Accountability, ethics and knowledge production: racialised academic staff navigating competing expectations in the social production of research with marginalised communities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.115 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.005 |
| 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 it