MétaCan
Menu
Back to cohort
Record W2062242899 · doi:10.1097/acm.0b013e31826291fa

Stability of Medical Student Career Interest

2012· article· en· W2062242899 on OpenAlexaffabout
Ian Scott, Margot Gowans, Bruce Wright, Fraser Brenneis

Bibliographic record

VenueAcademic Medicine · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedical educationPsychologyHigher educationMedicinePolitical science

Abstract

fetched live from OpenAlex

PURPOSE: To examine the stability and switching patterns of student career interests over the course of medical school. METHOD: From 2001 through 2004, during the first two weeks of classes, a survey on career interest was distributed to first-year students in 15 classes at eight Canadian medical schools. Students indicated interest in eight broad career paths (emergency medicine, family medicine, internal medicine, obstetrics-gynecology, pediatrics, psychiatry, surgery, and "other") and ranked their top three. Following these students' residency match three to four years later, student residency career choice was linked to their career interest at medical school entry. For students whose career interests switched be-tween medical school entry and exit, switching patterns were examined in terms of careers' matching difficulty scores (MDSs). RESULTS: Of 1,941 eligible students, 1,542 contributed to the final analysis. Family medicine, internal medicine, and surgery had the greatest student interest at both the beginning and end of medical school. Family medicine, surgery, obstetrics-gynecology, psychiatry, and "other" careers showed a net gain of student interest during medical school with the remaining careers showing a loss of interest. The most stable careers were family medicine, surgery, and internal medicine. The least stable were pediatrics and obstetrics-gynecology. Students tended to switch between careers with similar MDSs. CONCLUSIONS: Student career choice is relatively stable with a number of careers showing approximately 50% of stability from the entrance to the exit of medical school. Students tend to switch to careers with similar MDS, but some specific switching patterns exist.

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)0.009
metaresearch head score (Gemma)0.004
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.588
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.004
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.183
GPT teacher head0.432
Teacher spread0.249 · 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 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

Citations69
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueAcademic MedicineSame topicDiversity and Career in MedicineFrench-language works237,207