In Search of Belonging in a Grade 6-8 Public School in Western Canada
Bibliographic record
Abstract
Systemic racism and oppressive practices within and outside British Columbia institutions are negatively impacting students’ sense of belonging in schools. The Metro School District (MSD, a pseudonym) and BC Ministry of Education (BCMoE) have responded with the district equity plan and the K-12 Anti-Racism Action Plan, respectively, to address this issue. However, a gap remains between their goals and the current reality of creating inclusive school environments. Valley Middle School (VMS, a pseudonym) has seen instances of racism and exclusion affecting students and teachers from minoritized backgrounds, including myself as a Sikh, South Asian principal. My Dissertation-in-Practice (DiP) focuses on bridging this gap and fostering a sense of belonging for all students through inclusive school practices. Applying transformational, transformative, and culturally responsive leadership, informed by critical and postmodern lenses, aims to address equity, diversity, inclusion, and decolonization (EDID). Using Nadler and Tushman’s Congruence Model, I assessed the organization’s readiness for change, revealing a low readiness level across work, culture, structure, and people. Consequently, my DiP emphasizes developing teacher capacity in culturally responsive teaching and promoting change grounded in the ethics of care, critique, and justice. Implementing frameworks like Kotter’s 8-Step Change Model and Deming’s PDSA Cycle provide a structure for this change process, fostering a greater sense of belonging for all students.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.036 | 0.006 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".