MétaCan
Menu
Back to cohort
Record W2057774617 · doi:10.3138/jvme.33.1.105

Facilitator Training for Undergraduate Veterinary Communication Education in the United Kingdom and Ireland

2006· article· en· W2057774617 on OpenAlexvenueno aff
Carol Gray

Bibliographic record

VenueJournal of Veterinary Medical Education · 2006
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFacilitatorCommunication skillsMedical educationTraining (meteorology)Veterinary medicineUnit (ring theory)MedicinePolitical sciencePsychologyGeography

Abstract

fetched live from OpenAlex

As described in detail in a companion article, 1 a major effort has been undertaken to help the development of communications skills teaching in veterinary schools in the United Kingdom and Ireland. Two particular consequences have been the establishment of National Unit for the Advancement of Veterinary Communication Skills (NUVACS) and the appointment of a NUVACS lecturer whose responsibility is to facilitate the growth of communications skills in all of the veterinary schools. These efforts have been funded by the Veterinary Defence Society. It is this society’s observation that more than 80% of complaints brought against veterinarians revolve around problems of poor communication. One key element of the NUVACS activities has been training the facilitators who will provide student communication skills training. These endeavors are described in this report.

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)0.011
metaresearch head score (Gemma)0.017
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 score0.017
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0170.003

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 head0.492
GPT teacher head0.557
Teacher spread0.065 · 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

Citations4
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Veterinary Medical EducationSame topicVeterinary Practice and Education StudiesFrench-language works237,207