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Record W3101434605 · doi:10.17645/up.v5i4.3430

A Shared Everyday Ethic of Public Sociability: Outdoor Public Ice Rinks as Spaces for Encounter

2020· article· en· W3101434605 on OpenAlexaffabout
Mervyn Horgan, Saara Liinamaa, Amanda Dakin, Sofia Meligrana, Meng Xu

Bibliographic record

VenueUrban Planning · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPublic spaceEveryday lifeSociologyEthosAestheticsSpace (punctuation)Social psychologyEpistemologyPsychologyPolitical scienceArtComputer scienceLaw

Abstract

fetched live from OpenAlex

Everyday life in urban public space means living amongst people unknown to one another. As part of the broader convivial turn within the study of everyday urban life (Wise & Noble, 2016), this article examines outdoor public ice rinks as spaces for encounter between strangers. With data drawn from 100 hours of naturalistic and participant observation at free and accessible outdoor public non-hockey ice rinks in two Canadian cities, we show how ‘rink life’ is animated by a shared everyday ethic of public sociability, with strangers regularly engaging in fleeting moments of sociable interaction. At first glance, researching the outdoor public ice rink may seem frivolous, but in treating it seriously as a public space we find it to be threaded through with an ethos of interactional equality, reciprocal respect, and mutual support. We argue that the shared everyday ethic of public sociability that characterizes the rinks that we observed is a function of the (1) public and (2) personal materiality required for skating; (3) the emergence of on ice norms; (4) generalized trust amongst users; (5) ambiguities of socio-spatial differentiation by skill; and (6) flattened social hierarchies, or what we call the quotidian carnivalesque. Our data and analysis suggest that by drawing together different generations and levels of ability, this distinct public space facilitates social interactions between strangers, and so provides insights relevant to planners, policy makers and practitioners.

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)0.003
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 score0.074
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.017
Scholarly communication0.0050.004
Open science0.0010.005
Research integrity0.0010.001
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 head0.122
GPT teacher head0.362
Teacher spread0.240 · 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

Citations23
Published2020
Admission routes2
Has abstractyes

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