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Record W3173923565 · doi:10.4000/belphegor.3803

Genèse et circulations d’un genre populaire en régime médiatique : le cas du Country Noir

2021· article· fr· W3173923565 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBelphégor · 2021
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPolitical science

Abstract

fetched live from OpenAlex

Si l’expression « Country Noir » a été inventée en 1996 par l’écrivain étasunien de romans noirs, Daniel Woodrell, pour sous-titrer son roman Give Us a Kiss, a Country Noir, l’étiquette ne devient prolifique que dans les années 2010. Le Country Noir, qui relève de la fiction criminelle située en milieu rural, est un genre qui se construit médiatiquement selon trois modalités. L’expression est d’abord reprise par l’interdiscours médiatique dans une forme de négociation discursive entre les différents acteurs du champ culturel. Elle est ensuite transformée en étiquette dans les stratégies de communication des maisons d’édition françaises qui participent ainsi de sa légitimation. Enfin, elle se consolide dans la circulation transnationale, entre la France et les États-Unis, d’œuvres intermédiales sur des supports textuels et visuels tels que le roman policier, le cinéma et les séries télévisées. Cet article a pour objectif de démontrer la dynamique et les mouvances d’un genre fictionnel populaire en émergence.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.899
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0020.004
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.082
GPT teacher head0.296
Teacher spread0.214 · 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