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Record W7053514328

Violence et télévision

2018· book· en· W7053514328 on OpenAlexaboutno aff

Bibliographic record

VenueIndustrias Culturais (Universidade de Coimbra) · 2018
Typebook
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsPoison controlSuicide preventionHomicide
DOInot available

Abstract

fetched live from OpenAlex

Le massacre de l'École polytechnique à Montréal en 1989 ou bien encore le meurtre de la jeune Marie-Eve Larivière en 1992 ont fait rebondir le débat sur la violence à la télévision au Canada. Plus d'un million de personnes ont signé, à la suite de ce dernier drame, une pétition réclamant un renforcement du contrôle du contenu des programmes. Quelques faits sordides et sanglants ont eu le même impact sur une société américaine déjà ébranlée par les émeutes de Los Angeles et le revisionnement incessant de lynchages en direct, qu'il s'agisse de l'assassinat de touristes européens en Floride ou du meurtre gratuit du père de Michael Jordan par deux adolescents en Géorgie. Un débat identique se déroule alors aux États-Unis où, au début du mois d'août 1993, producteurs et directeurs de chaînes réunis à Los Angeles tentent d'élaborer un code de bonne conduite visant à réduire l'omniprésence de la violence sur les écrans de télévision américains. En France, le CSA adresse régulièrement des mises en garde aux chaînes, y compris publiques, contre les dérives de la programmation en ce qui concerne la violence et la sexualité.

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)0.001
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.081
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0050.009
Scholarly communication0.0070.002
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0400.004

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 head0.024
GPT teacher head0.265
Teacher spread0.240 · 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
Published2018
Admission routes1
Has abstractyes

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