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Record W4386789421 · doi:10.33137/utjph.v4i2.39198

Anti-Black Racism in Healthcare: Could critical race theory prove helpful in the Canadian context?

2023· article· en· W4386789421 on OpenAlex
Khandideh K A Williams, Nicole Kaniki

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueUniversity of Toronto Journal of Public Health · 2023
Typearticle
Languageen
FieldHealth Professions
TopicPublic Health Policies and Education
Canadian institutionsUniversity of TorontoMcGill University
Fundersnot available
KeywordsRacismHealth careHealth equityCritical race theoryEquity (law)Race (biology)Context (archaeology)Gender studiesSociologyInstitutional racismPolitical scienceCriminologyHistoryLaw

Abstract

fetched live from OpenAlex

Anti-Black racism persists in various Canadian areas, including healthcare. The legacy of white dominance from the period of colonization and slavery has spawned an afterlife of anti-Black racism, which has significantly contributed to shortcomings in Canadian healthcare equity. The underfunding of research specifically examining the experiences of Black communities in healthcare has resulted in a lack of evidence in the available literature and has further contributed to barriers to advocacy for addressing health disparities within these communities. In this commentary, we briefly discuss the history of anti-Black racism in Canada and how it continues to manifest in Canadian healthcare. We suggest that engaging critical race theory in the Canadian racial healthcare equity literature may provide a more nuanced analysis of the root causes of racial health disparities in Canada’s Black communities and is essential for developing effective strategies that address systemic and structural anti-Black racism in the Canadian healthcare environment.

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.

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)0.020
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.767
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.101
GPT teacher head0.430
Teacher spread0.329 · 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