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Record W4410134021 · doi:10.1002/dvr2.70022

Social Justice Agenda for Community Organizations in Morocco (Equity, Diversity, and Inclusion Reconsidered)

2025· article· en· W4410134021 on OpenAlexfundno aff
Kenza Oumlil

Bibliographic record

VenueDiversity & Inclusion Research · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsnot available
FundersEuropean CommissionSocial Sciences and Humanities Research Council of CanadaGovernment of Canada
KeywordsEquity (law)Social justiceInclusion (mineral)Diversity (politics)Social equalitySociologyPolitical scienceSocial scienceAnthropologyLaw

Abstract

fetched live from OpenAlex

ABSTRACT Theoretically and practically, how does the Equity, Diversity, and Inclusion (EDI) framework fit with the local specificities and needs of a non‐Western country like Morocco? Struggles for social justice have preceded the formulation of EDI language. This study takes interest in frameworks and practices of engagement in advocacy work, as well as challenges encountered in doing civil society work. The analysis is based on semi‐structured interviews conducted with Moroccan women's rights activists and sub‐Saharan women migrants in Morocco. The interviews show that the research participants have worked on implementing legal reforms to counter discriminatory laws and pursue the empowerment of their communities. Further, they have engaged in creating cultural transformations by presenting nonstereotypical and alternative views. Some of the challenges they encounter include backlashes from religious conservative forces. They “must” navigate integrating external funding demands while mobilizing for the issues that they deem a priority. Although these community organizations are distinct, this study seeks to generate knowledge from the ground up regarding epistemologies and practices, while also illuminating potential future directions for the implementation of social justice agendas.

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 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)0.011
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.1770.001
Scholarly communication0.0000.000
Open science0.0020.381
Research integrity0.0000.001
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 head0.372
GPT teacher head0.475
Teacher spread0.103 · 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 teacher head, not a consensus.

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
Published2025
Admission routes1
Has abstractyes

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