Development of a Canadian Framework for Global Health Access and Equity: Outcomes from the 2025 Global Health Access and Equity Workshop at the University of British Columbia
Bibliographic record
Abstract
The COVID-19 pandemic revealed stark inequities in access to life-saving technologies and innovations, particularly for countries in the Global South. While scientific advances were rapid, the benefits of those breakthroughs were not equitably shared, highlighting deep structural imbalances in global health governance. In response, Canadian institutions must lead by example to ensure that future innovations arising from publicly funded research are made equitably accessible. The Global Health Access and Equity Workshop, held in March 2025 by the Neglected Global Diseases Initiative at UBC, convened experts from academia, civil society, and government to identify key barriers and propose a framework for action. This viewpoint outlines the workshop’s vision, summarizes outcomes, and calls for the establishment of a Canadian framework guided by Global Access and Equity Principles (GAEP) to promote health equity globally and fulfill Canada’s moral, scientific, and policy obligations in the post-pandemic era.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.041 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.015 | 0.015 |
| Scholarly communication | 0.019 | 0.006 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 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".