An evaluation of accessibility and content of microsurgery fellowship websites
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background Websites for residency and fellowship programs serve as effective educational and recruitment tools. Objective To evaluate the accessibility and content of fellowship websites that are commonly used by microsurgery applicants for career development. Methods A list of one-year microsurgery fellowship websites (MFWs) was compiled by visiting the centralized American Society for Reconstructive Microsurgery (ASRM) website, followed by performing an extensive ‘Google’ search in October 2015. Accessibility of MFWs was assessed. Website content regarding key recruitment and education variables was also comprehensively reviewed. Website content was correlated with program characteristics using t tests and ANOVA (two-tailed; P<0.05 was considered to be statistically significant). Results A list of 53 eligible programs was compiled. Only 15 of 51 (29%) ASRM program links were functional. On average, the combined content from ASRM website and individual MFWs had 2.91 of 6 recruitment variables and 1.32 of 6 education variables, respectively. The majority of programs listed ‘eligibility criteria’ (87%) and ‘general information’ (87%). ‘Evaluation criteria’ were most poorly reported (4%). Recruitment score was higher for United States programs compared with international counterparts (51% versus 33%, respectively; P=0.02). It was also higher in programs that focus on ‘extremity’ versus ‘breast’ (58% versus 37%; P=0.0028). Education scores did not differ according to location, program size, subspecialty of focus or participation in the Microsurgery Match process. Conclusion Information regarding recruitment and education on most MFWs is scarce. Academic institutions should keep website content up to date and comprehensive to better assist candidates in the application process.
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.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 it