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Record W2149170512

Re-entry residency training: opportunities and obstacles.

2010· article· en· W2149170512 on OpenAlexaffabout
Jean L. Jamieson, Eric M. Webber, Kristin S. Sivertz

Bibliographic record

VenuePubMed · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsStornoway Diamond (Canada)
Fundersnot available
KeywordsRetrainingSpecialtyTraining (meteorology)MedicineFlexibility (engineering)Family medicineMedical educationPopulationService (business)WorkforceManagementBusiness
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To identify and quantify the reasons general practitioners and family physicians consider retraining and their reasons for not pursuing further training. DESIGN: Population-based mailed survey. SETTING: British Columbia. PARTICIPANTS: Family physicians and general practitioners identified by the College of Physicians and Surgeons of British Columbia. MAIN OUTCOME MEASURES: Practising physicians' level of awareness of the University of British Columbia's re-entry training program, the number and demographic characteristics of those who had considered retraining, their specialties of interest, and the barriers and possible inducements to retraining. RESULTS: Only half of the survey respondents were aware of the re-entry training program at the University of British Columbia. A small but substantial number of practising general practitioners and family physicians were interested in taking specialty training from the Royal College of Physicians and Surgeons of Canada. While several training programs were particularly popular (ie, anesthesia and psychiatry--18.5% of respondents for each), almost every specialty training program was mentioned. Physicians identified the length and hours of training, financial issues, family issues, and the need for relocation as obstacles to retraining. The availability of part-time training, regional training, and return-of-service financial assistance were all identified as potential inducements. CONCLUSION: To meet the needs of practising physicians, re-entry training programs will need to consider flexibility, where feasible, with regard to choice of specialty, intensity, and location of postgraduate training.

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)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.248

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.139
GPT teacher head0.276
Teacher spread0.137 · 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 designQualitative
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
Published2010
Admission routes2
Has abstractyes

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Same venuePubMed→Same topicDiversity and Career in Medicine→French-language works237,207→