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Record W2790796014 · doi:10.1163/15685306-12341495

Dogs on Campus

2018· article· en· W2790796014 on OpenAlex
John-Tyler Binfet, Kathryn Struik

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSociety and Animals · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsUniversity of British Columbia, Okanagan CampusKelowna General HospitalUniversity of British Columbia
Fundersnot available
KeywordsFormative assessmentMedical educationPsychologyAnimal-assisted therapyMedicinePet therapyAnimal welfarePedagogy

Abstract

fetched live from OpenAlex

Abstract Once used mostly in clinical settings such as hospitals and geriatric care centers, canine animal-assisted therapy programs have become increasingly commonplace on university campuses to reduce stress and support students’ social and emotional well-being. Researchers responding to the call for increased empirical rigor in studies assessing the effects of animal-assisted therapy and practitioners seeking to initiate well-being programs on campus can face challenges in accessing therapy dogs and their volunteer handlers. This article outlines how therapy canines and their handlers may be holistically assessed for participation in university-based initiatives and presents a model that includes the prescreening of volunteer handlers, training sessions for handlers, the use of multiple raters to assess canine temperament and behavior, the use of mock sessions, and the use of ongoing formative evaluation and feedback for handlers once they are accepted into the program.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score0.267

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.339
Teacher spread0.321 · 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