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Record W3172985586

MeToo and chivalry à la française

2019· article· fr· W3172985586 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueEtudes · 2019
Typearticle
Languagefr
FieldSocial Sciences
TopicFeminism, Gender, and Intersectionality
Canadian institutionsnot available
Fundersnot available
KeywordsChivalryOffensiveShameCriticismMultitudeBalance (ability)LawHistoryPolitical scienceSociologyPsychologyOperations researchEngineeringAncient history
DOInot available

Abstract

fetched live from OpenAlex

In France, the equivalent of the #MeToo movement, “Balance ton porc” (literally, “denounce your pig”), has been around for a long time. Its founder, Sandra Muller, has been summoned before the courts to answer to charges of defamation. Various individuals who have been indicted are trying to bring lawsuits against their female whistleblowers. Not one has had cause for concern to the same degree as others in the United States and Canada. A multitude of criticism has been leveled at this French version of #MeToo, with many of these attacks being heavily argued and highly offensive. Nonetheless, it would be a shame to forget the issues at stake and not respond to calls from Michelle Perrot and Laure Murat to “deconstruct the notion of chivalry a la francaise.”

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.812
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.306
Teacher spread0.286 · 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