Le sort des patients souffrant de troubles mentaux très graves et persistants lorsqu’il n’y a pas d’hôpital psychiatrique : étude de cas
Bibliographic record
Abstract
The Eastern Townships (Estrie) is an area of Québec which has never had a psychiatric hospital and is thus an extreme example of deinstitutionalization. How can people with the most severe mental illnesses be cared for? Does this system have harmful consequences? The authors present a case study with both qualitative and quantitative data to elucidate their questions. They found 36 patients with very severe mental illness (prevalence 12,4/100 000). This region does not send its most severely ill patients outside and generally succeeds in providing them with care and services in a network of small and medium size residential facilities. On the other hand, the authors have also been able to identify a certain drift of patients towards the correctional system ; cases with double or triple diagnosis do not easily have access to care ; through lack of an alternative, patients with potentially chronic violence often are stuck in a hospital in short stay beds (prevalence 1,6/100 000). It thus appears possible to eliminate the use of a psychiatric hospital for patients with very severe mental disorders as long as they are provided with supervised and long term care facilities (need : 10-20 places/100 000).
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".