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Record W4249385841 · doi:10.4000/itineraires.2642

Récits de société

2015· paratext· fr· W4249385841 on OpenAlexaboutno aff

Bibliographic record

VenueItinéraires · 2015
Typeparatext
Languagefr
FieldArts and Humanities
TopicLiterature and Culture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Quelle approche critique pour aborder les « innombrables récits » (Barthes) qui traversent et construisent notre imaginaire social ? Prise en tenailles entre le storytelling et le grand roman social, la notion de récit de société peut-elle réconcilier la littérature avec les usages communs de la narration, de l’anecdote au journalisme littéraire ? Dans l’optique d’un rapprochement disciplinaire entre histoire, littérature et sciences de l’information, ce volume interroge les formes que peut prendre le récit littéraire dans son amplitude à la fois générique et thématique. Il aborde d’abord l’idée de « récit de société » en la confrontant à des contre-modèles comme les mythes ou le storytelling, tout en intégrant la possibilité d’une approche transmédiale. Dans un second temps, le récit de société est travaillé comme un outil qui dépasse et transcende les genres littéraires, pour enfin agir comme un révélateur de désordres sociaux. La fiction narrative endosse alors un rôle de contre-pouvoir régulateur qui permet de reconfigurer les imaginaires, les repolitiser ou en faire apparaître les tabous. Le dossier est complété par une sélection de varia portant sur le Québec entrant en résonance avec le thème principal du volume avec un accent particulier mis sur les performances, les légendes et les pratiques musicales des Premières Nations.

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)0.006
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 score0.038
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0050.011
Scholarly communication0.0140.010
Open science0.0010.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0380.011

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 head0.035
GPT teacher head0.282
Teacher spread0.247 · 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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