Room for improvement: Palliating the ego in feedback-resistant medical students
Bibliographic record
Abstract
Feedback in medical education provides the impetus for growth in a field pressured to demonstrate continuous progress. Unfortunately, as it always incorporates some level of judgment, certain students appear more resistant than receptive to receiving feedback. Coupled with the ubiquitous stressors of medicine-examinations, perpetual knowledge acquisition, competition for employment-there subtly emerges a learning environment in which the mindset of medical trainees morphs from collegiality to outperformance of one's peers. As the unconscious mind is ultimately focused on self-protection, the cognitive response of reflecting upon received feedback is overcome by an emotional response to safeguard one's self-image against criticism in a culture of comparison. Although self-confidence plays a critical role in mitigating burnout, the relationship between resiliency and ego-armoring is rarely discussed in the literature. Consequently, despite the best intentions of educators in fostering clinical maturity among their trainees, the fact remains that insecurity, inadequacy and invulnerability continue to drive feedback-resistance among medical students.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".