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Les arts littéraires : transmédialité et dispositifs convergents

2022· paratext· fr· W4304845505 on OpenAlexaboutno aff

Bibliographic record

VenueRecherches & travaux · 2022
Typeparatext
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

À l’intersection des études littéraires et des sciences de l’information et de la communication, ce dossier de la revue Recherches & travaux entend explorer les ramifications de la notion d’arts littéraires, une notion promue dans les milieux culturels québécois qui tend peu à peu à s’imposer plus largement. L’enjeu est de saisir à travers cette dénomination émergente la multiplication des pratiques observées (lecture dessinée, poésie numérique, feuilletons radiophoniques, vidéo-poèmes, créations sonores immersives ou interactives). En montrant à partir des études sur la transmédialité (Jenkins, 2006 ; Bourdaa, 2012 ; Maigret, 2013), sur les médiations culturelles (Lamizet, 1999 ; Davallon, 2004 ; Caune, 2006), ainsi que sur la création littéraire (Rosenthal & Ruffel, 2010 ; Nachtergael, 2015), qu’il ne s’agit pas d’une simple juxtaposition de supports en quelque sorte absorbés par la littérature, ces articles visent à soutenir l’idée qu’émerge une nouvelle conception du littéraire et de sa pratique — d’où diverses appellations tentant d’en saisir la proposition inédite : « poésie performée », « arts de la parole », « œuvres transmédiatiques », « néolittérature », « littérature exposée »… L’objectif est alors de comprendre comment les arts littéraires tirent parti des processus de convergence en place pour renouveler les dispositifs de narration et les formes de médiation avec les publics.

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)0.006
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: Other
Teacher disagreement score0.052
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.006
Science and technology studies0.0130.031
Scholarly communication0.0260.017
Open science0.0020.015
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0290.004

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 head0.613
GPT teacher head0.413
Teacher spread0.200 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

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