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Record W2745535226 · doi:10.7202/1040751ar

Femmes leaders du secteur communautaire : leur engagement et leur contribution au changement social

2017· article· fr· W2745535226 on OpenAlexaffvenueabout
Lise Savoie, Marie-Andrée Pelland, Hélène Albert, Isabel Lanteigne

Bibliographic record

VenueReflets Revue d’intervention sociale et communautaire · 2017
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsPolitical scienceHumanitiesSociologyArt

Abstract

fetched live from OpenAlex

L’article porte sur les résultats d’une recherche visant à comprendre la trajectoire d’engagement de femmes qui occupent un poste de leader rémunéré dans le secteur communautaire à but non lucratif au Nouveau-Brunswick. Ces militantes ont relaté leurs motifs d’engagement et le sens qu’elles y accordent. Elles qui s’engagent dans la défense des droits des populations vulnérables, dans une perspective de justice et de changement social — le moteur de leur engagement — sont elles-mêmes en position d’iniquité. Cet engagement dans l’amélioration des conditions de vie des personnes contribue à la cohésion sociale dans un contexte où l’État social s’effrite. Ainsi, l’engagement des femmes dans ce secteur relève de la justice sociale pour reconstruire un monde plus équitable. Il s’agit d’un double défi : redonner du pouvoir d’agir aux populations vulnérabilisées tout en reconnaissant de manière équitable la contribution de ces femmes leaders dans le secteur communautaire tant au plan social qu’économique.

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)0.004
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: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.003
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.156
GPT teacher head0.414
Teacher spread0.258 · 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

Citations0
Published2017
Admission routes3
Has abstractyes

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