পদ্ধতির তুলনা করুন

	Ex-Ante Policy Appraisal	বাস্তববাদী সংশ্লেষণ
ক্ষেত্র	Public Policy	প্রমাণ সংশ্লেষণ
পরিবার	Process / pipeline	Process / pipeline
উদ্ভবের বছর	2022	2005
প্রবর্তক	Public-finance appraisal tradition; codified by HM Treasury (Green Book)	Ray Pawson (2005)
ধরন	Structured ex-ante appraisal of policy options	Framework
মৌলিক উৎস	HM Treasury (2022). The Green Book: Central Government Guidance on Appraisal and Evaluation. London: HM Treasury.	Pawson, R., Greenhalgh, T., Harvey, G., & Walshe, K. (2005). Realist review—a new method of systematic review designed for complex policy and programme evaluation. Journal of Health Services Research & Policy, 10(S1), 21–35.
অপর নাম	Policy Appraisal, Options Appraisal, Green Book Appraisal	Realist Review, CMO Configuration, Mechanism-Based Synthesis
সম্পর্কিত	4	1
সারসংক্ষেপ	Ex-ante policy appraisal is the structured assessment of the costs, benefits, risks and trade-offs of alternative options for achieving a policy objective, carried out before a decision is taken. Codified in guidance such as the UK Treasury's Green Book, it provides a disciplined framework for deciding whether to intervene and, if so, how — by establishing the rationale and objectives, generating and narrowing a range of options, appraising each against a counterfactual, and recommending the option that offers best value for public money. Appraisal is the forward-looking complement to ex-post evaluation, which judges interventions after they have run.	Realist synthesis is a theory-driven, interpretive method for evidence synthesis developed by Ray Pawson (2005) that focuses on understanding HOW and WHY interventions work, rather than WHETHER they work. Grounded in realist philosophy, realist synthesis examines Context-Mechanism-Outcome (CMO) configurations: how specific contextual conditions activate mechanisms that produce outcomes. Unlike traditional systematic reviews, which typically answer 'Does intervention X reduce outcome Y?', realist synthesis asks 'Under what conditions, through what mechanisms, for which populations does X work?' This approach is particularly valuable for complex interventions (policies, programs, multi-component treatments) where effectiveness varies dramatically across contexts, and for understanding why interventions succeed in some settings but fail in others.