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Record W2734529265 · doi:10.4000/belphegor.864

Montréal babélique ?

2017· article· fr· W2734529265 on OpenAlexvenueaboutno aff
Xavier Boileau, Micheline Cambron, Jérémi Perrault

Bibliographic record

VenueBelphégor · 2017
Typearticle
Languagefr
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Cet article vise à explorer la relation entre l’éclatement linguistique de Montréal et les caractéristiques de la couverture journalistique des Jeux olympiques. L’hypothèse initiale, selon laquelle la couverture de l’événement varierait selon la langue des différents journaux étudiés, ne se vérifie pas dans le traitement des cinq thèmes principaux (race, politique internationale, organisation sportive, esprit sportif et sport féminin) qui traversent les discours. Cependant, l’examen de l’iconographie révèle que les journaux francophones et anglophones s’appuient sur des imaginaires différents, les premiers accordant une place importante à des images tendant à vedettiser les athlètes alors que les seconds proposent plutôt des images du corps sportif. La couverture des Jeux des journaux montréalais n’apparaît donc pas fortement différenciée selon la langue.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.922
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0020.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.002

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 head0.039
GPT teacher head0.285
Teacher spread0.246 · 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
Published2017
Admission routes2
Has abstractyes

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