Opening up the black box: looking for a more capacious version of capacity in global health partnerships
Bibliographic record
Abstract
Some versions of capacity building construe the goal of North‒South partnerships as rendering African laboratories, doctors, scientists, and universities indistinguishable from their counterparts in wealthier nations. The specificities, histories, peculiarities, or inner workings of African institutions and individuals are black-boxed ‒ no one needs to know about them. This article draws on research at Malawi’s College of Medicine and the work of other social scientists and historians to sketch out a more capacious model of capacity, one in which capacity building is grounded in specificity, attends to material difference, is flexible and innovative, and involves as much learning as teaching. This model of capacity building requires consideration of areas in which the Northern partners in “global health” can be brought to the level of their colleagues in Africa.
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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 | 0.040 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.020 | 0.138 |
| Scholarly communication | 0.031 | 0.072 |
| Open science | 0.003 | 0.028 |
| Research integrity | 0.011 | 0.019 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".