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Record W2014111879 · doi:10.3138/jvme.35.1.091

Part III: A Case Study at the Virginia-Maryland Regional College of Veterinary Medicine

2008· article· en· W2014111879 on OpenAlexvenueno aff
Grant H. Turnwald, J. Blair Meldrum, D. Phillip Sponenberg

Bibliographic record

VenueJournal of Veterinary Medical Education · 2008
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumMedical educationCurriculum developmentCore curriculumCurriculum mappingProcess (computing)MedicinePolitical scienceEngineering ethicsSociologyPedagogyEngineeringComputer science

Abstract

fetched live from OpenAlex

This article presents a history of curriculum revision. Internal and external factors prompting the initial curriculum review included the Pew Report, a vision in the college for reform, and faculty retreats focusing on curriculum. The reformed curriculum was designed around a "core plus elective" strategy and was implemented following development by faculty representatives and approval by college and university levels of review. The curriculum was reviewed after being revised and after new courses were first offered, with further review of a few courses with specific challenges. Outcomes assessment was performed and curricular adjustments made. Challenges that arose during the process included organizing and documenting content as well as communicating the content and philosophy of the new curriculum to the various affected constituencies. A summary of factors considered essential to the successful design, implementation, and review of the new curriculum is presented; the majority of these factors would be applicable to reforms at other institutions.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0100.002
Scholarly communication0.0030.001
Open science0.0020.003
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.488
GPT teacher head0.555
Teacher spread0.067 · 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 designQualitative
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

Citations7
Published2008
Admission routes1
Has abstractyes

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