Evaluating program planning using an equity framework
Bibliographic record
Abstract
To plan for an expansion of healthcare services in newly developed neighbourhoods, a planning initiative was conducted to better understand the needs of the population. Ensuring equity of care was identified as a priority for this initiative. To evaluate how closely the planning adhered to the principles of health equity, we applied Ontario Health's Equity, Inclusion, Diversity, and Anti-Racism Framework to determine which areas of action were successfully addressed, and which areas of action require further focus. The framework contains 11 components, each delineating a key area of action. Using this framework helped identify areas where the principles of equity were well addressed, as well as pointing to additional areas where further efforts are required. Healthcare organizations must take a leadership role in advancing health equity by planning, delivering, improving, and advocating for the services and systematic changes that will allow its local community members to realize their highest attainable standard of health. Using such a framework can help develop strategic approaches to advancing equity.
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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 | 0.129 | 0.150 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".