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Record W3117334609 · doi:10.36834/cmej.70348

Factors influencing rheumatology residents’ decision on future practice location

2020· article· en· W3117334609 on OpenAlexafffundvenueabout
Justin Shamis, Jessica Widdifield, Michelle Batthish, Dharini Mahendira, Shahin Jamal, Alfred Cividino, Brendan Cord Lethebe, Claire Barber

Bibliographic record

VenueCanadian Medical Education Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal Disorders and Rehabilitation
Canadian institutionsUniversity of CalgaryUniversity of British ColumbiaSunnybrook Health Science CentreMcMaster UniversityUniversity of Toronto
FundersCanadian Rheumatology Association
KeywordsRheumatologyInternal medicineFamily medicineMedicineTelehealthPolitical scienceHealth careTelemedicine

Abstract

fetched live from OpenAlex

BACKGROUND: There are regional disparities in the distribution of Canadian rheumatologists. The objective of this study was to identify factors impacting rheumatology residents' postgraduate practice decisions to inform Canadian Rheumatology Association workforce recommendations. METHODS: test. RESULTS: A total of 34 of 67 residents completed the survey. Seventy-three percent of residents planned to practice in the same province as their rheumatology training. The majority of residents (80%) ranked proximity to friends and family as the most important factor in planning. Half of participants had exposure to alternative modes of care delivery (e.g. telehealth) during their rheumatology training with fifteen completing a community rheumatology elective (44%). CONCLUSIONS: The majority of rheumatology residents report plans to practice in the same province as they trained, and close to home. Gaps in training include limited exposure to community electives in smaller centers, and training in telehealth and travelling clinics for underserviced populations. Our findings highlight the need for strategies to increase exposure of rheumatology trainees to underserved areas to help address the maldistribution of rheumatologists.

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)0.000
metaresearch head score (Gemma)0.054
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.549
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.054
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)0.0060.000

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 head0.012
GPT teacher head0.315
Teacher spread0.303 · 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 designNot applicable
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

Citations1
Published2020
Admission routes4
Has abstractyes

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