The political origins of health inequity: prospects for change
Bibliographic record
Abstract
Despite large gains in health over the past few decades, the distribution of health risks worldwide remains extremely and unacceptably uneven. Although the health sector has a crucial role in addressing health inequalities, its eff orts often come into confl ict with powerful global actors in pursuit of other interests such as protection of national security, safeguarding of sovereignty, or economic goals. This is the starting point of The Lancet-University of Oslo Commission on Global Governance for Health. With globalisation, health inequity increasingly results from transnational activities that involve actors with diff erent interests and degrees of power: states, transnational corporations, civil society, and others. The decisions, policies, and actions of such actors are, in turn, founded on global social norms. Their actions are not designed to harm health, but can have negative sideeff ects that create health inequities. The norms, policies, and practices that arise from global political interaction across all sectors that aff ect health are what we call global political determinants of health.
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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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.021 |
| Scholarly communication | 0.012 | 0.014 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.017 | 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".