Dermatological games: Part 1. Original description and critique
Bibliographic record
Abstract
'Dermatological games' by J. A. Cotterill was a seminal article published in 1981, which attempted to explain the interaction between dermatologists and patients using Berne's game theory. In Part 1 of this series of two reviews, we review Cotterill's original list of games and how they applied to dermatology in the context of when they were written. We then critically appraise Cotterill's article and arguments. Although the article was deliberately provocative, we found Cotterill's arguments to be well-structured and logical, and the 'games' described are well-conceived. Cotterill's candid analysis of doctors' motivations and the potential impact on the patient is refreshing and insightful. It is striking that, 40 years on, many of the original 'games' described remain recognizable in current practice. In Part 2, a list of new 'games' that might be observed in modern dermatological practice is introduced. The relevance of Cotterill's paper and an explanation for why his educational article remains relevant to dermatology practice and training today is scrutinized in order to stimulate discussion, promote education and improve patient care.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".