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Record W6999429482

The contribution of Memorial University medical graduates to the family physician workforce in Newfoundland and Labrador

2021· article· en· W6999429482 on OpenAlexaffabout

Bibliographic record

VenueScholarship@Western (Western University) · 2021
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsMemorial University of NewfoundlandWestern University
Fundersnot available
KeywordsWorkforceSample (material)Graduate medical educationGraduate studentsMedical schoolRural area
DOInot available

Abstract

fetched live from OpenAlex

Recruiting and retaining family physicians (FP) in rural communities has been an ongoing issue in Canada and other developed nations. The objective of this thesis was to analyze the long-term contribution that Memorial University medical graduate FP make to the physician workforce in Newfoundland and Labrador (NL). We found that 47% of our sample ever worked in NL, 15% ever worked in rural NL and 58% who ever worked in NL stayed for at least 10 years. Being from NL was a predictor of working in NL for at least 5 years and 10 years, respectively. Doing at least some residency at MUN was a predictor of working in rural NL. The study supports policies that encourage the admission of NL students to undergraduate and post-graduate medical programs at Memorial University. Future research should examine retention of Memorial University graduate specialists.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.992
Threshold uncertainty score0.883

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.080
GPT teacher head0.388
Teacher spread0.308 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2021
Admission routes2
Has abstractyes

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