MétaCan
Menu
Back to cohort
Record W4409602961 · doi:10.1002/dvr2.70019

Bridging Antiracism and Equity, Diversity, and Inclusion Discourses Through Grassroots Organization Efforts

2025· article· en· W4409602961 on OpenAlexaff
Pascale Caïdor

Bibliographic record

VenueDiversity & Inclusion Research · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicRacial and Ethnic Identity Research
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsGrassrootsBridging (networking)Equity (law)Inclusion (mineral)Diversity (politics)Political scienceSociologyPublic relationsGender studiesPoliticsLaw

Abstract

fetched live from OpenAlex

ABSTRACT This article centers on the voices and experiences of racialized women, which are often marginalized in organizational settings that fail to adequately address racial discrimination. Grassroots organizations play a vital role in bridging the gap between antiracism and EDI discourses. Yet, research on their communication campaigns remains scarce, despite their key role in integrating these often‐conflicting narratives. These organizations are not merely supportive; they are essential in amplifying overlooked perspectives and shaping antiracism discourse in the public sphere. This paper examines the practices, tactics, and discourse of a grassroots organization that develops antiracism campaigns and initiatives with its publics. It is based on a collaborative project with FRY, a nonprofit organization founded by racialized women from the African diaspora. Drawing on the cocreational perspective, this study explores how grassroots organizations and their publics cocreate meanings around racial issues. Using qualitative methods including interviews, observations, and focus groups with nonprofit members, this research investigates how the organization collaborates with its audiences to cocreate diverse “safe spaces” and discourses tailored to the specific needs of racialized women. These spaces offer opportunities to openly discuss racism, find refuge from discrimination, foster sisterhood, and connect members with critical resources.

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)0.006
metaresearch head score (Gemma)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.443
Threshold uncertainty score0.955

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.1080.001
Scholarly communication0.0000.001
Open science0.0010.444
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 head0.094
GPT teacher head0.444
Teacher spread0.350 · 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 designObservational
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

Explore more

Same venueDiversity & Inclusion ResearchSame topicRacial and Ethnic Identity ResearchFrench-language works237,207