Les usagers NSA, un problème de solidarité?
Bibliographic record
Abstract
Alors que les hôpitaux sont saturés au Québec, de nombreux lits demeurent occupés par des usagers NSA, soit des usagers dont l’état de santé ne requiert plus de soins hospitaliers. La présence de ces usagers dans les hôpitaux affecte non seulement le bien-être de ces derniers, mais aussi celui de l’ensemble de la population. Cette situation met en lumière l’interdépendance humaine dans le contexte des usagers NSA. La valeur de la solidarité en santé publique permet de reconnaître cette interdépendance humaine et s’avère donc essentielle pour orienter les interventions en santé. En tenant compte du contexte actuel des usagers NSA et du portrait préoccupant de la situation, on peut se questionner à savoir si la valeur de la solidarité est suffisamment prise en compte pour baliser les interventions en santé concernant ces usagers. Cet essai propose d’analyser le cadre légal entourant les usagers NSA à travers le prisme de la solidarité, soit, plus particulièrement, la solidarité de l’État envers les usagers et celle des usagers envers la collectivité.
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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".