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Record W1982710505 · doi:10.3138/jvme.0912.082r

Subject Matter Expert and Public Evaluations of a Veterinary Toxicology Course Brochure-Writing Assignment

2013· article· en· W1982710505 on OpenAlexvenueno aff
David C. Dorman, Kristine M. Alpi, Kimberly H. Chappell

Bibliographic record

VenueJournal of Veterinary Medical Education · 2013
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsRubricReadabilityGrading (engineering)BrochureMedical educationMedicinePublic speakingPsychologyVeterinary medicineComputer scienceMathematics educationEngineering

Abstract

fetched live from OpenAlex

Veterinary schools are increasingly developing students' communication skills, with an emphasis placed on practice conveying medical and scientific knowledge to different audiences. We describe how patient-centered written communication has been integrated into the training of veterinary students using toxicology-related preventive materials. Third-year veterinary students were given an assignment to prepare a client-focused brochure related to veterinary toxicology. Since 2010, 148 students have completed this assignment, with an average score of 93.4%. Use of a grading rubric was instituted in 2011 and resulted in a more rigorous assessment of the brochures by the course instructors. In this study, we evaluated a sample (n=6) selected from 10 brochures volunteered for further public and expert assessment. Each brochure was measured for readability and assessed with a rubric for perceived usefulness and acceptability by 12 veterinary toxicologists and 10 or 11 adult members of the public attending a college of veterinary medicine open house. Veterinary toxicologist review anticipated that the brochures would be useful for most clients, and the public reviewers confirmed this assessment. Evaluation of the brochures using set marking criteria and readability indexes showed that students had successfully targeted the chosen audiences. Feedback showed that the general public rated the sample brochures highly in terms of quality, usefulness, and interest. Completion of this study has resulted in revision of the grading rubric, an increased use of brochure examples, and additional instruction in readability assessment and brochure development, thereby improving the assignment as a learning exercise.

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)0.019
metaresearch head score (Gemma)0.056
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.056
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
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 head0.074
GPT teacher head0.436
Teacher spread0.362 · 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.

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

Citations10
Published2013
Admission routes1
Has abstractyes

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