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Record W2123432121 · doi:10.3138/jvme.29.3.157

The Cornell Leadership Program for Veterinary Students

2002· article· en· W2123432121 on OpenAlexvenueno aff
Douglas D. McGregor, David R. Fraser

Bibliographic record

VenueJournal of Veterinary Medical Education · 2002
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsnot available
FundersUniversity of California, DavisRichard King Mellon Foundation
KeywordsTeamworkMedical educationVocational educationVeterinary medicinePsychologyGraduate studentsMedicinePolitical sciencePedagogy

Abstract

fetched live from OpenAlex

Cornell University hosts a summer program for veterinary students who aspire to research careers. The program features independent, faculty-guided research; vocational counseling; and professional enrichment activities that seek to build teamwork skills and to foster critical thinking and effective communication. A total of 255 students from 49 veterinary colleges worldwide have taken part in the program since 1990. Among those who have completed their veterinary education, approximately half have followed career trajectories of the kind envisioned by the program. While this outcome is gratifying, it was also learned that some program graduates subsequently withdrew from a research-oriented academic track after many years of graduate study. That disquieting outcome underscores the need to inform aspiring veterinary scientists about the realities of a research career; to structure their graduate studies in a manner that will maximize their prospects of success; to provide them with ongoing guidance and assistance; and to reward them at a level that will ensure that they remain in training for a period sufficient to realize their career expectations.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score0.965

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.743
GPT teacher head0.606
Teacher spread0.137 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations9
Published2002
Admission routes1
Has abstractyes

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