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Record W331007654 · doi:10.4000/lidil.3114

Rapports aux textes virtuels en formation de lettres : vers une nouvelle écriture professionnelle

2011· article· fr· W331007654 on OpenAlexaff
Véronique Rey, Céline Beaudet

Bibliographic record

VenueLidil · 2011
Typearticle
Languagefr
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsArtHumanities

Abstract

fetched live from OpenAlex

La littératie étendue correspond à des écritures générant la gestion de plusieurs contraintes. Les textes numérisés et les hypertextes exigent du scripteur des macrohabiletés textuelles et discursives qui nécessitent des formations. Un rapide historique rappelle les éléments principaux de cette révolution et leurs conséquences dans le domaine scolaire. La rupture est également abordée en interrogeant les enjeux pragmatiques et énonciatifs des hypertextes. Les comportements des enseignants de lettres face à cette nouvelle réalité professionnelle sont appréhendés au moyen d’un questionnaire. Il s’avère que les enseignants ont peu investi ce domaine. Les résultats sont discutés par une mise en perspective anthropologique entre technique et écriture et en s’interrogeant également sur l’enseignement de l’écriture de haut niveau en milieu universitaire.

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)0.008
metaresearch head score (Gemma)0.016
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: none
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0060.012
Scholarly communication0.0090.009
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0120.002

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 head0.034
GPT teacher head0.261
Teacher spread0.227 · 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

Citations2
Published2011
Admission routes1
Has abstractyes

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