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Record W2035303994 · doi:10.3138/jvme.32.4.447

Animal Welfare Training at the Ontario Veterinary College

2005· article· en· W2035303994 on OpenAlexaffvenueabout
Suzanne T. Millman, Cindy L. Adams, Patricia V. Turner

Bibliographic record

VenueJournal of Veterinary Medical Education · 2005
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsAnimal welfareTraining (meteorology)Veterinary medicineMedical educationWelfareMedicinePolitical scienceBiologyGeography

Abstract

fetched live from OpenAlex

The University of Guelph is internationally recognized as a leader in animal welfare and is home to the Colonel K.L. Campbell Centre for the Study of Animal Welfare and to numerous faculty with expertise in the discipline. However, while animal welfare receives significant attention within the agricultural college, its didactic teaching within the veterinary curriculum has been limited. Veterinary students receive four hours of instruction in animal ethics and apply their knowledge within the communication lectures and laboratories, totaling 11-15 hrs. Compulsory coursework explicitly addressing factual components of animal welfare science, welfare assessment, and associated animal-related policy constitute only 12 hrs throughout the four-year Doctor of Veterinary Medicine curriculum. However, an elective final-year clinical rotation and a graduate course specific to animal welfare were offered for the first time in 2004/2005. Student interest in animal welfare is evident through their participation in summer research projects in animal welfare, an animal welfare mentor group, and a student-run animal welfare club that organizes an Animal Welfare Forum each October. Veterinarians have important contributions to make in decision making about animal welfare issues, at clinician and policy levels. Although motivated individuals can seek out opportunities to expand their knowledge of animal welfare, a compulsory senior-level course in animal welfare is needed to develop the necessary depth of understanding of this discipline if veterinarians, as a profession, are to meet society's expectations about animal welfare.

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)0.003
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: none
Teacher disagreement score0.558
Threshold uncertainty score0.889

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1650.023

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 head0.416
GPT teacher head0.527
Teacher spread0.111 · 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

Citations23
Published2005
Admission routes3
Has abstractyes

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