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Record W2145050552 · doi:10.1080/01421590220134132

The East Anglia Deanery Communication Skills Teaching Project--six years on

2002· article· en· W2145050552 on OpenAlexaff
Juliet Draper, Jonathan Silverman, Arthur Hibble, R M Berrington, Suzanne Kurtz

Bibliographic record

VenueMedical Teacher · 2002
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of Calgary
FundersUniversity of Cambridge
KeywordsFacilitatorMedical educationTrainerCommunication skillsVocational educationMedicinePedagogyPsychologyComputer science

Abstract

fetched live from OpenAlex

This paper describes the Cascade Communication Skills Teaching Project, which is a programme of facilitator training enabling communication skills teaching in the consultation to general practitioners to be cascaded throughout the former East Anglia Deanery. The paper also explores the project's educational and organizational effectiveness. The programme is based on an ongoing training programme for a cohort of around 30 district-based communication skills facilitators, and was set up in the autumn of 1995. These facilitators are now able to act as a resource to cascade high-quality communication skills teaching into vocational training schemes, trainer education and the continuing professional development of established general practitioners throughout each district in the region. The project has now been extended into medical student teaching, specialist teaching at junior and senior level, and multi-disciplinary teaching.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.002
Scholarly communication0.0030.001
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.003

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.

Opus teacher head0.028
GPT teacher head0.339
Teacher spread0.311 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2002
Admission routes1
Has abstractyes

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