MétaCan
Menu
Back to cohort
Record W6984894260

[no title]

2021· other· fr· W6984894260 on OpenAlexaboutno aff

Bibliographic record

VenueDirectory of Open access Books (OAPEN Foundation) · 2021
Typeother
Languagefr
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Identity (music)Order (exchange)
DOInot available

Abstract

fetched live from OpenAlex

Dans toutes les démocraties occidentales, la télévision est devenue le moyen d'information principal — celui qui rejoint le plus large auditoire et auquel les gens accordent le plus de crédibilité. Présent dans pratiquement tous les foyers, le petit écran ouvre sur l'espace public fondamental de notre temps et sous-tend les liens les plus essentiels qui unissent les citoyens à leurs représentants politiques. Pourtant, en dehors des campagnes électorales, peu d'analystes politiques se sont intéressés aux informations télévisées. Denis Monière cherche ici à combler cette lacune. Il analyse systématiquement les journaux télévisés de quatre chaînes publiques francophones (Radio-Canada, France 2, la Radio-télévision belge et la Télévision suisse romande) pour la période qui va de décembre 1996 à mars 1997. En tenant compte des différences du cadre juridique et des situations politiques, il mène une étude empirique et comparative du contenu et de la forme des informations. À partir d'un sujet aussi précisément délimité, Denis Monière élargit sans cesse la perspective pour s'intéresser au rôle des médias dans le processus démocratique. Il montre qu'à l'ère du « village global », l'information continue néanmoins à s'accompagner d'un traitement différencié culturellement selon le public auquel on la destine.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Open science, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.799
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0070.009
Open science0.0130.019
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.8030.004

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 head0.106
GPT teacher head0.389
Teacher spread0.284 · 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; both teacher heads agree on what is shown here.

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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueDirectory of Open access Books (OAPEN Foundation)Same topicClimate variability and modelsFrench-language works237,207