Henri Ellenberger unsung pioneer of ethnopsychiatry: genesis and knowledge mobilized for the "Encyclopedie Medico-Chirurgicale" in 1965.: Henri Ellenberger, ethnopsychiatry's pioneer: cultural knowledge and populations at risk in the "Encyclopedia-Médico-Chirurgicale"
Bibliographic record
Abstract
This paper will present little known articles on ethnopsychiatry published by Henri Ellenberger in 1965 for the French "Encyclopédie Médico-Chirurgicale" (EMC), after a first transcultural study at McGill University about the impact of a physical illness of a child upon the family, according to the problem of cultural factors and pathogens (1961). By relying on archival documents (correspondance and manuscripts), we show how Henri Ellenberger took himself the initiative of involving the Anglo-Canadian specialist in epidemiology H. B. M. Murphy in a team composed solely with of Paris psychoanalysts. More precisely, we examine the knowledge mobilized by Henri Ellenberger to observe the distribution of mental disorders in populations at risk, according to the problems of cultural relativism and cultural specificity. We will discuss the scientific metaphor favored by Ellenberger at the time (the mapping of the frequency of mental disorders) and its relations to the ambient culturalism in North America, but in the context of French reception, hostile to this paradigm as well.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.017 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".