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Record W2169507883 · doi:10.14574/ojrnhc.v8i2.116

Who Stays in Rural Practice?: An Internatinal Review of the Literature on Factors Influencing Rural Nurse Retention

2008· article· en· W2169507883 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.

Bibliographic record

VenueOnline Journal of Rural Nursing and Health Care · 2008
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsNursingAffect (linguistics)Job satisfactionEmployee retentionRural areaPsychologyMedicineBusinessMarketingSocial psychology

Abstract

fetched live from OpenAlex

This paper explores factors that influence rural nurse retention. A comprehensive literature review was used to highlight, examine and evaluate studies that identify factors, including personal characteristics and experiences, in relation to rural nurse retention and job satisfaction. The findings from the literature review suggest rural nurse retention is influenced by level of job satisfaction. The findings also suggest factors, including personal characteristics and experiences, influence job satisfaction. The literature review findings further indicate factors, including personal characteristics and experiences, affect the duration of rural nurse practice. The current rural nursing retention strategies in British Columbia are explored. Based on the findings from the literature review, detailed recommendations for future research and recommendations for rural nursing retention strategies are made. The concepts identified inform health human resources retention strategies, specifically nursing retention in rural areas.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.431
Threshold uncertainty score0.934

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.042
GPT teacher head0.464
Teacher spread0.422 · 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