From Amsterdam to Bamako: a qualitative case study on diffusion entrepreneurs’ contribution to performance-based financing propagation in Mali
Bibliographic record
Abstract
For the past 15 years, several donors have promoted performance-based financing (PBF) in Africa for improving health services provision. European and African experts known as 'diffusion entrepreneurs' (DEs) assist with PBF pilot testing. In Mali, after participating in a first pilot PBF in 2012-13, the Ministry of Health and Public Hygiene included PBF in its national strategic plan. It piloted this strategy again in 2016-17. We investigated the interactions between foreign experts and domestic actors towards PBF diffusion in Mali from 2009 to 2018. Drawing on the framework on DEs (Gautier et al., 2018), we examine the characteristics of DEs acting at the global, continental and (sub)national levels; and their contribution to policy framing, emulation, experimentation and learning, across locations of PBF implementation. Using an interpretive approach, this longitudinal qualitative case study analyses data from observations (N = 5), interviews (N = 33) and policy documentation (N = 19). DEs framed PBF as the logical continuation of decentralization, contracting policies and existing policies. Policy emulation started with foreign DEs inspiring domestic actors' interest, and succeeded thanks to longstanding relationships and work together. Learning was initiated by European DEs through training sessions and study tours outside Mali, and by African DEs transferring their passion and tacit knowledge to PBF implementers. However, the short-time frame and numerous implementation gaps of the PBF pilot project led to incomplete policy learning. Despite the many pitfalls of the region-wide pilot project, policy actors in Mali decided to pursue this policy in Mali. Future research should further investigate the making of successful African DEs by foreign DEs advocating for a given policy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.012 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".