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Record W2228058590 · doi:10.12927/hcpol.2016.24447

Inter-Provincial Migration Intentions of Family Physicians in Canada: The Roles of Income and Community Characteristics

2015· article· en· W2228058590 on OpenAlexafffundvenueabout
Haizhen Mou, M. Rose Olfert

Bibliographic record

VenueHealthcare policy · 2015
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsUniversity of Saskatchewan
FundersCanadian Institutes of Health ResearchHealth CanadaCanadian Medical AssociationCollege of Family Physicians of CanadaRoyal College of Physicians and Surgeons of Canada
KeywordsDestinationsIncentiveCompensation (psychology)Demographic economicsGeographySocioeconomicsEconomic growthPolitical sciencePsychologySociologyEconomicsSocial psychology

Abstract

fetched live from OpenAlex

The inter-provincial migration patterns of family physicians in canada show that some provinces like newfoundland and saskatchewan experience persistent net out-migration, while others, including ontario and british columbia, are destinations more often than origins of migrants. Governments in provinces exhibiting net out-migration have responded with a number of incentive and recruitment programs. In this study, we investigate the determinants of the stated interprovincial migration intentions of 3,995 rural and urban family physicians in the 2010 wave of the national physician survey. We consider a range of physician characteristics, community attributes and working conditions. We find that in the intention to move, higher compensation has a modest effect, while the community characteristics have a consistently important influence. Our results suggest that policy and program designers should acknowledge the critical role of community-level living and working conditions in their family physician recruitment and retention efforts.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.087
GPT teacher head0.421
Teacher spread0.334 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations11
Published2015
Admission routes4
Has abstractyes

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