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Record W3158529736 · doi:10.3917/lps.201.0117

La recherche communautaire pour soutenir l’action au GRIS-Montréal

2020· article· fr· W3158529736 on OpenAlex
Olivier Vallerand, Amélie Charbonneau, Kévin Lavoie, Marie Houzeau

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueLes Politiques Sociales · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsMontreal General HospitalUniversité LavalMontreal Clinical Research Institute
Fundersnot available
KeywordsHumanitiesSociologyArtPolitical science

Abstract

fetched live from OpenAlex

Olivier Vallerand, Amélie Charbonneau, Kévin Lavoie & Marie Houzeau Depuis 1994, le Groupe de recherche et d’intervention sociale de Montréal (GRIS-Montréal) réalise des ateliers de démystification de la diversité sexuelle et de genre dans les écoles primaires et secondaires. L’expérience acquise avec le temps et les recherches menées par l’organisme ont permis d’améliorer sa méthode d’intervention, entre autres en outillant ses bénévoles afin que leur intervention mette davantage l’accent sur la déconstruction des stéréotypes de genre. En utilisant l’exemple de l’évaluation qualitative d’un projet de semaine d’activités pour les écoles primaires, cet article présente comment l’organisme utilise la recherche communautaire afin d’adapter son travail aux besoins des populations rencontrées.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.638
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.003
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.722
GPT teacher head0.477
Teacher spread0.245 · 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