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Record W2120029972 · doi:10.1177/0193945914545176

A Qualitative Investigation of the Significance of Companion Dogs

2014· article· en· W2120029972 on OpenAlexafffund
Nandini Maharaj, Colleen J. Haney

Bibliographic record

VenueWestern Journal of Nursing Research · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsQualitative researchFocus groupPsychologyTheme (computing)Agency (philosophy)Interpersonal communicationInterpersonal relationshipContent analysisSocial psychologySociologySocial science

Abstract

fetched live from OpenAlex

Using a qualitative design, the purpose of this study was to examine how people describe their relationship with their dog and what they do that suggest this bond represents a meaningful relationship. Dog owners (N = 27) aged 19 years and older were invited to participate in one of seven focus group discussions. A qualitative content analysis revealed the presence of three themes: (a) the impact of dogs on interpersonal relationships, (b) dogs as subjective beings, and (c) psychological and health benefits of dogs. The second theme reflects the personal agency of dogs and their unique contributions to the human-dog relationship. These themes are discussed in light of the current research in the field. The findings suggest implications for counseling research and practice in improving the health and well-being of dog owners.

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)0.030
metaresearch head score (Gemma)0.038
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.038
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0070.009
Scholarly communication0.0030.004
Open science0.0020.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.181
GPT teacher head0.524
Teacher spread0.343 · 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

Citations47
Published2014
Admission routes2
Has abstractyes

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