Beyond Traditional: Clearing the Roadblocks to Advancement in Academic Medicine
Bibliographic record
Abstract
In academic medicine, the label of nontraditional is often used to refer to scholars whose outputs or journeys differ from what is considered normative. Those who do not sufficiently align with traditional expectations may be at risk of being excluded from fully participating or achieving advancement in academic medicine, an experience that disproportionately affects groups who have been historically marginalized and underrepresented in medicine. In this eye opener, the authors use the lenses of their own stories in academic medicine to illustrate some of the traditional roadblocks experienced by these scholars, such as the lack of mentorship, the tendency to overlook or discourage work on nontraditional topics, and difficulty fitting innovative scholarship formats into curricula vitae or promotion packets. To clear the roadblocks, the authors call upon institutional leaders to enhance their processes, support systems, and criteria for learner and faculty academic advancement. Secondly, the authors call upon individuals to consider how they might engage in and frame their scholarly pursuits in a way that their merit can be readily ascertained.
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 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 | 0.060 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.031 | 0.116 |
| Scholarly communication | 0.041 | 0.050 |
| Open science | 0.004 | 0.035 |
| Research integrity | 0.010 | 0.023 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".