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Record W3175831536 · doi:10.25071/2291-5796.79

Career Advancement: The Experiences of Minority Nurses in Accessing Leadership Positions in a Tertiary Care Setting

2021· article· en· W3175831536 on OpenAlex
Naima Bouabdillah, Amélie Perron, Dave Holmes

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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueWitness The Canadian Journal of Critical Nursing Discourse · 2021
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of OttawaUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsWorkforceNonprobability samplingNursingHealth careLeadership developmentFace (sociological concept)PsychologyEthnographyMedical educationMedicinePublic relationsPolitical scienceSociology

Abstract

fetched live from OpenAlex

Minority nurses are underrepresented in leadership roles in the Canadian healthcare system. The purpose of this study was to explore MNs’ perceptions and experiences with regards to career development and MNs in leadership positions. Twelve nurses, four Caucasian and eight from the Caribbean and Africa in a tertiary care setting were recruited through purposive sampling. Face-to-face semi-structured interviews were conducted, transcribed, coded, and analyzed using critical ethnography. Findings revealed lack of social support, of equal opportunities, of recognition and of trust. Despite negative experiences, minority nurses recognized the value of their work experience at the hospital where they were employed. Committing to a diverse workforce in leadership roles can ultimately have an effect on patient care. Minority nurses’ leadership is needed to provide role models and to ensure the delivery of competent care to diverse populations.

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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score0.891

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 studies0.0000.002
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 head0.045
GPT teacher head0.388
Teacher spread0.343 · 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