Les infirmières psychiatriques témoins d’un mouvement d’humanisation au cours des premières et deuxièmes vagues de la désinstitutionnalisation au Québec (1960-1990)
Bibliographic record
Abstract
Introduction : This study examines the humanization movement at the Saint-Jean-de-Dieu psychiatric hospital between the 1960s and the 1990s.Context : Conducting a historiography of psychiatric deinstitutionalization in Quebec during the twentieth century shows that the institution was a place of social control and, above all else, a place where psychiatric patients were neglected and dehumanized.Objective : While the historiography since the 1960s has focused on a largely one-dimensional and critical reading of the way in which deinstitutionalization took place in Quebec, I have instead chosen to focus on the changes that took place within the Quebec hospital's walls.Method : In addition to the medical records of the patients who were interned in 1961, I conducted interviews to examine the experiences and emotions of nurses who worked in the psychiatric hospital between the 1960s and 1990s.Results : The examination of medical records revealed patients' reluctance and resistance to reintegrate into society. The interviews with nurses revealed that they often felt close to their patients.Discussion : The words and memories of nurses enrich and deepen the complexity of the history of psychiatric nursing practices, extend the existing historiography, and open new avenues for research in the field.Conclusion : The deinstitutionalization movement promoted mental health policies that transformed the old psychiatric hospital. This new analytical approach contributed to renewing the history of psychiatric nursing practices.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".