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Record W2113291407 · doi:10.3138/jvme.1114-115r

Development, Evaluation, and Evolution of a Peer Support Program in Veterinary Medical Education

2015· article· en· W2113291407 on OpenAlexvenueno aff
Stacy Spielman, Kirsty Hughes, Susan Rhind

Bibliographic record

VenueJournal of Veterinary Medical Education · 2015
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsnot available
FundersNational Eating Disorders Association
KeywordsMedical educationPeer supportConfidentialityPeer feedbackPeer mentoringPsychologyPeer reviewPeer groupFocus groupDistrustMedicineNursingPolitical scienceSociology

Abstract

fetched live from OpenAlex

The majority of peer support programs in UK universities focus on academic support (e.g., through peer-assisted learning programs). Following student consultation, a pilot pastoral-based student peer support program was developed and implemented in a UK veterinary school. Thirty-one students were trained in the pilot year, and continued with the program to the end of the academic year (and beyond). The trainees were asked for feedback at the end of training and at the end of the year; the rest of the student body was surveyed as to their perception of the peer support program at the end of the year. Feedback from the training (N=19) was positive, with themes of enhanced self-development, improved communication skills, and bonding with other trainees. The wider student body responded (N=497) with concerns over confidentiality within a small community and distrust due to the competitive environment. Despite this, however, most students (74%) agreed that having peer support available created a supportive atmosphere, even if they did not personally plan on using the program. The paper concludes with a description of the changes being made to the program as a result of the evaluation.

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)0.010
metaresearch head score (Gemma)0.015
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.701
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.470
GPT teacher head0.598
Teacher spread0.129 · 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 designOther design
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

Citations14
Published2015
Admission routes1
Has abstractyes

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