Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Participatory Evaluation× | Most Significant Change× | |
|---|---|---|
| Область | Public Policy | Public Policy |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1998 | 2005 |
| Автор метода≠ | J. Bradley Cousins & Elizabeth Whitmore | Rick Davies & Jess Dart |
| Тип≠ | Collaborative, stakeholder-engaged evaluation approach | Participatory, story-based monitoring and evaluation technique |
| Основополагающий источник≠ | Cousins, J. B., & Whitmore, E. (1998). Framing participatory evaluation. New Directions for Evaluation, 1998(80), 5–23. DOI ↗ | Davies, R., & Dart, J. (2005). The 'Most Significant Change' (MSC) Technique: A Guide to Its Use. link ↗ |
| Другие названия≠ | Collaborative Evaluation, Stakeholder-Based Evaluation, Practical Participatory Evaluation | MSC, MSC Technique, Story-Based Monitoring, Davies-Dart Most Significant Change |
| Связанные | 4 | 4 |
| Сводка≠ | Participatory evaluation is a family of approaches in which stakeholders — program staff, beneficiaries, community members — are engaged as active partners in conducting the evaluation rather than as passive subjects of it. In their influential 1998 framing, J. Bradley Cousins and Elizabeth Whitmore distinguished two streams: practical participatory evaluation, oriented to improving program decisions and use, and transformative participatory evaluation, oriented to empowerment and social justice. What unites them is shared control of the inquiry, but they vary along dimensions of who participates, how much control they hold, and how deeply they are involved. | The Most Significant Change (MSC) technique is a participatory, story-based approach to monitoring and evaluation developed by Rick Davies and refined with Jess Dart. It involves the systematic collection of stories of significant change from the field and the deliberative selection of the most significant of these by panels of stakeholders. There are no predefined indicators; instead, value judgements about what change matters most are made transparently by those involved, making MSC especially suited to capturing unexpected and qualitative outcomes in complex programs. |
| ScholarGateНабор данных ↗ |
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