MétaCan
Menu
← Back to cohort
Record W1972765890 · doi:10.3138/jvme.35.4.567

LIVE: The Creation of an Academy for Veterinary Education

2008· article· en· W1972765890 on OpenAlexvenueno aff
Birgit Pirkelbauer, Matthew J. Pead, Paul Probyn, Stephen A. May

Bibliographic record

VenueJournal of Veterinary Medical Education · 2008
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsnot available
FundersKU Leuven
KeywordsExcellenceVeterinary educationIncubatorMedical educationVeterinary medicineFaculty developmentProfessional developmentMedicineSociologyPolitical scienceCurriculumPedagogyBiology

Abstract

fetched live from OpenAlex

The purpose of this paper is to introduce a new educational development and research program; to describe the vision which created the LIVE Centre for Excellence in Teaching and Learning (CETL) at the Royal Veterinary College, University of London, UK; and to give details of the educational developments and research that have been pursued in LIVE since 2005. LIVE's purpose, to act as an "incubator" to help support all those interested in veterinary teaching and learning, and associated research, is discussed. The paper describes how the aims of the initial funding bid are being realized through the development of a multi-layered strategy. The discussion concludes by suggesting that new faculty models such as the US Academy Network for Medical Educators or veterinary hubs such as LIVE could act as catalysts for the development of a new breed of clinical teachers and educational researchers, empowered by innovative teaching and learning methods relevant to both medical and veterinary 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.

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)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.029
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0050.004
Scholarly communication0.0090.008
Open science0.0020.016
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0290.007

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 head0.090
GPT teacher head0.456
Teacher spread0.367 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations9
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Veterinary Medical Education→Same topicInnovations in Medical Education→French-language works237,207→