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Record W2543787901

A review of the recruitment and retention strategies of rural and northern physicians in Manitoba, Canada

2015· review· en· W2543787901 on OpenAlexaffabout
Jaymie Walker

Bibliographic record

VenueGlobal Health: Annual Review · 2015
Typereview
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRural areaEconomic shortagePromotion (chess)MedicineCurriculumRural healthHealth careNursingPolitical scienceMedical educationFamily medicine
DOInot available

Abstract

fetched live from OpenAlex

Recruitment and retention of rural healthcare workers is an important health issue for almost all countries around the world. In 2010, the WHO released guidelines on the sorts of strategies and initiatives countries should implement to improve the number of rural physicians (1). These guidelines, along with recent literature from Canada and Australia, were explored for similar suggestions and themes. These themes were then used to examine the current recruitment and retention initiatives in Manitoba, Canada. Manitoba has over 300,000 citizens living in rural areas and over 100 physician vacancies (2, 3). Despite many new strategies, the shortage is on going (1). Therefore, the current strategies and initiatives in Manitoba are explored in detail and compared to what is recommended in the literature. From there, recommendations were made on how to improve the current deficit of rural physicians in Manitoba based on suggestions from the literature. To improve recruitment, more mandatory rural rotations, incorporation of rural health issues and topics into undergraduate and postgraduate curricula, and promotion of a rural lifestyle should be implemented. To improve retention, expanding continuing medical education or professional development programs in rural areas, implementation of a professional association, and support for physician’s families should be top priority. If Manitoba were to consider implementation of these strategies, rural physician recruitment and retention rates should improve in the next few years.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.499
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.145
GPT teacher head0.484
Teacher spread0.339 · 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 designSystematic review
Domainnot available
GenreReview

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
Published2015
Admission routes2
Has abstractyes

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