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Record W1731741333 · doi:10.36834/cmej.36585

Radiation Oncology Workforce Recruitment Survey of 2000-2010 Graduates: Is There Need for Better Physician Resource Planning?

2012· article· en· W1731741333 on OpenAlexaffvenueabout
Shaun Loewen, Michael Brundage, Keith Tankel, Alysa Fairchild, Theresa Trotter, Ericka Wiebe, Paris Ann Ingledew, Teri Stuckless, Don Yee

Bibliographic record

VenueCanadian Medical Education Journal · 2012
Typearticle
Languageen
FieldMedicine
TopicAdvances in Oncology and Radiotherapy
Canadian institutionsDr. H. Bliss Murphy Cancer CentreThames Valley Children's CentreHealth Sciences CentreAlberta Cancer FoundationSunnybrook Health Science CentreCancer Care South East
Fundersnot available
KeywordsRadiation oncologySpecialtyWorkforceMedicineCertificationRadiation TherapistCurriculumFamily medicineMedical educationPsychologyInternal medicineManagementRadiation therapyPolitical science

Abstract

fetched live from OpenAlex

PURPOSE OF THE STUDY: To survey employment and training characteristics of Canadian radiation oncology training program graduates and foreign medical graduates with Canadian radiation oncology post-graduate education or specialist certification. METHODS: A 38-question, web-based survey was distributed to radiation oncologists who completed specialty training between 2000-2010. RESULTS: Out of 256 radiation oncologists contacted, 148 completed the survey (58% response rate). Thirty-two respondents (22%) were foreign MD graduates. One-hundred and fifteen respondents (78%) undertook fellowship training after residency. Many Canadian MD graduates (77%) and foreign MD graduates (34%) had staff positions in Canada, while 11% of all respondents had staff positions outside Canada, and 21% did not have a commitment for staff employment. Of the 31 respondents without a staff position, 22 graduated from Canadian residency training in 2009 or 2010, and 21 had completed medical school training in Canada. CONCLUSIONS: The majority of respondents were successful in securing staff positions in Canada. A sizeable proportion extended training with fellowships. New graduates may have more difficulty in finding Canadian staff positions in radiation oncology in the near future. Implications for specialty training programs and for an improved national strategy for physician resource planning are discussed.

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)0.002
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.438
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0030.000

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 head0.063
GPT teacher head0.422
Teacher spread0.359 · 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

Citations12
Published2012
Admission routes3
Has abstractyes

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