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Record W2060592843 · doi:10.3138/jvme.34.3.340

Factors Associated with Practice Decisions of Nebraska Veterinarians Regarding Type of Practice and Community Size

2007· article· en· W2060592843 on OpenAlexvenueno aff
John A. Schmitz, Rebecca J. Vogt, Gary P. Rupp, Bruce W. Brodersen, Jeramie M. Abel, Arden Wohlers, David B. Marx

Bibliographic record

VenueJournal of Veterinary Medical Education · 2007
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsMedical educationPractice managementPsychologyMedicineFamily medicine

Abstract

fetched live from OpenAlex

Nebraska veterinary practitioners were surveyed to collect data about background characteristics and other factors related to veterinarians' decision to include or not include food animals in their practices and to practice in rural versus urban communities. Background characteristics that were significantly (p < or = 0.05) associated with choosing food-animal practice included growing up on a working farm or ranch; having parents who owned livestock; growing up in a town with a population of less than 10,000; majoring in animal science at university; being male; and having a primary interest, at the time of entering veterinary college, in food animal-exclusive or mixed-animal veterinary practice. The primary factor for choosing the community in which to practice was rural/urban lifestyle for rural veterinarians, while this factor was second for urban veterinarians. For all groups of veterinarians, the primary consideration in selecting their current practice was the species orientation of the practice. The primary reason for not choosing food-animal practice was better working conditions and lifestyle in companion-animal practice, followed by greater interest elsewhere.

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)0.009
metaresearch head score (Gemma)0.140
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.131
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.140
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.229
GPT teacher head0.543
Teacher spread0.314 · 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 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

Citations16
Published2007
Admission routes1
Has abstractyes

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