“Knowing nothing about EDI:” A collaborative autoethnography exploring how an anti-racist project was created, publicized, and silenced
Bibliographic record
Abstract
This collaborative autoethnography explores how a group of students and professors from across Canada came together following racial justice protests of 2020. Driven by a desire to pressure Canadian higher education organizations to act on statements and commitments they had made regarding anti-racism, the group embraces a students-as-partners framework in the creation of a list of demands for institutions. Despite claims by such organizations that they were addressing racism, the demands were largely ignored. The authors explore both phases of the project, from factors leading to the successful creation of the demands to experiencing dismissal by the institutions they were designed to help. Twin messages are drawn from this work: students-as-partners is a powerful and useful method for engaging in conversations and taking action regarding anti-racism in higher education, yet this has little bearing on the institutions and structures which participate in oppression.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.029 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".