The “Equity Waltz” in Canada: Whiteness and the informal realities of racism in education
Bibliographic record
Abstract
Canada has long perceived itself to be a country in which multiculturalism, and a concomitant respect for diversity, is a unique and defining feature of its identity. Although Canada is a de facto multicultural country, owing to its rapidly evolving demography and the explicit notion of multiculturalism enshrined in its Constitution, there remains a plethora of problems and issues related to equity, diversity and human rights. This paper explores the context and impact of racism in education within a framework that acknowledges and critically positions the predominance of Whiteness. The salience of identity, therefore, is a primary consideration to understanding how marginalized groups face systemic barriers in education. The concluding analysis sheds light on the educational policy process, and focuses on the notion of accountability for anti-racism and social justice in education within a time of neoliberal reforms. The paper is critical of the lack of attention, resources and comprehensive plans in place to ensure that all students benefit from a more holistic education that includes a focus on social justice.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.038 | 0.038 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".