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Record W3040977155 · doi:10.7202/1070018ar

Enquêter sur la violence conjugale au Maroc : les défis d’un féminisme intersectionnel du positionnement

2020· article· fr· W3040977155 on OpenAlexaffvenue
Salima Massoui, Michaël Séguin

Bibliographic record

VenueRecherches qualitatives · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicMulticulturalism, Politics, Migration, Gender
Canadian institutionsHEC MontréalUniversité du Québec à Montréal
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Si diverses auteures ont abordé le changement de positionnement que de mener une enquête en tant que féministe implique, peu se sont attardées à ce que cela signifie de le faire dans une société arabo-amazighe à majorité musulmane en tant que chercheure indigène (ou insider). En relisant dans la perspective d’un féminisme intersectionnel du positionnement une recherche menée auprès de femmes violentées de milieu populaire de la région de Rabat, cet article propose d’expliciter des enjeux méthodologiques comme l’accès solidaire à un terrain sensible, la présentation auprès d’enquêtées issues du même milieu social, le tissage de liens de confiance de diverses natures et le recueil de récits douloureux. Au-delà de la construction des données, il propose de réfléchir à l’analyse des résultats, qu’il s’agisse de donner sens aux justifications culturelles et religieuses de la violence conjugale ou encore de rendre compte de ses manifestations intergénérationnelles et interclasses entre femmes.

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)0.009
metaresearch head score (Gemma)0.013
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 score0.067
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0130.019
Scholarly communication0.0070.004
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.318
GPT teacher head0.443
Teacher spread0.125 · 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

Citations2
Published2020
Admission routes2
Has abstractyes

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