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Record W2805191467 · doi:10.7202/1046498ar

Qui est-ille ? Le respect langagier des élèves non-binaires, aux limites du droit

2017· article· fr· W2805191467 on OpenAlexaffvenueabout
Florence Ashley

Bibliographic record

VenueService social · 2017
Typearticle
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsMcGill University
Fundersnot available
KeywordsObligationPolitical scienceHumanitiesEthnologyPhilosophySociologyLaw

Abstract

fetched live from OpenAlex

Dans cet article, l’autrice explore la question de savoir si une obligation légale de respecter les pronoms et accords neutres existe en contexte scolaire francophone au Québec. Ille débute par un survol du contexte vécu par les personnes non-binaires francophones ainsi que de leurs besoins par rapport au respect des pronoms et accords neutres. Ensuite, ille analyse l’état actuel du droit relativement au harcèlement et à la discrimination envers les personnes trans en contexte scolaire et évalue la plausibilité qu’une obligation de respecter les pronoms et accords neutres soit retenue par les tribunaux québécois. Enfin, à la lumière des limites du droit, ille propose une approche stratégique concernant le respect des pronoms et accords neutres qui met l’accent sur le développement de politiques institutionnelles s’appuyant sur le droit.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.306

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.017
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.000

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 head0.023
GPT teacher head0.263
Teacher spread0.240 · 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

Citations13
Published2017
Admission routes3
Has abstractyes

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