Strangers in a strange land: The experience of physicians undergoing remediation
Bibliographic record
Abstract
INTRODUCTION: The experience of remediation in practising physicians has not been widely studied. Remediatees frequently present negative emotions, but observers can only infer the underlying reasons behind these. Understanding remediatees' perspectives may help those mandating and organising remediation to structure the process in ways that improve the experience for all concerned parties and maximise chances of a successful outcome for remediatees. METHODS: Seventeen physicians who had undergone remediation for clinical competence concerns were interviewed via telephone. Participant data were first iteratively analysed thematically and then reanalysed using a narrative mode of analysis for each participant in order to understand the stories as wholes. Figured worlds (FW) theory was used as a lens for analysing the data for this constructivist research study. RESULTS: Participants entering the FW of remediation perceived that their position as a 'good doctor' was threatened. Lacking experience with this world and with little available support to help them navigate it, participants used their agency to draw on various discursive threads within the FW to construct a narrative account of their remediation. In their narratives, participants tended to position themselves either as victims of regulatory bodies or as resilient individuals who could make the best of a difficult situation. In both cases, the chosen discursive threads enabled them to maintain their self-identity as 'good doctor'. CONCLUSION: Remediation poses a threat to a physician's professional and personal identity. Focusing mainly on the educational aspect of remediation-that is, the improvement in knowledge and skills-risks missing its impact on physician identity. We need to ensure not only that we support physicians in dealing with this identity threat but that our assessment and remediation processes do not inadvertently encourage remediatees to draw on discursive threads that lead them to see themselves as victims.
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.016 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.005 |
| 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".