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Experiences of epistemic racism among occupational therapists

2022· article· en· W4226276706 on OpenAlexaffabout
Brenda L. Beagan, Kaitlin R. Sibbald, Tara Pride, Stephanie R. Bizzeth

Bibliographic record

VenueCadernos Brasileiros de Terapia Ocupacional  · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCritical Race Theory in Education
Canadian institutionsDartmouth General HospitalDalhousie University
Fundersnot available
KeywordsRacializationRacismSociologyEpistemologyInstitutional racismSocial psychologyPsychologyGender studiesRace (biology)Philosophy

Abstract

fetched live from OpenAlex

Abstract Objective Epistemic racism establishes the knowledges and ways of knowing of a dominant group as legitimate, invalidating those of groups marked by racialization. Professions are demarcated by their knowledge claims, making epistemic racism a powerful mechanism of exclusion within professions. This paper examines experiences of epistemic racism in occupational therapy across Canada. Method Using a critical interpretive qualitative approach, ten therapists from racialized groups were interviewed (in-person or telephone), with transcripts coded and analyzed iteratively. Results Participants routinely experienced epistemic ‘mis/fit’ with the profession, rarely seeing themselves reflected in the profession’s knowledge base, leadership, values or assumptions. Racialized therapists were routinely denied expertise and authority, by students, clients and colleagues. They walked a tightrope between professional assimilation and marginalization. Conclusion The presence of racialized therapists is insufficient, when their authority is consistently delegitimized and they are required to assimilate. Leadership roles for racialized therapists must be accompanied with epistemological multiplicity, destroying the domination of whiteness.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.338
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.000

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 head0.025
GPT teacher head0.356
Teacher spread0.331 · 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.

Study designQualitative
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

Citations10
Published2022
Admission routes2
Has abstractyes

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