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Record W3021171917 · doi:10.7202/1068351ar

La recherche partenariale féministe : des rapports égalitaires sous tension1

2020· article· fr· W3021171917 on OpenAlexvenueaboutno aff
Isabelle Courcy, Lyne Kurtzman, Berthe Lacharité, Lucie Pelletier-Landry, Isabel Côté, Nathalie Lafranchise

Bibliographic record

VenueRecherches féministes · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Un grand nombre de recherches sont conjointement élaborées par des chercheuses et des groupes de femmes en vue de changer les structures d’inégalité et d’augmenter le pouvoir d’agir des femmes. Au Québec, ces initiatives s’inscrivent depuis près de 50 ans dans une tradition de développement et de promotion de la recherche partenariale. Les auteures présentent les résultats d’une recherche empirique menée afin de tracer un portrait des pratiques de recherche partenariale féministe et mieux comprendre la manière dont ce type de recherche est conçu et vécu par les chercheuses. Les résultats montrent que la recherche féministe partenariale est privilégiée pour son potentiel de contribution à la société. Son exercice doit par ailleurs relever des défis qui éclairent l’enjeu irrésolu de la hiérarchisation des savoirs, celui-ci se traduisant notamment dans les façons de nommer les pratiques de recherche, de concrétiser la coconstruction des connaissances et de développer des pratiques de résistance devant les inévitables dynamiques de pouvoir.

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)0.047
metaresearch head score (Gemma)0.031
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: none
Teacher disagreement score0.108
Threshold uncertainty score0.254

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0470.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0180.057
Scholarly communication0.0160.012
Open science0.0020.013
Research integrity0.0050.007
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 head0.545
GPT teacher head0.430
Teacher spread0.115 · 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

Citations6
Published2020
Admission routes2
Has abstractyes

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