Can a Focus on Equity, Diversity and Inclusion Transform Health Service Research?
Bibliographic record
Abstract
The new Canadian Institutes of Health Research - Institute of Health Services and Policy Research's Strategic Plan 2021-2026 (CIHR IHSPR 2021) holds potential. Barriers are anticipated, including that commitments to equity, diversity and inclusion (EDI) are tokenistic. This commentary provides four recommendations to support EDI as transformative. First, EDI must start with an honest history of the role of institutions in upholding injustice. Second, performative EDI must be replaced by changes in money, power and resources. Third, data collection alone must never be the end goal of EDI. And fourth, for EDI to be transformative, it must be grounded in praxis, taking direction from communities and movements seeking justice.
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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 | 0.281 | 0.279 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.020 | 0.139 |
| Scholarly communication | 0.047 | 0.060 |
| Open science | 0.009 | 0.026 |
| Research integrity | 0.034 | 0.065 |
| Insufficient payload (model declined to judge) | 0.006 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".