De la neurologie à la psychanalyse : évolutions et continuité du modèle de prise en charge psychothérapeutique du Sanatorium Prévost
Bibliographic record
Abstract
Since its opening, in July 1919, Dr. Albert Prévost's sanatorium tried to stand out from others' health care institutions, by offering a therapeutic mainly based on psychotherapy. Far from big and overcrowded asylums or physical therapies, as electrotherapy, used in others private clinics, Dr. Albert Prévost (1881-1926) wanted an institution where he could practice this new form of care he had discovered in Paris and which was yet more and more in vogue in the US. This will to keep the sanatorium at the avant-garde of the science of spirit remained, even after Prevost's death. Indeed, the Sanatorium Prévost, which became the Institut Albert-Prévost in 1955, was during all its existence, a space of experimentation and valorization of the psychiatric sciences' latest discoveries. This is what we want to demonstrate in this paper by following the path and realisations of the sanatorium main physicians, from the founders of francophone Québec neurology like Albert Prévost, Edgar Langlois (1893-1941), Roma Amyot (1899-1980) and Jean Saucier (1899-1968) to the first Québec psychoanalysts Karl Stern (1906-1975), Victorin Voyer (1917-1975) or Camille Laurin (1922-1999). We will yet see that the Sanatorium Albert-Prévost has always been at the cutting edge of psychiatric science, while keeping its own psychotherapeutic approach, centered on the patients' care, on which it had been founded.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.049 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".