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Record W2308917828

Adding Reality to Clinical Skills Training: A Defining Point

2007· article· en· W2308917828 on OpenAlexaboutno aff
Helen Moriarty

Bibliographic record

VenueFocus on Health Professional Education A Multi-Professional Journal · 2007
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsCredentialingMedical educationCurriculumWorkforceSpecialtyMultidisciplinary approachMedicinePsychologyPolitical sciencePedagogyFamily medicine
DOInot available

Abstract

fetched live from OpenAlex

History shows that curriculum review has brought progressive change to undergraduate medical content, structure and strategic direction, but in recent times there has been escalation of change in response to the overcrowded medical curriculum, workforce shortages and credentialing issues. Current global trends include: problem-based learning replacing an older emphasis on didactic specialty lectures; increased community-based compared to a focus on hospital-based experience; more self-directed learning; inter-professional teaching and learning; and particular emphasis on the structure, nature and timing of clinical skills training. Our Faculty of Medicine funded a project on international perspectives on undergraduate clinical skills teaching and learning to inform such change. In our consultation project, a senior team of four multidisciplinary academic staff set out to collate peer-reviewed literature, including medical education conference proceedings, and to consult with international key informants (20 clinical skill tutors and programme managers, mostly from UK, Canada, USA, Australia and New Zealand) to identify the issues of primary importance to clinical skills teaching and learning and to develop a framework for further debate. This information was then discussed with local medical education consumers (our medical students) and producers (educationalists, clinicians and their patients) and key informants reviewed the final report before the web-based dissemination (Moriarty et al 2006) was launched.

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 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)0.016
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.796
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.143
GPT teacher head0.564
Teacher spread0.421 · 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 teacher head, not a consensus.

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

Citations0
Published2007
Admission routes1
Has abstractyes

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