Bibliographic record
Abstract
This issue has a typically wide coverage of locations and topics.The first, at the 'macro' level, explores the issue of NHI in Saudi Arabia.The second, at the 'micro' level, analyses the unit costs of public hospitals and primary care centres.The third, at the macro level, examines the role of US AID in Bolivia over 40 years, from a critical perspective.The fourth, at the micro level, examines the conditions for a successful public health programme concerned with HIV in India.The fifth explores the use of 'outcome mapping' in changing the model of care delivery in a Canadian province.Moving to the online articles, the sixth explores accreditation-in the context of primary care in the Lebanon.The seventh is also concerned with primary care, but this time in terms of the effect of user fees upon quality and utilization in Afghanistan.Continuing with utilization in terms of access by the poor, the eighth article examines policy and reality regarding exemptions from charges in Tanzania.The final article looks at monetary incentives in a different sense-as motivation for health workers engaged in treating patients with tuberculosis in rural China.
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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.075 | 0.052 |
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".