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Record W7161828791 · doi:10.82308/23385

"Trouver les mots pour le dire" : s'approprier un certain pouvoir sur l'expérience de la folie à travers la prise de parole

2002· dissertation· fr· W7161828791 on OpenAlexaboutno aff
Karine. Vanthuyne

Bibliographic record

Venuenot available
Typedissertation
Languagefr
FieldSocial Sciences
TopicPublic Health and Social Inequalities
Canadian institutionsnot available
Fundersnot available
KeywordsArticulation (sociology)Mental healthNarrativeExpression (computer science)Power (physics)Mental illness

Abstract

fetched live from OpenAlex

This anthropological study focuses on people's subjective experiences of mental health problems in Quebec, and highlights the different processes involved in the narrativization and enunciation of the experience of psychiatric disorder. It was completed in Montreal in 2001, and included participant observation in three resources of the Regroupment des resouces alternatives en sante mentale du Quebec (RRASMQ). Nine people of Quebecois origin, users of these mental health services, were interviewed. After a brief survey of the literature concerned with the narrative transformation of experience and its expression in the social realm, this report identifies some of the narrative structures of the illness accounts that were collected for this project. I look, on the one hand, at the various languages used in the articulation of "mental illness", and on the other hand, at the power relations that are activated through the use of those languages. This study tries to determine to what extent it is possible for a sufferer of "mental illness" to empower him/herself through the narrativization and expression of one's experience of mental health problems.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.472
Threshold uncertainty score0.939

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0200.029
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.028
GPT teacher head0.315
Teacher spread0.287 · 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 designQualitative
Domainnot available
GenreEmpirical

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
Published2002
Admission routes1
Has abstractyes

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Same topicPublic Health and Social InequalitiesFrench-language works237,207