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Record W3115867313 · doi:10.5663/aps.v9i1.29359

Where are you From? Reframing Facilitated Admissions Policies in the Faculty of Health Sciences

2020· article· en· W3115867313 on OpenAlexaffvenueabout
Danielle Soucy, Cornelia Wieman

Bibliographic record

Venueaboriginal policy studies · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRace, Genetics, and Society
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCognitive reframingIndigenousCommissionIndigenous educationPolitical scienceElitePoliticsPopulationPublic administrationIndigenous rightsSociologyPublic relationsEconomic growthLawPsychologySocial psychology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.366
Threshold uncertainty score0.409

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.062
GPT teacher head0.406
Teacher spread0.344 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2020
Admission routes3
Has abstractyes

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