Vaccine nationalism will persist: global public goods need effective engagement of global citizens
Bibliographic record
Abstract
Covid-19 presents a unique opportunity to transform democratic engagement in the governance of global public goods. In this paper, I describe a global public goods framework and how it relates to Covid-19 vaccines, and summarize some of the global responses to Covid-19. I discuss some of the global threats to health and prosperity posed by the inequitable distribution of vaccines, and propose transformative thinking to democratically engage citizens in the governance of global public goods. In recent years, public-private partnerships and philanthropic organizations have successfully stepped in to help international organizations like the UN and WHO provide global public goods, but they are not democratically elected or publicly accountable. Global public goods are critical to addressing Covid-19, future pandemic preparedness, global health policy, health equity, and the unfolding climate crisis. To make us more resistant and resilient to future global health crises we need transformative thinking to democratically engage global citizens. We need to lay the foundations for a 'global social contract' on global public goods.
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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 | 0.023 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.024 |
| Scholarly communication | 0.019 | 0.024 |
| Open science | 0.001 | 0.019 |
| Research integrity | 0.010 | 0.017 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".