Capturing the Moments: An Autoethnographic Exploration of Self-Preservation in Clerkship
Bibliographic record
Abstract
Phenomenon For most medical students, clerkship represents a transitional phase into the ‘real world’ of medicine. This transition is often accompanied by significant mental stressors, burnout, and empathy decline. Educator led resilience curricula designed to support students during this critical period often focus on teaching generalized strategies to promote wellness and lack the student input and perspective in their development. Thus, they may be of minimal value when learners are faced with acute moments of challenge and distress in their day-to-day work. The following project seeks to provide an insider view on the experience, interpretation, and response to these moments of challenge and distress from the frontline perspective of clinical clerks. Approach: Using collaborative autoethnography, two medical students documented 85 reflections on their emerging professional identity over the course of a core clerkship year. A narrative analysis was conducted iteratively in partnership with a staff internist and a medical education researcher experienced in autoethnography, allowing for robust multi-perspective input. Reflections were analyzed and coded thematically; disagreements were resolved by consensus discussion. Findings: A key theme of the reflections was self-preservation, conceptualized within two principal contexts: (i) Clerk-patient relationships, wherein we found ourselves in emotionally difficult situations; and (ii) Clerk-preceptor relationships, in which self-preservation manifested through a series of self-protective mechanisms. Insights: The practice of self-preservation is understood as the conscious act of boundary-setting and psychological defense in situations that pose a real (or perceived) threat to the clerk’s wellbeing. At best, self-preservation serves as a temporary compromise to the stressors and burnout of clerkship. We speculate, however, that, left unchecked, acts of self-preservation may lead to habitual selfishness and apathy, qualities that are in diametric opposition to those expected of future physicians, and may manifest later (when these learners progress through the hierarchy) as the unprofessional behaviors that perpetuate the cycle of the hidden curriculum.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".