De la psychanalyse à la psychothérapie psychodynamique à Albert-Prévost
Bibliographic record
Abstract
Objectives The goal of this paper was first to review the contributions of Dr. Camille Laurin in the development of psychiatric services at Albert-Prévost, and more specifically the role he played in promoting psychoanalysis as a modality of thinking which informs the various therapeutic measures with psychic caring and therapeutic relationship as a main focus. Psychoanalysis and psychodynamic psychotherapy are currently taught; this teaching is informed by the contemporary challenges posed by the evidence-based medicine, the neuroscience and the recent technological developments in the field of communication. Methods In the first section of this article, a biographical research was completed. In the second section, a brief review of literature was conducted for each topic discussed. Results Dr. Camille Laurin played a major role in the development of psychoanalytic thinking at Albert-Prévost. His heritage is still alive, mainly in the different courses and training activities offered at the Psychotherapy Center of this institution. The efficacy of the psychodynamic psychotherapy as a treatment has now been confirmed for many years. Even if neuroscience and psychoanalysis are two totally different fields of investigation, each of those disciplines can benefit from an open dialogue. The development of new communication technologies and artificial intelligence could eventually modify the practice of psychotherapy. Conclusion Psychoanalysis in its basic theoretical tenets are still widely taught to psychiatric students who mostly apply its principles when they practice psychodynamic psychotherapy. Dr. Camille Laurin played a significant role in promoting this approach at Albert-Prévost and more generally at the Department of psychiatry and addictions of the Université de Montréal.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".