Social justice and equity : exploring the perspectives of senior administrators on whiteness and racism in postsecondary education
Bibliographic record
Abstract
This study explored senior administrators? perspectives on Whiteness and racism in postsecondary education. The study focused on Canadian senior administrators at postsecondary institutions located in 2 provinces and in 2 communities with populations of less than 100,000. Using critical ethnography and narrative inquiry methodologies, this study?s participants acknowledged that Whiteness and racism exist in postsecondary institutions. It found that senior administrators are in a position to influence the postsecondary institutional climate, and that they perceive their role as being accountable to the organization including responses to Whiteness and racism. This study asserts that as a well-educated and predominantly White culture-sharing group, the senior administrators? conscientiousness of White privilege is required to address racism. Most of this study?s senior administrator participants acknowledge having been exposed to specific acts of racism in higher education. The findings suggest specific actions to challenge racism within postsecondary institutions, such as senior administrators? role-modeling actions against racism; adopting a critical pedagogical approach toward institutional antiracist education; the enforcement of institutional antidiscrimination and harassment policies; and hiring procedures informed by nondominant perspectives to promote employee diversity. This research also revealed prejudices disproportionately focused on Aboriginal students and communities, which implies a role for further research and government response.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.023 | 0.019 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".