Global health governance: we need innovation not renovation
Bibliographic record
Abstract
Although the global health community widely accepts that WHO, as currently configured, is no longer fit-for-purpose, commentators cling to renovation (‘reform’), rather than innovation, at the expense of a global health governance system that reflects the needs of a very changed world.Collective action in a globalised world requires institutions that look very different from what we currently have. Rather than the renovation of outdated institutional forms—which are closed, territorially fixed and hierarchical—we need to harness innovations such as social networks, open-source systems and the sharing economy.One of the biggest forms of institutional innovation more broadly is ‘network governance’, by which collective action is achieved through interconnected institutions spanning government, business and civil society.
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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 | 0.053 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.071 |
| Scholarly communication | 0.019 | 0.039 |
| Open science | 0.006 | 0.014 |
| Research integrity | 0.054 | 0.058 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".