arranged forms of involvement on eight rungs ranging from manipulation and therapy (non-participation) through informing, consultation and placation (tokenism) up to partnership, delegated power and citizen control (degrees of citizen power). The assessment combines this ladder with surveys of participants and documentary review to classify a participation process by its level of real power-sharing, judge who is included, and diagnose whether engagement is substantive or merely symbolic.	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.