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Record W2418867335 · doi:10.1080/01490400.2016.1165638

Leisure Spaces, Community, and Third Places

2016· article· en· W2418867335 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 · 2016
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsVancouver Island UniversityConcordia University
Fundersnot available
KeywordsConceptualizationSociologyDiversity (politics)Field (mathematics)Isolation (microbiology)Public relationsSocial psychologyEpistemologyPsychologyPolitical scienceComputer science

Abstract

fetched live from OpenAlex

After decades of highlighting the decline of social networks, leisure spaces as third places constitute a welcomed approach to mediate this loss. Third places are defined as public gathering places that ultimately contribute to the strength of community. We appreciate the concept and believe that it has and will continue to influence scholars in the field of leisure. For this reason, this research reflection argues Oldenburg's conceptualization of third places requires reconsideration. Specifically, we address the increasing prevalence of technology and question Oldenburg's claim that technology contributes to the isolation of individuals. We also encourage a more complex understanding of third places—one that is beyond the idealized notion of public places. Oldenburg's social dimensions of third places (enjoyment, regularity, pure sociability/social leveler, and diversity) are offered as a useful framework. More specifically, we argue that diversity is the most relevant characteristic when exploring third places as a platform for community.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.679

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.049
GPT teacher head0.334
Teacher spread0.285 · 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