Taking ‘Third World’ Lives Seriously: Decolonising Global Health Governance to Promote Health Capabilities in the Global South
Bibliographic record
Abstract
Behind glib claims of universalism in global health, evidenced by the push for universal health coverage in the Sustainable Development Goals 2030 (SDGs), lies an uncomfortable truth about the unequal, uneven and broken system of the existing framework for global health governance. A situation made more evident by the behaviour of powerful states of the Global North at the height of the Covid-19 pandemic through the hoarding of vaccines, refusal to accommodate waivers to the Trade-Related Aspects of Intellectual Property Rights (TRIPS) regime to allow cheaper versions of the Covid-19 vaccines to be manufactured for the Global South and the preference for securitisation over solidarity in the response to the pandemic. The rhetoric of “vaccine apartheid” was deployed by WHO Director General to describe this lack of solidarity by Global North States (particularly in the context of vaccines procurement). However, this paper argues contrarily that the colonial foundations of the current framework for global health governance, which does not take Third World lives as seriously as those of citizens of the West, has functioned exactly as designed. This has led to the “othering” of Third World peoples, generating pathologies of suffering and vulnerabilities in their encounter with global health governance frameworks. Informed by critical Third World Approaches to International Law (TWAIL) this paper makes the case for decolonising existing frameworks for global health governance to promote health capabilities in the Global South.
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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 | 0.018 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.057 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.001 | 0.017 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".