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Record W4394751495 · doi:10.4000/rsh.5314

De la « mise-en-légende » comme condition du raconter dans Peut-être Esther de Katja Petrowskaja

2024· article· fr· W4394751495 on OpenAlexaff
Benoîte Turcotte-Tremblay

Bibliographic record

VenueRevue des Sciences Humaines · 2024
Typearticle
Languagefr
FieldArts and Humanities
TopicFrench Literature and Critical Theory
Canadian institutionsMinistry of Labour, Employment and Social Solidarity
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Paru dans sa traduction française en 2015, le récit Peut-être Esther de l’autrice ukrainienne exophone Katja Petrowskaja retrace l’enquête mémorielle à laquelle s’est livrée l’autrice pour donner un sens aux histoires familiales criblées de silences qui ont nourri son imaginaire et façonné sa sensibilité. Née à Kyïv (appelée Kiev dans la traduction) dans une famille juive non pratiquante, Petrowskaja a grandi dans l’Ukraine soviétique des années 1970, et fait partie de la troisième génératio...

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)0.002
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.009
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.057
GPT teacher head0.312
Teacher spread0.255 · 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
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
Published2024
Admission routes1
Has abstractyes

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