Pimping in Residency: The Emotional Roller-Coaster of a Pedagogical Method – A Qualitative Study Using Interviews and Rich Picture Drawings
Bibliographic record
Abstract
Phenomenon: Pimping has become a well-known and distinct form of questioning in medical education, and as a pedagogical method it has both proponents and detractors. Pimping occurs when a teacher (pimper) asks difficult questions of the learner (pimpee), usually in rapid succession. There is a paucity of literature formally studying this technique and its effects on teachers and learners. Our study examines the use of and attitudes toward pimping in a pathology residency program to better understand its perceived value and effectiveness. Approach: Using a qualitative approach, we conducted semistructured interviews with 8 pathology trainees and 9 pathologists. As part of the interview process, we asked participants to draw a rich picture of a pimping encounter. Consistent with this qualitative method, we analyzed data iteratively using constant comparison. Findings: Negative emotions including anxiety and self-doubt dominated among the learners during pimping encounters. For some, these resulted in motivation to study, and for others this was a futile, nonmotivating experience. Most trainees felt that they were being judged during pimping; however, they perceived that the intentions of pimping were not malicious and in their best interests. This was supported by pathologists, who stated that their motivation for pimping was to identify knowledge gaps, thus benefiting the trainee. Insights: Pimping created a dichotomy of emotions within the majority of learners in this study. Negative emotions occurred during pimping encounters; however, following the encounter, pimping was perceived in a more positive light. Recognizing when and how pimping can create negative emotions that may interfere with learning may enable educators to create more consistently meaningful interactions.
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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 | 0.019 | 0.024 |
| 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 | 0.013 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".