Bibliographic record
Abstract
Purpose – Today, as the understanding of diversity is further expanded, the meaning of social justice becomes even more complicated, if not confusing. The purpose of this paper is to explore how school principals with social justice commitment understand and perceive social justice in their leadership practices. Design/methodology/approach – A qualitative research design is used for this study. In total, 22 school principals in Ontario were interviewed. The interviews glean data on principals’ work context, their perceptions of social justice, and anecdotes, stories, and examples concerning social justice in their practices. Findings – The research findings draw attention to the central importance of awareness of the social injustices in schools – in structure, policy, and practices – and open space for debate on what can be considered as leadership for social justice. They also provide a useful starting point in exploring how leadership roles and practices can be improved to reverse injustices associated with the diversity of students based on race, socioeconomic status, gender, sexual orientation, and ability. Originality/value – What principals perceive may have a significant impact on the actions and practices for social justice. Therefore, it is important to gain insight into principals’ persecutions and perspectives on social justice as they may become norms and criteria that guide their actions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.022 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.015 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".