MétaCan
Menu
Back to cohort
Record W50503495

Demographics and career path choices of graduates from three Canadian veterinary colleges.

2008· article· en· W50503495 on OpenAlexaffabout
Murray Jelinski, John Campbell, K. Lissemore, Lisa M. Miller

Bibliographic record

VenuePubMed · 2008
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsGraduation (instrument)DemographicsVeterinary medicineCareer pathPopulationMedicineDemographySociologyManagementEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

The classes of 2007 from the Atlantic Veterinary College, Ontario Veterinary College, and Western College of Veterinary Medicine were surveyed to determine what factors influenced the respondents' career path choices. Seventy percent (166/237) of those contacted participated in the survey of which 89.1% were female, 62.7% had an urban upbringing, and 33.0% expected to be employed in a small center (population < or = 10,000). Half (52.5%) of the respondents reported that they were interested in mixed or food animal practice at the time of entry into veterinary college, but this proportion declined to 34.2% by the time of graduation. Three factors were significantly associated with choosing a career in mixed or food animal practice: having been raised in a small center, being a male, and having a good to excellent knowledge of food animal production at the time of entry into veterinary college, as determined by a self-assessment.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.999
Threshold uncertainty score0.490

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.368
GPT teacher head0.382
Teacher spread0.014 · 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.

Study designObservational
DomainIncentives
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

Citations17
Published2008
Admission routes2
Has abstractyes

Explore more

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