Where are you From? Reframing Facilitated Admissions Policies in the Faculty of Health Sciences
Bibliographic record
Abstract
Understanding that Indigenous learners can face specific barriers or challenges when pursuing higher education, schools and programs within McMaster’s Faculty of Health Sciences have facilitated admissions streams for Indigenous (First Nations, Métis, and Inuit) applicants. The intent of reframing admissions policies is to provide equitable access while aligning with the Truth and Reconciliation Commission of Canada’s Calls to Action, specifically Number 23. This work explores the development of an Indigenous-determined Facilitated Indigenous Admissions Program (FIAP), a self-identification policy that moves away from the politics of mathematical blood quantum to nationhood, community, and seeing the applicant as whole being. Further, it critiques (for example) medical school admissions as biased, in that they often replicate an elite and narrow segment of society. It also addresses how interpretations of decisions like Daniels v Canada, which speaks to the rights of Métis and non-status Indigenous peoples, are communicated or miscommunicated within emerging population groups in terms of rights and their potential relationship to admissions.
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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 | 0.047 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.039 | 0.036 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.004 | 0.022 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".