What Did the Multicultural Policies of the Last Century Promise that Need to Be Re-Imagined in Today’s DEDI Post-Secondary World?
Bibliographic record
Abstract
This article is an expanded version of the 2023 Plenary Lecture at the Canadian Society for the Study of Education (CSSE) Conference held at the Congress of the Humanities and Social Sciences. This invited essay explores the extent to which the promise of DEDI’s (decolonization, equity, diversity, and inclusion) polices and initiatives might bring about the imagined institutional changes in today’s context. Contending that we have been here before, the essay reckons that changes will not come about simply through verbal rhetoric, targeted hiring, or training sessions where individuals engage in self-reflection on their attitudes, values, and behaviours, but through critical examination of institutional policies, programs, and practices that result in the removal of systemic barriers which have operated over the years to maintain the inequitable situation being addressed.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.048 |
| Scholarly communication | 0.019 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.009 |
| 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".