The equity group: Supporting Cochrane's social responsibility of improving health equity
Bibliographic record
Abstract
Introduction: Health equity is a moral and ethical imperative for clinicians, researchers, policymakers, and all who use health research. Both Cochrane and the Campbell Collaboration have focused on health equity for many years. Methods: The new Equity Group will continue and expand this work by designing a program of projects aiming to (1) promote equity in the evidence base, (2) ensure equitable processes for stakeholder engagement, (3) produce high-priority, equity-focused evidence syntheses, (4) build capacity for equity design, analysis, and reporting, and (5) promote equity in implementation tools. Results: We will build on our current network of collaborators and create a group structure striving to recruit across the PROGRESS-Plus characteristics. Conclusion: We invite readers to join our cause and contribute wherever they are able. Together, we can help Cochrane achieve its social responsibility of improving health equity at a planetary level.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.156 | 0.136 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads 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".