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Record W2288029726 · doi:10.1080/14427591.2011.586325

An Evolutionary Concept Analysis of Caring for a Pet as an Everyday Occupatio

2011· article· en· W2288029726 on OpenAlex

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

VenueJournal of Occupational Science · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsGlobeNewspaperPsychologyFlourishingMoralityEveryday lifeSocial psychologySociologyPublic relationsMedia studiesPolitical scienceLaw

Abstract

fetched live from OpenAlex

This study explores the everyday occupations of caring for a pet, as conveyed in the North American print media spanning 1999-2008 that discusses pet ownership. The incidence of pet ownership is increasing in North America and research suggests that pet ownership can improve health and well-being. Yet, to date, occupational scientists have contributed little to this growing knowledge base. The present study adopted Rodgers’ (2000) evolutionary concept analysis approach to analyze North American newspapers and bestselling books. Findings were synthesized with historical insights and accounts from around the globe. Analysis revealed that pet ownership is a complex concept consisting of: responsibility, investment, occupational engagement, entrepreneurship, relationships, morality, and attitude. Occupational engagement appeared as the central attribute. The Rubik's Cube emerged as a mental image representing the complexity of pet ownership. Having a mental image to study caring for a pet is the end product of concept analysis and can be useful for occupational scientists studying these occupations in the future.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.661
Threshold uncertainty score0.272

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 head0.060
GPT teacher head0.421
Teacher spread0.361 · 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