Eradicating Systemic Discrimination: Advancing Democratic Leadership in Canada's Education System
Bibliographic record
Abstract
Social Justice Leadership, Critical Race Theory, and 21st Century Teaching bring forth the imperative need to nurture inclusivity and address systemic inequities in educational settings.It is educators and leaders who can knowingly help create such an area that is preoccupied with equity, justice, and social issues.The ability to function and integrate technology in schools demonstrates a key competence for 21st-century leadership, while critical thinking, collaboration, and flexibility are being developed in students.This article calls for a paradigm shift away from the more conventional ways of leadership to adopting a framework in leading towards social justice.In its support for the creation of critical spaces and dialogues at the community level, this article argues that such an approach is necessary in empowering communities by planting the practice of social justice right at the core of all educational institutions.Using literature from social justice leadership, critical race theory, and the best practices of teaching today, there are four identified critical areas that need to be taken with regard to leadership action: visionary leadership, instructional leadership, organizational leadership, and collaborative leadership.These areas are recommended for principals and assistant principals to take proper action as a measure toward mitigating or overcoming the racial discipline gap.The proposed strategies for educational leadership will be aimed at reflecting the principles of social justice and the transforming power of contemporary teaching and learning practices with the purpose of bringing a more inclusive and equitable learning environment.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.034 | 0.009 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.005 |
| 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".