Bibliographic record
Abstract
RESUMEN La equidad es uno de los principios fundamentales de los sistemas sanitarios públicos. En España la asignación de recursos sanitarios ha seguido un criterio puramente capitativo por lo que se plantea la idoneidad de repasar los métodos empleados en otros países, con el objeto de encontrar experiencias comparadas útiles que concreten la noción de equidad en el reparto de los recursos sanitarios. Para ello repasamos tanto métodos asignativos basados en fórmulas de medición de las necesidades de gasto sanitario, casos del Reino Unido y Nueva Zelanda , como asignaciones mediante transferencias finalistas desde el gobierno central hacia las administraciones territoriales, concretados en los casos de Canadá y Australia. ABSTRACT The fairness is one of the fundamental principles of the sanitary systems public. In Spain the allocation of sanitary resources has followed a criterion purely per capita reason why the suitability considers to review the methods used in other countries with the intention of finding compared experiences useful that they make specific the notion of fairness in the distribution of the sanitary resources. For it we reviewed methods based on formulas of measurement of the necessities of sanitary cost, cases of the United Kingdom and New Zealand, and allocations by means of transferences finalists from the central government towards the territorial administrations, made specific in the cases of Canada and Australia.
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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 | 0.010 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.018 | 0.021 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".