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Record W2503647692 · doi:10.7202/1036456ar

L’engagement du spectateur de théâtre de rue. Revivre l’espace urbain

2016· article· fr· W2503647692 on OpenAlexvenueno aff
Catherine Aventin

Bibliographic record

VenueTangence · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtESPACE

Abstract

fetched live from OpenAlex

En tant qu’architecte, c’est par une approche pluridisciplinaire que Catherine Aventin étudie les arts de la rue, d’un point de vue spatial et sensible par le biais des ambiances architecturales et urbaines. Elle travaille entre autres sur la réception de ce type d’action artistique, où la scène peut être une rue, une place, voire une ville entière. Son article aborde la réception par les différentes composantes de l’espace public à l’oeuvre (physique, sociale et sensible) et montre quels liens peuvent se créer entre le lieu de représentation, l’événement artistique et les pratiques et représentations sociales. Elle présente aussi des stratégies développées par les spectateurs lors de représentations, ainsi que les changements de perception et de représentation des espaces après ces spectacles. Pour cela, elle s’appuie sur ses enquêtes et analyses menées en France (particulièrement à Grenoble et à Calais), principalement sur la base d’observations participantes, de spectacles de différentes échelles (intimes comme s’adressant à une ville entière) et de tous types (fixes, déambulatoires, courts ou durant plusieurs jours).

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.027
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0110.010
Scholarly communication0.0090.007
Open science0.0010.007
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0210.003

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 head0.037
GPT teacher head0.268
Teacher spread0.232 · 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 designNot applicable
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

Citations0
Published2016
Admission routes1
Has abstractyes

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