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Record W3048232178 · doi:10.7202/1070516ar

Portraits littéraires et généricité

2020· article· fr· W3048232178 on OpenAlexvenueno aff
Dominique Maingueneau

Bibliographic record

VenueTangence · 2020
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Cet article étudie les collections à visée commerciale, en particulier « Écrivains de toujours » et « Poètes d’aujourd’hui », du point de vue de la généricité. En s’appuyant sur une typologie des genres de discours, il s’attache à montrer pourquoi les textes qu’on y publie ne peuvent qu’être très divers ; leur seule contrainte est de se tenir à distance de deux frontières : celles qui les séparent, d’une part, des ouvrages scolaires et, d’autre part, de la littérature. Corrélativement, leurs auteurs ne sont pas, en règle générale, des écrivains de premier plan et ne doivent pas se présenter comme des enseignants, mais plutôt comme des « connaisseurs » de la littérature. La comparaison avec le genre des « souvenirs littéraires », qui est alors en voie d’extinction, est à cet égard éclairante. Cette double instabilité, celle du genre et celle du statut des auteurs, se manifeste à travers l’écriture de ces livres, qui montrent un ethos de « lettré » ; en témoigne l’étude d’un passage du Pascal (« Écrivains de toujours ») d’Albert Béguin, auteur très représentatif de l’esprit de la collection concernée.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.010
Science and technology studies0.0090.009
Scholarly communication0.0110.007
Open science0.0020.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0340.010

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 head0.354
GPT teacher head0.324
Teacher spread0.029 · 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 designTheoretical or conceptual
Domainnot available
GenreEmpirical

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
Published2020
Admission routes1
Has abstractyes

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