Culturally Responsive Leadership:How Principals Employ Culturally Responsive Leadership to Shape the School Experiences of Marginalized Students
Bibliographic record
Abstract
This qualitative study research examines how 2 elementary principals in Ontario schools employ culturally responsive leadership (CRL) to shape the school experiences of marginalized students. In particular, it explores the strategies 2 principals use to enact this approach to leadership, the barriers and resistance they face that impede their social justice agenda, the supports that facilitate their work in schools, and the impact CRL has on various stakeholders. This study employed semi-structured interviews with open-ended questions guided by the conceptual framework derived from the literature review around culturally responsive pedagogy, culturally responsive leadership, social justice leadership, and educational leadership. Five teachers from each school were also interviewed in order to capture their insights as to how their principalâ s culturally responsive leadership practices impacted their teaching and understanding of cultural responsiveness. The findings in the study show that principal participants foster a cultural responsive culture, promote culturally responsive pedagogy, create a welcoming climate in their school and build authentic relationships with all stakeholders, to move their social justice agenda forward. They also advocate passionately on behalf of their community to access resources to benefit students and families in the school community. These administrators also endeavor to change unjust structures that serve to perpetuate inequity and deter students from reaching high academic standards. In doing so, these leaders encounter formidable resistance and obstacles, despite which they continue to respond to the needs of their community in order to create socially just and equitable schools.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.017 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".