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Immigrant Nurses' Experience of Racism

2001· article· en· W2029345422 on OpenAlex

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

VenueJournal of Nursing Scholarship · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsToronto Metropolitan UniversityUniversity of WindsorUniversity of Toronto
Fundersnot available
KeywordsRedressImmigrationRacismEquity (law)Qualitative researchExploratory researchNursingFace (sociological concept)Focus groupSociologyPsychologyPublic relationsPolitical scienceMedicineGender studiesLaw

Abstract

fetched live from OpenAlex

PURPOSE: To document and describe the experiences of immigrant nurses of colour who have filed grievances concerning their employers' discriminatory practices; and to solicit their views of existing policies and recommendations for equity in professional life. DESIGN AND METHODS: In this descriptive, exploratory study nine immigrant nurses of colour in Ontario, Canada, were interviewed between 1997 and 1998. Data were collected through face-to-face interviews and in focus groups. The discourse theory and methods of van Dijk and Essed were used to analyse the qualitative data. FINDINGS: Recurring themes were: (a) being marginalized and acknowledging and naming the racist experiences; (b) experiencing physical stress and emotional pain; (c) strategizing to cope and survive; (d) recommending policy changes. CONCLUSIONS: All nurses interviewed had experienced reprisals as a result of complaining or filing grievances and unfairness was encountered in the redress process itself. Participants recommended policy initiatives to ensure equity and fair practices in the nursing profession.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.370
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.097
GPT teacher head0.437
Teacher spread0.340 · 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