Generalizability and transportability puzzles in Development Research in Africa
Should policy makers rely on less rigorous evidence from a local context or more rigorous evidence from elsewhere? Should a new experiment always be done locally before a program is scaled up? Must an identical program or policy be replicated a specific number of times before it is scaled up? How can we transport evidence from one context to the others?
A great and timely topic. Adapting relevant external policies to local contexts is indeed a valuable approach, but it often presents crucial implementation challenges. The most effective way to transfer evidence or policies across contexts is by ensuring strong local ownership by closely engaging all stakeholders who are directly impacted by the policy. Such inclusive engagement not only facilitates smoother acceptance but also enhances successful implementation and scale-up.
Excellent point. Strong local ownership is often the bridge between evidence and effective implementation.
Even when external policies are backed by rigorous evidence, successful adaptation depends on how well they are understood, accepted, and shaped by local stakeholders. Engaging communities, implementers, policy makers, and affected populations early helps ensure relevance, trust, and sustainability.
Inclusive stakeholder involvement not only improves acceptance but also helps identify contextual barriers, necessary adaptations, and practical pathways for scale-up.
In many cases, the success of policy transfer depends as much on participation and ownership as it does on the strength of the original evidence.
Excellent questions. Policy makers often must balance rigorous evidence from elsewhere with local relevance.
Strong external evidence can show what works, but local context—such as culture, systems, resources, and implementation capacity—matters greatly. Less rigorous local evidence may be more context-specific but often comes with greater uncertainty.
Rather than choosing one over the other, the best approach is usually to:
- Use rigorous external evidence as a foundation
- Assess how similar the local context is
- Use local data, pilots, or phased implementation to test fit
A new local experiment is not always required before scaling, but local validation is often important.
There is also no fixed number of replications needed before scale-up. What matters more is:
- Strength of existing evidence
- Contextual similarity
- Feasibility
- Risk and urgency
The key question is not just “Does it work?” but “Will it work here, for this population, under these conditions?”
Successful policy scaling depends on combining evidence with thoughtful local adaptation.