Use of a School-based Audit Tool for Guiding Anti-racism Education in Schools: A Pilot Assessment
Bibliographic record
Abstract
The negative health impacts of racism and race-based discrimination have been well established within the public health literature. Though public health acknowledges racism and education as determinants of health, the field has failed to adequately address the health-harming impacts of racism within the education system, and thus has underutilized anti-racism work as a preventative and health equity strategy. This project piloted a school-based audit tool to assess school policies and practices for supporting cultural diversity and addressing race-based discrimination in two Alberta junior high schools to explore how an audit could be useful in guiding the development of anti-racism education. The study found that the utilization of an audit tool can help to begin a process of formalized discussion and raising awareness about interpersonal and institutional racism within educational contexts; however, the tool needs to be paired with action-oriented steps to successfully address racism as a determinant of health and education.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".