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Record W1982964773 · doi:10.3138/jvme.36.4.429

Utilizing Filmed Authentic Student–Client Interactions as a Communication Teaching Tool

2009· article· en· W1982964773 on OpenAlexvenueno aff
McArthur Hafen, Bonnie R. Rush, Susan C. Nelson

Bibliographic record

VenueJournal of Veterinary Medical Education · 2009
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSession (web analytics)PublicityProtocol (science)Medical educationStrengths and weaknessesCommunication skillsMultimediaPsychologyComputer scienceMedicineWorld Wide WebAlternative medicine

Abstract

fetched live from OpenAlex

In the past decade, communication training within veterinary medical training programs has received extensive publicity. Now, training programs are utilizing large-group lecturing, small-group discussions, and simulated client programs to address the need for veterinarians to effectively communicate with their clients. This paper presents a communication training protocol utilized at Kansas State University. The principle focus of this protocol is utilizing filmed student interactions with authentic veterinary medical clients. All veterinary medical students are required to film two interactions with hospital clientele. After each filmed session, students attend feedback sessions where communication strengths and weaknesses are discussed. Specific communication goals are identified for future interactions. A detailed description of the protocol follows, with preliminary impressions from students and instructors noted. As a promising tool for teaching communication skills, future directions for filmed authentic interactions are discussed.

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 categoriesInsufficient 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 score0.534
Threshold uncertainty score0.999

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.349
GPT teacher head0.600
Teacher spread0.251 · 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

Citations18
Published2009
Admission routes1
Has abstractyes

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