Trying to Stand Out: Analysis of "Extracurricular" Activities Of Otolaryngology Residency Applicants
Bibliographic record
Abstract
Medical students strategically engage in extracurricular activities outside the formal curriculum to distinguish themselves from peers and improve their candidacy for a residency program. This study explores longitudinal characteristics and prevalence of these activities reported by applicants to competitive Canadian OTL-HNS residency across time. A retrospective, descriptive study was designed to review specific sections of the curriculum vitae of applicants to OTL-HNS programs in Canada. These sections were self-reported, and included research productivity, involvement in volunteer and leadership activities, membership in associations, and honours / awards granted. Analysis of the results relied on descriptive statistics. Between 2013 to 2017, a total of 267 applicants reported a median of 12.6 research publications, 9.6 volunteer activities, 6 leadership activities, 6 association memberships and 9.8 honours / awards. At least one applicant every year reported having over 46 publications, and over 32 honours/ awards. Applicants were younger over time, with proportions of applicants over 30 years old decreasing from 56% in 2013 to 9% in 2017. Medical students applying to Canadian OTL-HNS residency programs are reporting consistently high rates of extracurricular activities. As students pursue becoming the “ideal” candidate with unobtainable and unsustainable qualifications, residency selection committees have difficulty in differentiating between quality applicants. We urge key stakeholders to challenge and rethink the current application process, to broaden the selection criteria, and to adapt a more holistic assessment of medical students aligned with residency goals and expectations toward competency.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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 teacher head, 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".