Bibliographic record
Abstract
The rising trend in global migration has made Canadian schools more diverse. This diversity includes students from migrant families, students coming from war-torn, terrorism or conflict-affected countries, students with disabilities, students living in poverty, as well as racialized and Indigenous students. While this diversity brings resilience and cultural richness to schools, at times school principals find it challenging to support the academic achievements and physical and mental well-being of these students. This paper provides a review on various reforms, initiatives and education policies of the United Nations and Ontario that guide school leadership to enact equity and inclusion in schools. This paper reports on a systematic review of literature that explore the role of school leadership in supporting students affected by war and terrorism in Ontario. I discuss the emerging role of school leadership in the context of increasing diversity in schools, propose changes to Bronfenbrenner’s (1999) bioecological model of human development , and recommended that by adopting Shield’s (2010) transformative leadership framework , school leaders can make their schools more equitable and inclusive. I also advocate for the establishment of cross-cultural educational partnerships to connect the educational policy-makers, researchers, practitioners, and school leaders through the Train-the-Trainer model to mobilize knowledge globally.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".