Reconnaître la différence : le défi de l’ethnopsychiatrie
Bibliographic record
Abstract
Recognizing difference of the Other is the basis of legitimacy of ethnopsychiatry that is necessarily multiple, changing, and itself bearing subtleties and variations. It is from their practice at the Service d'aide psychologique spécialisée aux immigrants et réfugiés (SAPSIR), that the authors propose another perspective of this discipline taking into account of course, the cultural and psychological dimension of the individual; they also consider existential and humanistic universals such as the need of giving meaning, of continuity of the self and coherence as well as the various dimensions of identity. Their clinical approach, respectful of the principles of ethnopsychiatry, is structured around three axis : work on links, work on different dimensions of identity, work on coherence and meaning of situations experienced. This approach allows to accompany and facilitate essential elaborations involved in the psychological work of refugees as well as individuals exposed to extreme situations such as torture.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.018 |
| Scholarly communication | 0.007 | 0.013 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.001 | 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".