Abstract
Despite 20 years of increasing acceptance, implementing complexity-appropriate methods for ex-post evaluation remains a challenge: instead of focusing on complex interventions, methods need to help evaluators better explore how policies (no matter how simple) take place in real-world, open, dynamic systems where many intertwined factors about the cases being targeted affect outcomes in numerous ways. To assist in this advance, we developed case-based scenario simulation, a new visually intuitive evaluation tool grounded in a data-driven, case-based, computational modelling approach, which evaluators can use to explore counterfactuals, status-quo trends, and what-if scenarios for some potential set of real or imagined interventions. To demonstrate the value and versatility of case-based scenario simulation we explore four published evaluations that differ in design (cross sectional, longitudinal, and experimental) and purpose (learning or accountability), and present a prospective view of how case-based scenario simulation could support and enhance evaluators’ efforts in these complex contexts.
| Original language | English |
|---|---|
| Pages (from-to) | 116-137 |
| Number of pages | 22 |
| Journal | Evaluation |
| Volume | 27 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2021 |
Keywords
- case-based methods
- computational social science
- evaluation
- policy
- scenario analysis
- social complexity
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