Revealing power in truth Comment on "Knowledge, moral claims and the exercise of power in global health"
Bibliographic record
Abstract
Jeremy Shiffman's editorial appropriately calls on making all forms of power more apparent and accountable, notably productive power derived from expertise and claims to moral authority. This commentary argues that relationships based on productive power can be especially difficult to reveal in global health policy because of embedded notions about the nature of power and politics. Yet, it is essential to recognize that global health is shot through with power relationships, that they can take many forms, and that their explicit acknowledgement should be part of, rather than factored out of, any reform of global health governance.
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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 | 0.016 | 0.069 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.020 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.048 | 0.043 |
| Insufficient payload (model declined to judge) | 0.003 | 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".