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Record W2119896435 · doi:10.1080/01490400.2014.888020

On the Fence: Dog Parks in the (Un)Leashing of Community and Social Capital

2014· article· en· W2119896435 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

VenueLeisure Sciences · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsFence (mathematics)Social capitalCapital (architecture)SociologyGeographySocial scienceArchaeologyEngineering

Abstract

fetched live from OpenAlex

Using qualitative data, this article critically explores social processes of human relationship-building in dog parks and their implications for enhancement of community (or lack thereof). Doing so contributes to the leisure literature by expanding understanding of the roles dogs can play in facilitating social capital among people. Similar to online gaming communities where users experience shared virtual space through an avatar, findings from this study suggest owners navigate parks through their pet. How dogs behave toward other dogs and toward people influence their owners’ social networks and access to resources. Positive interactions provide opportunities for relationships and communities of interest to form, where sources of support, information sharing, collective action, and conformity can be mobilized. Negative perceptions of dogs, however, often extend towards owners, thereby leading to tension, judgment, and sometimes even exclusion from social networks or public space altogether. Recommendations are offered for policy and future research.

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)0.001
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 score0.646
Threshold uncertainty score0.374

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.033
GPT teacher head0.349
Teacher spread0.316 · 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