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Record W4404925156 · doi:10.7202/1114129ar

Note empirique sur les journaux qui s’adressent aux francophones minoritaires du Canada

2024· article· fr· W4404925156 on OpenAlexaffvenueabout
Simon Laflamme

Bibliographic record

VenueCahiers Charlevoix Études franco-ontariennes · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsLaurentian University
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

En recourant à la textométrie dans une étude précédente, Simon Laflamme a comparé, sur toute l’année 2019, le contenu de deux journaux régionaux de l’Ontario : l’un en langue anglaise, le Northern Life, et l’autre en langue française, Le Voyageur. Cette comparaison a permis de montrer que le contenu des journaux était différencié en fonction du destinataire quoiqu’il comportât des similitudes qui correspondaient aux préoccupations que les lectorats avaient en commun. Cette étude mettait en question la thèse qui veut que la rédaction des journaux locaux soit alignée sur celle des journaux nationaux sous la pression de l’industrialisation, du capitalisme et de la domination de classe. Dans le prolongement de cette étude, notre collègue compare quatorze journaux en langue française dans le Canada hors Québec, encore une fois pour toute l’année 2019. Cette nouvelle analyse oblige, elle aussi, à mettre en doute la pertinence de la thèse de l’aliénation des journaux régionaux. Elle met en lumière des sujets qui se rapportent à l’ensemble des journaux, comme le développement socio-économique, la francophonie et les problèmes des sociétés; elle rappelle que chaque journal propose à son lectorat un contenu empreint de particularités.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.615

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0190.007
Scholarly communication0.0060.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.012
GPT teacher head0.225
Teacher spread0.213 · 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 designObservational
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
Published2024
Admission routes3
Has abstractyes

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