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Record W2620332731 · doi:10.1186/s12960-017-0209-0

Nurses who work in rural and remote communities in Canada: a national survey

2017· article· en· W2620332731 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHuman Resources for Health · 2017
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsUniversity of ReginaDalhousie UniversityHôpital Maisonneuve-RosemontAurora CollegeLaurentian UniversityUniversity of SaskatchewanUniversité de MontréalUniversity of LethbridgeUniversity of Northern British Columbia
FundersCanadian Institutes of Health Research
KeywordsWorkforceNursingWorkforce planningMedicineNurse educationNursing researchRural areaWork (physics)Health services researchPublic healthPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: In Canada, as in other parts of the world, there is geographic maldistribution of the nursing workforce, and insufficient attention is paid to the strengths and needs of those providing care in rural and remote settings. In order to inform workforce planning, a national study, Nursing Practice in Rural and Remote Canada II, was conducted with the rural and remote regulated nursing workforce (registered nurses, nurse practitioners, licensed or registered practical nurses, and registered psychiatric nurses) with the intent of informing policy and planning about improving nursing services and access to care. In this article, the study methods are described along with an examination of the characteristics of the rural and remote nursing workforce with a focus on important variations among nurse types and regions. METHODS: A cross-sectional survey used a mailed questionnaire with persistent follow-up to achieve a stratified systematic sample of 3822 regulated nurses from all provinces and territories, living outside of the commuting zones of large urban centers and in the north of Canada. RESULTS: Rural workforce characteristics reported here suggest the persistence of key characteristics noted in a previous Canada-wide survey of rural registered nurses (2001-2002), namely the aging of the rural nursing workforce, the growth in baccalaureate education for registered nurses, and increasing casualization. Two thirds of the nurses grew up in a community of under 10 000 people. While nurses' levels of satisfaction with their nursing practice and community are generally high, significant variations were noted by nurse type. Nurses reported coming to rural communities to work for reasons of location, interest in the practice setting, and income, and staying for similar reasons. Important variations were noted by nurse type and region. CONCLUSIONS: The proportion of the rural nursing workforce in Canada is continuing to decline in relation to the proportion of the Canadian population in rural and remote settings. Survey results about the characteristics and practice of the various types of nurses can support workforce planning to improve nursing services and access to care.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.130
GPT teacher head0.465
Teacher spread0.335 · 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