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Record W2966751594 · doi:10.7202/1074720ar

Le Mentorat féminin dans les contes de fées : de ruses en ruses

2021· article· fr· W2966751594 on OpenAlexaffvenue
Marianne Legault

Bibliographic record

VenueTopiques études satoriennes · 2021
Typearticle
Languagefr
FieldSocial Sciences
TopicHistorical and Literary Studies
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsArtHumanities

Abstract

fetched live from OpenAlex

Cet article examine les différentes formes de mentorats féminins dans trois contes de fées du Grand Siècle: Riquet à la Houppe, L’Adroite princesse ou les aventures de Finette, et L’Enchanteur. On y trace le rôle du mentorat dans la relation conteuses-lectrices, ainsi que son influence sur le refus des contraintes domestiques et sociales imposées sur les femmes. Le mentorat féminin, qui apparaît chez ces conteuses dans des maximes, dans un appel à l’écriture, ou dans la conclusion de l’intrigue, sert à dénoncer les hommes et à encourager les femmes tant à la production du genre merveilleux qu’à la liberté de conduite féminine.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0080.012
Scholarly communication0.0050.004
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.026
GPT teacher head0.287
Teacher spread0.260 · 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 designQualitative
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
Published2021
Admission routes2
Has abstractyes

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