MétaCan
Menu
Back to cohort
Record W4312549419 · doi:10.1079/hai.2021.0005

Best in Show: Public Perceptions of Different Dog Breeds as Service Dogs

2021· article· en· W4312549419 on OpenAlexaboutno aff
Jennifer K. Link, Matthew Wice

Bibliographic record

VenueHuman-animal interaction bulletin · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLegitimacyPerceptionLabrador RetrieverService (business)BreedAnimal welfareHUBzeroAnimal-assisted therapyPsychologyPet therapySocial psychologyVeterinary medicineMedicinePolitical scienceBiologyAnimal scienceMarketingLawBusinessSurgeryEcology

Abstract

fetched live from OpenAlex

Abstract Recent research has shed light on the amount of discrimination faced by those who require service dogs ( Mills, 2017 ). While most of the research thus far on discrimination against those who use service dogs has pertained to the appearance of the disabled individual, very little has assessed the appearance of the dog in the amount of discrimination an individual faces. The current study aimed to examine the ways in which the breed of dog impacts the way they are viewed as Service Animals. Participants each looked at one picture of a dog, either a Pomeranian, a Pit Bull type dog, or a Labrador Retriever. They then answered a series of five questions about the animals’ legitimacy as a Service Animal. Pomeranians were rated significantly lower on perceived legitimacy than both Labrador Retrievers and Pit Bull type dogs. Additionally, participants rated themselves as the least comfortable around Pit Bull type dogs, regardless of their perceived legitimacy. These findings continue to shed light on the ways that individuals with service dogs are perceived and contributes to the larger body of research surrounding those who are discriminated against for their disability.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.716
Threshold uncertainty score1.000

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)0.0110.001

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 head0.037
GPT teacher head0.362
Teacher spread0.325 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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

Citations4
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueHuman-animal interaction bulletinSame topicHuman-Animal Interaction StudiesFrench-language works237,207