Pandemics, intellectual property and ‘our economy’: A worldview analysis of Canada’s role in compromising global access to COVID-19 vaccines
Bibliographic record
Abstract
Despite self-congratulatory rhetoric, Canada compromised COVID-19 vaccine equity with policies impeding a proposed global waiver of vaccine intellectual property (IP) rules. To learn from Canada’s vaccine nationalism we explore the worldview – a coherent textual picture of the world – in a sample of Government of Canada communications regarding global COVID-19 vaccine sharing. Analysed documents portray risks and disparities as unrelated to the dynamics and power relations of the Canadian and international economies. Against this depoliticised backdrop, economic growth fueled by strict IP rules and free trade is advanced as the solution to inequities. Global vaccine access and distribution are pursued via a charity-focused public-private-partnership approach, with proposals to relax international IP rules dismissed as unhelpful. Rather than a puzzling lapse by a good faith ‘middle power’, Canada’s obstruction of global COVID-19 vaccine equity is a logical and deliberate extension of dominant neoliberal economic policy models. Health sector challenges to such models must prioritise equity in global pandemic governance via politically assertive and less conciliatory stances towards national governments and multilateral organisations. Mobilisation for health equity should transform the overall health-damaging macroeconomic model, complementing efforts based on specific individual health determinants or medical technologies.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.024 | 0.016 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".