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Transplant Surgery Fellow Perceptions About Training and the Ensuing Job Market—Are the Right Number of Surgeons Being Trained?

2011· article· en· W1523587233 on OpenAlexaboutno aff
David J. Reich, John C. Magee, Kimberly A. Gifford, Robert M. Merion, John P. Roberts, G Klintmalm, Peter G. Stock

Bibliographic record

VenueAmerican Journal of Transplantation · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsnot available
FundersCollege of Medicine, Drexel UniversityDrexel University
KeywordsMedicinePerceptionTraining (meteorology)Medical educationSurgeryPhysical therapy

Abstract

fetched live from OpenAlex

The American Society of Transplant Surgeons (ASTS) sought whether the right number of abdominal organ transplant surgeons are being trained in the United States. Data regarding fellowship training and the ensuing job market were obtained by surveying program directors and fellowship graduates from 2003 to 2005. Sixty-four ASTS-approved programs were surveyed, representing 139 fellowship positions in kidney, pancreas and/or liver transplantation. One-quarter of programs did not fill their positions. Forty-five fellows graduated annually. Most were male (86%), aged 31–35 years (57%), married (75%) and parents (62%). Upon graduation, 12% did not find transplant jobs (including 8% of Americans/Canadians), 14% did not get jobs for transplanting their preferred organ(s), 11% wished they focused more on transplantation and 27% changed jobs early. Half fellows were international medical graduates; 45% found US/Canadian transplant jobs, particularly 73% with US/Canadian residency training. Fellows reported adequate exposure to training volume, candidate selection, pre/postoperative care and organ procurement, but not to donor management/selection, outpatient care and core didactics. One-sixth noted insufficient ‘mentoring/preparation for a transplantation career’. Currently, there seem to be enough trainees to fill entry-level positions. One-third program directors believe that there are too many trainees, given the current and foreseeable job market. ASTS is assessing the total workforce of transplant surgeons and evolving manpower needs. The American Society of Transplant Surgeons (ASTS) sought whether the right number of abdominal organ transplant surgeons are being trained in the United States. Data regarding fellowship training and the ensuing job market were obtained by surveying program directors and fellowship graduates from 2003 to 2005. Sixty-four ASTS-approved programs were surveyed, representing 139 fellowship positions in kidney, pancreas and/or liver transplantation. One-quarter of programs did not fill their positions. Forty-five fellows graduated annually. Most were male (86%), aged 31–35 years (57%), married (75%) and parents (62%). Upon graduation, 12% did not find transplant jobs (including 8% of Americans/Canadians), 14% did not get jobs for transplanting their preferred organ(s), 11% wished they focused more on transplantation and 27% changed jobs early. Half fellows were international medical graduates; 45% found US/Canadian transplant jobs, particularly 73% with US/Canadian residency training. Fellows reported adequate exposure to training volume, candidate selection, pre/postoperative care and organ procurement, but not to donor management/selection, outpatient care and core didactics. One-sixth noted insufficient ‘mentoring/preparation for a transplantation career’. Currently, there seem to be enough trainees to fill entry-level positions. One-third program directors believe that there are too many trainees, given the current and foreseeable job market. ASTS is assessing the total workforce of transplant surgeons and evolving manpower needs.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.293
Threshold uncertainty score0.629

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.258
Teacher spread0.235 · 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 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

Citations40
Published2011
Admission routes1
Has abstractyes

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