An Egalitarian Argument in Favour of Free Access to Healthcare and Rationing
Bibliographic record
Abstract
La pensée égalitariste a traditionnellement promu l’idéal d’un système de santé universel, gratuit et accessible à tous les membres de la société. J’appuie cette position en répliquant tout d’abord à la critique qui prétend que les riches tireraient plus d’avantages que les pauvres de la gratuité du système de santé. J’ouvre ensuite la réflexion sur ce qui me semble être un enjeu crucial pour l’avenir des systèmes modernes de santé : le rationnement de l’offre. Cette idée ne plaît généralement pas à la population, aux décideurs politiques et à de nombreux égalitaristes. Je considère pourtant que les principaux arguments invoqués contre le rationnement sont incohérents ou faussement égalitaristes. La gratuité des services de santé n’est pas incompatible avec la limitation de l’offre publique.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.029 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 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".