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Record W2337061150 · doi:10.3138/jvme.0715-121r

Incorporating Inter-Professional Education into a Veterinary Medical Curriculum

2016· article· en· W2337061150 on OpenAlexvenueno aff
Amara H. Estrada, Linda S. Behar‐Horenstein, Daniel J. Estrada, Erik W. Black, Alison Kwiatkowski, Annie Bzoch, Amy V. Blue

Bibliographic record

VenueJournal of Veterinary Medical Education · 2016
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsnot available
Fundersnot available
KeywordsAccreditationCurriculumInterprofessional educationMedical educationTeamworkExperiential learningHealth careMedicineHealth professionsProfessional developmentPharmacyPublic healthVeterinary medicineNursingPsychologyPolitical sciencePedagogy

Abstract

fetched live from OpenAlex

Inter-professional education (IPE) is identified as an important component of health profession training and is listed in the accreditation requirements for many fields, including veterinary medicine. The goals of IPE are to develop inter-professional skills and to improve patient-oriented care and community health outcomes. To meet these goals, IPE relies on enhanced teamwork, a high level of communication, mutual planning, collective decision making, and shared responsibilities. One Health initiatives have also become integral parts of core competencies for veterinary curricular development. While the overall objectives of an IPE program are similar to those of a One Health initiative, they are not identical. There are unique differences in expectations and outcomes for an IPE program. The purpose of this study was to explore veterinary medical students' perceptions of their interprofessional experiences following participation in a required IPE course that brought together beginning health profession students from the colleges of medicine, dentistry, nursing, pharmacy, nutrition, public health and health professions, and veterinary medicine. Using qualitative research methods, we found that there is powerful experiential learning that occurs for both the veterinary students and the other health profession students when they work together at the beginning of their curriculum as an inter-professional team.

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)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.654
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.000

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 head0.055
GPT teacher head0.495
Teacher spread0.440 · 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

Citations31
Published2016
Admission routes1
Has abstractyes

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