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Record W3208348659

Veterinary Practice - The Canadian multinational veterinary workforce.

2021· article· en· W3208348659 on OpenAlexaffabout
Terry L Whiting

Bibliographic record

VenuePubMed · 2021
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsCanadian Women's Health Network
Fundersnot available
KeywordsWorkforceContext (archaeology)Public relationsPolitical scienceMultinational corporationVeterinary medicineMedicineGeography
DOInot available

Abstract

fetched live from OpenAlex

The veterinary profession, from acceptance to veterinary college to retirement, has experienced extensive organizational change in the past 3 decades. This paper is an attempt to understand the context and complexity of national workforce planning in veterinary medicine in Canada. It identifies the obvious practical and ethical considerations, exposing inherent problems in guiding the future of the profession. The discourse concludes there is a structural deficiency in veterinary education program capacity in Canada (practical fact) and Canadian youth may have increasingly difficult access to tertiary education (ethical concern). Adaptation, rather than planning, characterizes current practices in which migration of foreign-trained veterinarians mitigates the structural deficiency in training capacity. Due to the pervasive adoption of neo-liberal marketing principles in tertiary education, a nationally self-sufficient Canadian veterinary college infrastructure is an unlikely future possibility. Our current system, reliant on migration of internationally trained professionals, raises questions of global justice and individual rights. Strategic solutions require reflection on veterinary professional identity, broad discussion, and a commitment to a rigorous concept of professional responsibilities, global citizenship, and the public good.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.620
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.420
GPT teacher head0.483
Teacher spread0.062 · 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 designNot applicable
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

Citations2
Published2021
Admission routes2
Has abstractyes

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Same venuePubMedSame topicVeterinary Practice and Education StudiesFrench-language works237,207