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Record W4417286752 · doi:10.4324/9781003504283-20

Architectural Rehearsal

2025· book-chapter· en· W4417286752 on OpenAlexaboutno aff
Aurélie Dupuis

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldPsychology
TopicDiversity and Impact of Dance
Canadian institutionsnot available
Fundersnot available
KeywordsEmbodied cognitionDanceChoreographyGestureProcess (computing)Architecture

Abstract

fetched live from OpenAlex

In the Western tradition, architectural precedents remain limited to buildings. Consequently, the plurality of ways of making worlds is rendered silent. Reckoning with embodied knowledge as an architectural precedent, this chapter reexamines the operations that architectural knowledge production legitimizes. Drawing on Israeli-born artist, curator, and historian Ariella Aïsha Azoulay, this chapter addresses this critical process as an ‘architectural rehearsal’ that involves thinking with bodies, practices, and forms of knowledge that affirm a plurality of spatialities and worlds. It outlines these embodied practices and gestures as what Spanish architect and scholar Lucía Jalón Oyarzun calls “minor architectures,” or uncommon precedents for contemporary architecture. Dance and choreography can contribute to the affirmation and transmission of “minor gesture[s],” as conceptualized by Canadian philosopher Erin Manning, to address situations in which bodies, histories, grounds, and architectures maintain depleted relationships that reproduce violence and deny possibilities. The case of the Judson Dance Theater and contemporary practices that refer to it are discussed from this perspective. This chapter reveals that an inquiry into dance practices and the minor embodied knowledge they engage can be a veritable methodology for researching embodied architectural knowledge and histories and mobilizing them as uncommon precedents.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.063
Threshold uncertainty score0.211

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.006
Scholarly communication0.0040.003
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0630.012

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 head0.024
GPT teacher head0.285
Teacher spread0.261 · 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
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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