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Record W4408612204 · doi:10.1097/nne.0000000000001846

Success Strategies That Support First Nations Students in Undergraduate Nursing Programs

2025· article· en· W4408612204 on OpenAlexaboutno aff
Linda Deravin, Rebecca Keogh, Keden Montgomery, Louise Wells, Jayne Lawrence, Suzanne Querruel, Lorraine Rose, Karen Francis

Bibliographic record

VenueNurse Educator · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsAttritionWorkforceThematic analysisReflexivityNursingNurse educationHealth careMedical educationPsychologyMedicinePolitical scienceSociologyQualitative researchSocial science

Abstract

fetched live from OpenAlex

BACKGROUND: A strategy that may improve health outcomes for First Nations Peoples is to have greater representation of First Nations Peoples within the health care workforce. There are systemic issues within higher education institutions that impact recruitment, retention, and academic progression of First Nations nursing students entering and completing undergraduate programs, which contributes to a higher rate of attrition compared to their non-First Nations counterparts. PURPOSE: To establish what strategies support First Nations students to succeed within undergraduate nursing programs. METHOD: A scoping review of 5 databases was utilized. RESULTS: Eight papers were included in the review. Reflexive thematic analysis resulted in 4 themes: (1) social learning environments, (2) culturally safe places (3) embracing support, and (4) external impacts. CONCLUSION: Despite positive actions, attrition rates and prolonged course lengths continue to impact course progression for First Nations nursing students.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.865
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.000
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 head0.021
GPT teacher head0.390
Teacher spread0.369 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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