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Record W7160462694

Claire Le Men, Le syndrome de l’imposteur. Parcours d’une interne en psychiatrie, Paris, La Découverte, 2019. Alexandre Klein (Université d’Ottawa)

2019· other· fr· W7160462694 on OpenAlexaffabout
Alexandre Klein

Bibliographic record

VenueCairn.info · 2019
Typeother
Languagefr
Field
Topic
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsExplicationFace (sociological concept)IntentionalityFirst person
DOInot available

Abstract

fetched live from OpenAlex

Cet article fait le point sur les différentes théories concernant le phénomène hypnotique, en partant du principe qu’il s’agit plus d’un fait anthropologique majeur qu’une simple modification psychologique ou de la conscience, tant le phénomène hypnotique est intégré à une problématique sociale dans de nombreuses civilisations. C’est pourquoi nous abordons la question de manière épistémologique, sans prendre parti pour telle ou telle théorie et en essayant de dégager ce que chacune d’entre elles apporte à la connaissance de ce phénomène complexe. Il apparaît en réalité que la multiplicité des théories relativise la force de chacune d’elle et que, au bout du compte, il est bien difficile de proposer un schéma d’ensemble cohérent ou une théorie unificatrice de ce qu’est le phénomène hypnotique. De manière simplifiée, deux cadres théoriques se font face : les approches psychologiques au sens large (psychologie cognitive, psychanalyse, psychologie sociale) et les approches physiologiques (dont les neurosciences) sans qu’aucune d’elle n’apporte d’explication décisive. Une telle prolifération incite à se demander si finalement envisager une explication du phénomène hypnotique a un sens et si l’on n’est pas avec l’hypnose au cœur du « problème difficile » (ou fossé explicatif) des neurosciences concernant la conscience.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.019
Scholarly communication0.0040.007
Open science0.0010.003
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0090.002

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.

Opus teacher head0.004
GPT teacher head0.202
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2019
Admission routes2
Has abstractyes

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Same venueCairn.infoFrench-language works237,207