Tempering Applied Critical Leadership: The Im/Possibilities of Leading for Racial Justice in School Districts
Bibliographic record
Abstract
How do leaders make the impossible choice between harm enacted on racially oppressed students and families, and harm enacted on them as advocates for racial justice in systems steeped in whiteness? How do they negotiate multiple harms in Black and Brown bodies? Purpose: Situated in between the literature on tempered radicalism and Applied Critical Leadership (ACL), this study explores the experiences of six Black and Brown mid-level and senior-level district leaders in Greater Toronto Area, in Ontario, Canada. Research Methods/Approach: We draw on counter-narrative methodologies including in-depth oral history interviews and ongoing communication with participants to explore the impossibilities and possibilities of leading for racial justice. Findings: Impossibilities include complicities and complexities, accountabilities and alliances, and different metrics, different expectations. Possibilities include present and future hopes, personal power and voice, and joy and fulfillment. Implications for Research and Practice: This study adds to the literature on critical race-tempered radicalism by offering three important shifts in perspectives about leading for racial justice that blur revolutionary leadership and ACL. These include challenging a politics of representation and the necessary change in metrics, accountability measures, and systemic necessary to demonstrate the readiness for anti-racist leadership; anti-racist leadership as messy, ambiguous, and contextual that make space for complicities and complexities of this work; and anti-racist leadership beyond anti-racist leaders, which recognizes leadership beyond any one person, role, location, or generation.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.026 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.004 |
| 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".