Bridging Antiracism and Equity, Diversity, and Inclusion Discourses Through Grassroots Organization Efforts
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.108 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.444 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".