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Record W3012397042 · doi:10.22215/etd/2019-13702

Pet Ownership, Attachment, and Well-Being

2019· dissertation· en· W3012397042 on OpenAlexaff
Maria Pranschke

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsSocial connectednessPsychologyPsychosocialAnimal-assisted therapySocial psychologyDevelopmental psychologyClinical psychologyMedicineAnimal welfarePsychiatryPet therapyBiology

Abstract

fetched live from OpenAlex

The present research examined links between attachment to pets and psychological well-being in different populations. Key factors among pet owners that were expected to moderate the relationship between attachment and well-being, notably social connectedness and genetic polymorphisms relating to oxytocinergic functioning, were also explored. Survey responses and saliva samples were gathered from attendees at a pet exhibition (Study 1), members of the public (pet owners and non-owners) at a mall and museum (Study 2), and low-income, marginally housed pet owners (Study 3). Pet owners reported greater quality of life and were more likely to have a polymorphism of the oxytocin receptor gene (rs225429). However, across all three studies, greater attachment to pets was associated with negative psychological well-being and the presence of physical health conditions. Overall, findings suggest that pet attachment and its relation to human well-being can differ depending on psychosocial characteristics of pet 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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.013
GPT teacher head0.347
Teacher spread0.334 · 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 designObservational
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

Citations1
Published2019
Admission routes1
Has abstractyes

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Same topicHuman-Animal Interaction StudiesFrench-language works237,207