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Record W2904378219 · doi:10.3138/jvme.0917-119r

Current Policies and Support Services for Pregnant and Parenting Veterinary Medical Students and House Officers at United States Veterinary Medical Training Institutions

2018· article· en· W2904378219 on OpenAlexvenueno aff
Brianna L. Molter, Annie S. Wayne, Megan K. Mueller, Megan Gibeley, Marieke Rosenbaum

Bibliographic record

VenueJournal of Veterinary Medical Education · 2018
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsnot available
FundersBrown University
KeywordsDemographicsAccreditationMedicineConsistency (knowledge bases)Graduate medical educationFamily medicineMedical educationVeterinary medicine

Abstract

fetched live from OpenAlex

Wellness and work-life balance are prominent concerns in the veterinary profession and data suggest that personal relationship-building with peers and family assist veterinary trainees and veterinarians with wellness. The demographics of veterinary medical trainees (students, interns, and residents) have shifted to a female-dominated cohort and veterinary training overlaps with peak reproductive age for the majority of trainees. Despite a robust body of literature in the human medical profession surrounding pregnancy, parenting, and family planning (PPFP) among human medical students, interns, and residents, no comparable data exist within the United States veterinary medical community. This study reviewed policies and support services in place to support PPFP at accredited United States veterinary medical training institutions through the use of an online administrator survey and the review of handbooks and relevant written material. Results from this study highlight a lack of consistency across veterinary medical training institutions for policy and support services for PPFP for trainees, especially related to lactation support and parental leave. Our data can help facilitate the development of standards or best practices for policies and support services that support PPFP among veterinary medical trainees, and opens the dialogue to consider the unique needs of our shifted trainee demographics.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.773
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.458
GPT teacher head0.577
Teacher spread0.119 · 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

Citations7
Published2018
Admission routes1
Has abstractyes

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