COVID-19 vaccine apartheid and the failure of global cooperation
Bibliographic record
Abstract
The equitable distribution of COVID-19 vaccines is one of the most important tests of global cooperation that the world has faced in recent decades. Collectively, global leaders failed that crucible abysmally, creating a 'vaccine apartheid' that divided the world according to income into countries with widespread access and those without. Why, given that leaders were fully aware of the risks and injustice of vaccine inequity, did governments of wealthy countries hoard doses, impede the expansion of vaccine manufacturing and otherwise prevent equitable access to vaccines? We argue that their decisions to act selfishly are best explained by governments' accountability to domestic constituencies, their lack of leadership and commitment to multilateralism and their adoption of short-term perspectives, as well as their unwillingness to curb the influence of profit-oriented global pharmaceutical companies and, to a certain extent, of an additional private actor, the Bill and Melinda Gates Foundation.
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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 | 0.017 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.023 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".