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Record W2171366267 · doi:10.3109/0142159x.2012.737960

Medical dramas on television: A brief guide for educators

2012· article· en· W2171366267 on OpenAlex
Cassandra J. Hirt, Kelly Wong, Sune Brinch Erichsen, Julian White

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMedical Teacher · 2012
Typearticle
Languageen
FieldHealth Professions
TopicFilm in Education and Therapy
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDramaPopularityCLIPSMedical illustrationMedical educationPower (physics)PsychologyMultimediaMedicineVisual artsComputer scienceArtSurgerySocial psychology

Abstract

fetched live from OpenAlex

The popularity of medical television dramas is well-established and medical educators are beginning to recognize the power of medical media as a potential tool for education. The purpose of this study was to view a number of medical dramas and consider their potential use in medical education. A total of 177 episodes from eight popular television medical dramas produced between 1990 and 2009 were systematically viewed and analyzed and a brief guide was developed for each drama. The dramas analyzed contained a wealth of material applicable to medical education. In our experience, each drama may be best suited to a particular educational use: for example, clips from "ER" and "Scrubs" offer more examples of teaching and learning than "House" and "Grey's Anatomy", which are perhaps better suited for topics on ethics or team work. We hope that this brief guide will encourage others to consider integrating this material into their teaching, and to explore how television drama may be used most effectively in medical education.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.431
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1370.002

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.

Opus teacher head0.072
GPT teacher head0.494
Teacher spread0.422 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it