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Record W3099631384 · doi:10.7202/1072753ar

Le risque de contagion suicidaire lié à l’identification aux personnages de films et de séries

2020· article· fr· W3099631384 on OpenAlexvenueno aff
Christophe Gauld, Charles-Édouard Notredame

Bibliographic record

VenueFrontières · 2020
Typearticle
Languagefr
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsnot available
FundersAustralian Government
KeywordsHumanitiesPhilosophyArt

Abstract

fetched live from OpenAlex

La représentation cinématographique (incluant les séries télévisées) d’un suicide pourrait influencer le taux de suicide par le biais d’un phénomène d’identification au personnage visualisé à l’écran. Lorsqu’elle conduit à l’imitation du geste suicidaire, cette projection identificatoire, par contagion suicidaire, est nommée « effet Werther » (EW); son corollaire, pour prévenir le phénomène suicidaire, est « l’effet Papageno » (EP). Le présent article analyse le rôle de l’identification au cinéma dans l’appropriation émotionnelle et cognitive des scènes de suicide, et son implication dans les EW et EP. Pour ce faire, nous nous sommes appuyés sur une bibliographie scientifique couvrant trois domaines : la contagion suicidaire, les études en communication et les études sur le cinéma.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.646
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.289
Teacher spread0.250 · 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 teacher head, not a consensus.

Study designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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