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Most Significant Change for Development×Theory-Based Impact Evaluation×
DziedzinaDevelopment StudiesDevelopment Studies
RodzinaProcess / pipelineProcess / pipeline
Rok powstania20052009
TwórcaRick Davies & Jess DartCarol Weiss; Howard White (3ie)
TypParticipatory, story-based monitoring and evaluation techniqueEvaluation approach / framework
Źródło pierwotneDavies, R., & Dart, J. (2005). The 'Most Significant Change' (MSC) Technique: A Guide to Its Use. CARE International, Oxfam, et al. link ↗White, H. (2009). Theory-Based Impact Evaluation: Principles and Practice. Journal of Development Effectiveness, 1(3), 271–284. DOI ↗
Inne nazwyMSC technique, Story-based monitoring, Most significant change stories, Monitoring without indicatorsTheory of Change Evaluation, Contribution Analysis, Theory-Driven Evaluation, Causal-Chain Impact Evaluation
Pokrewne44
PodsumowanieThe Most Significant Change (MSC) technique is a participatory, story-based approach to monitoring and evaluating development programmes that dispenses with predefined indicators. Developed by Rick Davies and elaborated with Jess Dart in their widely used 2005 guide, it works by systematically collecting stories of significant change from those closest to a programme and then filtering and selecting the most significant of them through deliberative panels at successive levels of the organisational hierarchy. The result is a structured, dialogical account of what stakeholders themselves judge to be the most important outcomes of an intervention.Theory-based impact evaluation evaluates a programme by first making explicit the theory of change — the causal chain of assumptions and mechanisms through which inputs are expected to produce outcomes and impacts — and then gathering evidence to test whether each link in that chain holds. Rather than treating the programme as a black box and estimating only the net effect, it asks not just whether a programme worked but why, for whom, and under what conditions. Articulated by Carol Weiss and brought into development practice by Howard White and 3ie, it complements, rather than competes with, counterfactual designs.
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