Accountability, ethics and knowledge production: racialised academic staff navigating competing expectations in the social production of research with marginalised communities
Bibliographic record
Abstract
Universities, both in Canada and throughout the global North, are predicated on empiricist and positivist understandings of knowledge and knowledge production which are communicated and strengthened through research practices and protocols. Drawn from a larger study exploring research leadership among accomplished academic staff, this paper examines interviews with eight racialised female academic staff who focus on social justice research predicated on co-producing knowledge with marginalised communities. Building on the rich scholarship which conveys the consequences of systemic discrimination for racialised and Indigenous scholars working in Canadian universities, we explore how participants navigate systems that fail to understand their epistemological and methodological orientation towards research and consider what it reveals about research culture and claims of inclusiveness in the Canadian academy. Drawing on Sara Ahmed’s work on performative diversity in academia, we consider how academic structures, protocols and policies associated with research influence the social production of knowledge and resist change toward greater equity and Reconciliation demanded of Canadian higher education.
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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 | 0.086 | 0.099 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.056 | 0.081 |
| Scholarly communication | 0.024 | 0.008 |
| Open science | 0.003 | 0.022 |
| Research integrity | 0.004 | 0.006 |
| 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".