Professional Identity Formation in medical school: One measure reflects changes during pre-clerkship training
Bibliographic record
Abstract
This article was migrated. The article was marked as recommended. Professional Identity Formation (PIF), the process of internalizing a profession's core values and beliefs, is an explicit goal of medical education. The Professional Identity Essay (PIE), a developmental measure of the extent to which individuals have a complex and self-defined understanding of their professional role, is a tool to both study and scaffold PIF. PIE staging has internal reliability and response process validity and correlates with a validated measure of moral reasoning. In this study, we investigate whether PIF, as measured by PIE, changes during pre-clerkship training. Medical students in the class of 2019 completed the PIE during orientation to medical school (PIE#1) and 15 months later, during orientation to clerkships (PIE#2), to the same prompts. These written responses are PIF-staged by an expert rater. On average, PIF scores reveal that 46% of the group remained at the same stage as they were on entry to medical school, 42% scored at a higher stage of PIF, and 15% of students scored at a lower stage of PIF after pre-clerkship training. This result suggests that medical students are heterogeneous with respect to the development of their medical PIF early in medical school training.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".