“Navigating the Different Spaces”: Experiences of Inclusion and Isolation Among Racially Minoritized Faculty in Canada
Bibliographic record
Abstract
The intersection of multiple identities (e.g., racialization, gender, class) strongly determines an individual’s social location. In-depth interviews with 42 racially minoritized academics in Canadian universities allowed U.S. to begin to grasp the challenges faced by those who must negotiate the different spaces in an academy that is predominately white, Eurocentric and male. Using an anti-racist framework, we found that the level of inclusion that racially minoritized academics in our study felt within their workplaces depended upon their experiences with 1) acceptance (e.g., through hiring, promotion, and tenure); 2) visibility (e.g., in terms of perceived power in informal and formal work interactions); 3) support (e.g., via collegial and administrative encouragement, assistance, collaboration and resource support); and 4) mentoring (e.g., in terms of providing and seeking mentor experiences). Our findings suggest that the increasing presence of racially minoritized academics may better serve institutional purposes of portraying a mission of diversity than actually achieving a mission of equity.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.056 | 0.016 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| 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".