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Record W2902407696 · doi:10.1080/16078055.2018.1550438

The transformative (and potentially discriminatory) possibilities of animating public space

2018· article· en· W2902407696 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

VenueWorld Leisure Journal · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTransformative learningPublic spacePlacemakingSpace (punctuation)SociologyGlobePublic relationsPower (physics)WarrantAnimationAestheticsMedia studiesPolitical scienceVisual artsArchitectureComputer sciencePsychologyUrban designArchitectural engineeringBusinessEngineeringArt

Abstract

fetched live from OpenAlex

Despite their proliferation across the globe, efforts to animate public space remain largely unexamined in the leisure literature. Animating public space refers to “the deliberate, usually temporary, employment of festivals, events, programmed activities, or pop-up leisure to transform, enliven, and/or alter public spaces and stage urban life.” This article examines the practice of animating public space as a form of transformative placemaking that enables urban inhabitants to assert their “right to the city”, while considering how such practices reproduce power relations to create (unintentionally or intentionally) discriminatory outcomes. In so doing, the article explores the complex nature of animation efforts and tensions that exist in animated public spaces that, on the surface, appear inclusive. Its conclusions provide direction for future research on the topic by identifying questions that warrant attention.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.792
Threshold uncertainty score1.000

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 studies0.0020.001
Scholarly communication0.0000.001
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 head0.031
GPT teacher head0.314
Teacher spread0.284 · 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