Informing Canada’s Health System Response to COVID-19: Priorities for Health Services and Policy Research
Bibliographic record
Abstract
To inform Canada's research response to COVID-19, the Canadian Institutes of Health Research's Institute of Health Services and Policy Research (IHSPR) conducted a rapid-cycle priority identification process. Seven COVID-19 priorities for health services and policy research were identified: system adaptation and organization of care; resource allocation decision-making and ethics; rapid synthesis and comparative policy analysis of the COVID-19 response and outcomes; healthcare workforce; virtual care; long-term consequences of the pandemic; and public and patient engagement. Three additional cross-cutting themes were identified: supporting the health of Indigenous Peoples and vulnerable populations, data and digital infrastructure, and learning health systems and knowledge platforms. IHSPR hopes these research priorities will contribute to the broader ecosystem for collective research investment and action.
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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 | 0.183 | 0.157 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.029 | 0.016 |
| Scholarly communication | 0.032 | 0.010 |
| Open science | 0.008 | 0.019 |
| Research integrity | 0.014 | 0.021 |
| Insufficient payload (model declined to judge) | 0.011 | 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".