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Record W3002074854 · doi:10.7202/1066655ar

Pouvoir, inconfort et apprentissage : les cours féministes peuvent-ils et doivent-ils être des espaces préfiguratifs et sécuritaires ?

2020· article· fr· W3002074854 on OpenAlexaffvenue
Geneviève Pagé

Bibliographic record

VenueÉthique en éducation et en formation Les Dossiers du GREE · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

L’enseignement féministe se donne souvent comme mandat d’être préfiguratif, c’est-à-dire de produire dans le ici et maintenant les formes de relations sociales qui sont l’objectif des mouvements (féministes) (Boggs, 1977, p. 100). De même, les pédagogues féministes tentent souvent de créer des espaces dits « sécuritaires » ( safe space ), où les personnes apprenantes se sentent en sécurité d’exprimer leurs pensées (Holley et Steiner, 2005). S’il est important et légitime de favoriser la participation de tous, particulièrement des personnes qui prennent rarement la parole publiquement (les femmes et les personnes racisées), j’avance, à l’instar de hooks (1994) et de Barret (2010), que tenter de créer un espace sécuritaire ( safe space ) dans une salle de classe n’est ni réaliste ni désirable. Je propose plutôt d’investir le concept d’« espace d’apprentissage » et d’y construire des pratiques pédagogiques féministes visant à outiller les personnes étudiantes pour qu’elles deviennent des actrices de changement jonglant avec des personnes et des contextes imparfaits.

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)0.006
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.024
Scholarly communication0.0120.012
Open science0.0010.004
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0090.001

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 head0.108
GPT teacher head0.405
Teacher spread0.297 · 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

Citations4
Published2020
Admission routes2
Has abstractyes

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