Voices of racialized and Indigenous leaders in Canadian universities
Bibliographic record
Abstract
Despite increasing interest in the development of K-12 educational leadership, and the slowly growing interest in leadership within higher education, the experiences of racialized and Indigenous leaders remain largely unheard and undocumented in Canada. Using a multiple-case study research design, participants were asked to answer the research question: What are the experiences of racialized and Indigenous leaders in Canadian universities? Ten racialized and Indigenous leaders serving various leadership roles in Canadian universities were interviewed in relation to this question using individual, semi-structured interviews and interpreted through the framework of Critical Race Theory. Six themes emerged to describe the complex and demanding roles of the participating leaders: a) Navigating Power, Politics, & Action, b) Resilience & Managing Distractions, c) Maintaining Values and Principles, d) Practicing Sustainable Leadership, e) Negotiating a Unique Identity: Insiders & Outsiders, and d) Negotiating Organizational Trust. The findings show that the nature of leadership practiced by the participating leaders is dynamic, fluid, and evolving. This research also revealed the important role race plays in influencing the day to day experiences of these leaders in higher education and how their presence, positive identity leadership traits, and personal politics, directly or indirectly result in socially just and equitable leadership outcomes, ultimately making Canadian universities more equitable. These findings support Applied Critical Leadership (ACL), an emerging theory in educational leadership research. It also captures insights, which inform future research agendas in educational leadership generally, and leadership in higher education more specifically.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.049 | 0.013 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".