Career Mentors & 5-Year Data on the IUSM Anesthesiology Match
Bibliographic record
Abstract
Introduction: \nThe IU Department of Anesthesia provides Anesthesiology Career Mentors to 3rd and 4th year medical students. We have approximately 47 requests per class year. In the past 5 years, we have matched 181 students into Anesthesiology, averaging 36 students per year (range 30-46). \nWhere do these students match into Anesthesiology? How many of them use the Career Mentorship program? If they don’t choose Anesthesiology, which other specialties appeal to them? \n \nObjective: \nThe purpose of this presentation is to examine the pipeline of students interested in anesthesiology who request a career mentor and match into anesthesiology. \n \nMethods: \nMatch data from publicly obtained IUSM Graduation Booklets for the Class of 2017 through 2021 was filtered for those students matching into Anesthesiology Residency Programs. These programs were mapped and cross-referenced for medical school rankings based on the 2022 US News & World Report Medical School Rankings for Research. \n \nAnesthesiology career mentorship requests were tracked starting in 2019 for the class of 2020 onwards, so students who matched into Anesthesiology were cross-referenced with students who had formally requested Anesthesiology Career Mentors in 2020 and 2021. Students who had formally requested Anesthesiology Career Mentors in 2020 and 2021 were also cross-referenced with the IUSM Graduation Booklet data to see how many of these students matched into Anesthesiology or other fields. \n \nResults: \nOf the 181 students that have matched into Anesthesiology from 2017-2021, 63 students matched at IU (35%). The rest are distributed across the regions of the US, including residency programs at the top 25 medical schools including Harvard, NYU, Duke, Stanford, and UCSF. \n \nThe majority of students matching into Anesthesiology request Anesthesiology Career Mentors, with 73% (48/66) of students assigned to mentors in the graduating class of 2020 and 2021. 96 mentors were requested in the class of 2020 and 2021, with 29 students (30%) not matching into Anesthesiology. These students may have changed careers and not applied to Anesthesiology. Many of these students choose to pursue other specialties, including Internal Medicine, Radiology, Pediatrics, Family Medicine, General Surgery, Obstetrics-Gynecology, Orthopedic Surgery, and Psychiatry. Some students were not listed in the IUSM Graduation Booklet or did not have a residency listed. \n \nConclusion: \nLimitations of this analysis include students’ choice to publish their Match data in the IUSM Graduation Booklet and the possibility of some students being lost to follow up due to not graduating yet or changing their name. No direct link can be made between formally assigned Anesthesiology Career Mentors and the Match, especially since some students may have sought out informal mentorship. \n \nAnesthesiology continues to be a competitive field with high student interest. More research can be done to understand factors that influence student decisions for specialty and to track student alumni and follow their career progression into fellowship and the physician workforce. Additional data collection on the usefulness of the career mentorship program and ways to improve and further support student career choice and Match success will be especially helpful as Step 1 changes to pass/fail.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.039 | 0.027 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".