Les programmes de premier épisode de schizophrénie et une médecine fondée sur les données factuelles : un cas de syndrome des habits de l’empereur 1 ?
Bibliographic record
Abstract
In this essay, the author states that the first onset psychoses clinics described in many articles of this special issue of Santé mentale au Québec are not as evidence-based than the enthusiasm of its promoters would lend to believe. Using three stories based on observations made recently in Quebec where the argument of evidence-based support was brought, it will be illustrated how groups, their interventions and programs positioned themselves to their advantage.. These promoters in the health care system aim at better care, but they are also motivated by their own professional, departmental and research agendas ; they are supported by other logics and stakeholders like pharmaceutical firms, consumers and relatives; but can be slowed down by decision-makers and planners querying the ressources required, the efficiency, the accessibility, the training and the impact on other programs in a balanced mental health care system. This essay also briefly review the definitions, the limits of an evidence-based approach, and its origins from clinical epidemiology and public health. It does not consist solely of evidence drawn from randomised clinical trials and quantitative research designs, but also from qualitative and mixed designs, that have been developed by human sciences. The practice and application of evidence is not mastered in mental health systems, but the author hopes that with increased training by all stakeholders in its use, it will introduce a continuous evaluation at the individual clinical level, at the program and system levels. A continuous questioning that signals quality in clinical practices and services.
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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 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".