Social Justice Agenda for Community Organizations in Morocco (Equity, Diversity, and Inclusion Reconsidered)
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.014 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".