Bibliographic record
Abstract
Purpose: This study is to investigate how principals promote social justice to redress marginalization, inequity, and divisive action that are prevalent in schools. Research Method: This study employs a qualitative research design with semistructured interviews. Twenty-two elementary and secondary school principals were interviewed in the Greater Toronto Area, Ontario, Canada. Research Findings: Principals who are social justice advocates exercise their influence by focusing on people in an effort to build a socially just community. Their people-centered leadership practice focuses on: putting students at the center, positioning as a social justice leader, developing people for social justice, building school climate through social justice, and fostering positive relationships with families and communities. Social justice leadership is grounded in a very proactive way in bringing about the changes that such a paradigm demands. Implications: This study generates discussions among participants on the dynamics associated with social justice practice and helps practitioners navigate tactically entrenched power structures for the well-being of their students. It also deepens our understanding of social justice leadership by providing empirical evidence how social justice advocates take risks and innovative approaches to social change that embraces the value of democracy, inclusion, representation, and difference.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.047 | 0.011 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".