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Record W2097052877 · doi:10.4000/communiquer.1772

Perspectives en communication (02)

2015· article· fr· W2097052877 on OpenAlexvenueno aff
Benoît Cordelier, Maude Bonenfant, Martin Lussier, Florence Millerand

Bibliographic record

VenueCommuniquer Revue de communication sociale et publique · 2015
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Depuis son lancement en 2009, la Revue internationale de communication sociale et publique a publié jusqu'à présent 10 numéros. Nous nous étions donné pour premier objectif de publier deux numéros par an. C'est donc, pour nous, un succès que nous avons le plaisir de partager avec nos auteurs, les membres de nos comités d'évaluation et nos lecteurs. C'est aussi une motivation pour continuer et envisager de nouveaux projets. Aujourd'hui, notre revue bénéficie de l'appui financier du Conseil de recherches en sciences humaines (CRSH), l'un des organismes subventionnaires les plus importants au Canada. Cette reconnaissance institutionnelle nous donne les moyens de travailler à de nouveaux développements que nous tenons à marquer par un changement de nom symbolique. La Revue internationale de communication sociale et publique s'appellera bientôt Communiquer, revue de communication sociale et publique. À cette occasion, nous nous sommes interrogés sur ce qu'allait devenir notre discipline. Et nous souhaitons y réfléchir avec les chercheurs du domaine en vous invitant à participer à un numéro spécial avec dossier sur les Perspectives en sciences de la communication.

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)0.003
metaresearch head score (Gemma)0.007
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.089
Threshold uncertainty score0.297

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0040.006
Scholarly communication0.0170.009
Open science0.0010.004
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0890.028

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 head0.284
GPT teacher head0.376
Teacher spread0.092 · 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
Published2015
Admission routes1
Has abstractyes

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