Bibliographic record
Abstract
The World Health Organization (WHO), as the most prominent global health institution as a specialized agency of the United Nations, has expressed concern for health equity as part of its mandate, “the attainment by all peoples of the highest possible level of health”. However, there is a lack of clarity around the WHO’s fundamental definition and conceptualization of equity. Through drawing on the WHO’s Urban Health Equity Assessment and Response Tool (Urban HEART) as an illustrative case, the aim is to determine how the WHO operationalizes equity in practice. Preliminary findings suggest there is no consistent understanding of what the goal of Urban HEART is. This research has direct implications for practice: not only can the findings be applied to other global health work that seeks to improve equity, but the WHO is planning to reinstate Urban HEART. As such, this research may be beneficial in guiding these plans. Further, the findings yield an important consideration for global and public health policy and practice more broadly: the need to clarify objectives around equity (e.g. because how equity is defined determines the work undertaken and the populations served).
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 | 0.035 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.005 | 0.033 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.007 | 0.013 |
| 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; 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".