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Record W2990316684 · doi:10.36834/cmej.56976

Factors perceived to influence rural career choice of urban background family physicians: a qualitative analysis

2019· article· en· W2990316684 on OpenAlexaffvenueabout
Olga Szafran, Douglas Myhre, Jacqueline Torti, Shirley Schipper

Bibliographic record

VenueCanadian Medical Education Journal · 2019
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsWestern UniversityUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsRural areaQualitative researchPsychologyFamily medicineMedicineSociology

Abstract

fetched live from OpenAlex

BACKGROUND: Urban background physicians are the main source of physician supply for rural communities across Canada. The purpose of this study was to describe factors that are perceived to influence rural career choice and practice location of urban background family medicine graduates. METHODS: We conducted a qualitative, descriptive study employing telephone interviews with 9 urban background family physicians practicing in rural locations. Those who completed residency training between 2006 and 2011, were in rural practice, and had an urban upbringing were asked: when the decision for rural practice was made; factors that influenced rural career choice; and factors that influenced choice of a particular rural location. Emerging themes were identified through content analysis of interview data. RESULTS: We identified four themes as factors perceived to influence rural career choice - variety/broad scope of rural practice, rural lifestyle, personal relationships, and positive rural experience/physician role models. We also identified factors in four areas perceived to influence the choice of a particular rural practice location - having lived in the rural community, spousal influence, personal lifestyle, and comfort with practice expectations. CONCLUSION: Decisions for rural career choice and rural practice location by practicing urban background family medicine graduates are based on clinical practice considerations, training experience, as well as personal and lifestyle factors.

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0180.000

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 head0.066
GPT teacher head0.472
Teacher spread0.406 · 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 designObservational
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

Citations14
Published2019
Admission routes3
Has abstractyes

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