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Record W2898826750 · doi:10.3138/ctr.176.016

Nocturnal Rhythms and Collective Practices

2018· article· en· W2898826750 on OpenAlexvenueaboutno aff
Eleonora Diamanti

Bibliographic record

VenueCanadian Theatre Review · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicNight-time city culture
Canadian institutionsnot available
Fundersnot available
KeywordsTemporalitySociologyRhythmPerceptionUrban theoryAestheticsVisual artsPsychologyArtEcologyEpistemology

Abstract

fetched live from OpenAlex

Choreographies of assembly are grounded in the relationship between urban design and collective, bodily modes of reproducing, inhabiting, and reimagining urban space. Through a case study of urban regeneration, culture-led development, and social movements in Montreal, this article examines the particular nocturnal spatio-temporal rhythms of gathering in public space. For a long time, the night was left in the shadows by urban development experts who focus their attention on daytime plans and activities. However, following the rise of nighttime economies, sleepless societies, and ‘24/7’ cities, the night has received increasing attention since the 1990s (Crary; Gwiazdzinski and Straw). Critical engagements with the night as an object of study have shed light upon temporality, rhythms, and links between space and time. Such perspectives rethink urban life in terms of rhythm. Drawing from Henri Lefebvre’s theory of “rhythmanalysis,” this article focuses on the aesthetic, bodily, and sensorial experiences of collective practices. This article takes up Lefebvre’s notion of polyrhythmia—the idea that the living body is an association of a multiplicity of rhythms—to study the polyrhythmic qualities of collective and bodily practices in urban space at night. This night-focused study draws out the complex relations between collectivity, movements, and urban design. Moreover, a rhythmic study of the city at night foregrounds the multimodal perception process, following James Gibson’s theory of ecological perception. Hence, this article asks: how does the night affect our collective experience of the city?

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)0.002
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 score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.016
Scholarly communication0.0040.003
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.036
GPT teacher head0.337
Teacher spread0.301 · 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

Citations3
Published2018
Admission routes2
Has abstractyes

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