Bibliographic record
Abstract
ALL INDICATIONS SUGGEST THAT CINEMEDUCATION IS HERE TO STAY. The use of film as a bona fide teaching tool appears to be occurring everywhere, from film-based, state-sanctioned continuing education classes for psychologists and social workers 1 , 2 to common utilization as an adjunct to psychotherapy. 3–5 Some residency programs have a regular “movie night” in which films are watched in their entirety and then discussed for learning purposes. 6 Entire courses are being offered based on movies that shed light on various aspects of the medical profession. 7 A recent issue of the International Review of Psychiatry was devoted to cinema, showcasing the worldwide appeal of film as a teaching tool and featuring authors from India, Denmark, New Zealand, Australia, and Canada (as well as prominent medical educators from the United States and the United Kingdom). 8 A few chapters in this landmark issue highlighted non-English-speaking films, such as those from Malaysia or from specific Indian cultures (Kannada, Tamil Nadu, Hindi), that are useful in graduate and medical education programs. Also, it’s no longer just film that is being used for teaching; many educators are now using clips from televised medical dramas in their medical and graduate programs. 9 , 10
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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; both teacher heads agree on what is shown here.
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".