Navigating the Path of Critical Leadership: Tensions and Possibilities of the Leadership Journey
Bibliographic record
Abstract
Abstract This chapter examines our leadership journey as Black female social justice leaders and culturally responsive leaders from the Caribbean Diaspora in Canada. Borrowing from Mullen, Fenwick, and Kealy (2014) and Campbell’s (2008) notion of leadership as a journey, we critically examine what it means to navigate educational leadership contexts. Through our lived experiences as racialized leaders, border crossing spaces and cultures, and with a deep sense and agency to resolve social inequities and injustice we critically gaze at our leadership contexts. This chapter examines ways we, as critical leaders, challenge inequities, issues of power and marginalization, and find transformative actions and purpose by critically reflecting on our leadership journey. This work will add to the educational leadership discourse by positing ways that leaders can develop agency and engage in leadership that is transformative – bringing theory into action.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.045 |
| Scholarly communication | 0.025 | 0.011 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".