Social justice in public high schools: a literature analysis and field insights from two Canadian high schools
Bibliographic record
Abstract
Purpose This pilot study explores social justice education in the context of two schools in the interior of British Columbia that self-identify as advocates and promoters of social justice. Design/methodology/approach First, I identify key trends in recent (2014–24) literature on social justice education in high schools, noting the prevalence of three key themes: social justice programming, curriculum activities and teacher and leadership development. Then, drawing on the work of Iris Marion Young (1990) and Lee Ann Bell (2016), I analyze findings from my pilot study of four administrators, six teachers and four staff members from my two selected school sites. Findings While these early findings show some overlap with the findings of existing research, importantly, they also gesture at potentially substantial gaps in our critical conception of how social justice education is understood and practices, notably in rural Canadian schools. Originality/value Without studying diverse contexts within the landscape of Canadian high schools, this paper suggests, education researchers may be inadequately preparing teacher education programs and their teacher candidates for work in rural schools and may be missing the chance to broaden and diversify interventions in urban 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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.015 | 0.024 |
| Science and technology studies | 0.039 | 0.011 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 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".