Navigating Allyship through Indigenization, Decolonization, and Reconciliation: Perspectives from Non-Indigenous Pharmacy Educators
Bibliographic record
Abstract
As pharmacy schools across Canada and North America work towards authentic and meaningful curriculum and learning opportunities in Indigenous health and cultural safety, the conversation of "why" we need to do this has become clearer, but the task of "how" we do this remains challenging. This curricular transformation can be increasingly more complex to navigate as a non-Indigenous ally and pharmacy educator. Defining your role as an ally is deeply personal and critically important, as it can transform based on the collaborative work undertaken with Indigenous partners and communities. The purpose of this article is to share perspectives gained over years of experience and practical applications of allyship through the lens of three key separate, but interconnected concepts - indigenization, decolonization, and reconciliation.
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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 | 0.018 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.026 | 0.040 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.002 | 0.022 |
| Research integrity | 0.004 | 0.012 |
| 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".