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Record W2018041977 · doi:10.1017/s0266464x10000278

Site-Specific Dance in a Corporate Landscape

2010· article· en· W2018041977 on OpenAlexaboutno aff
Melanie Kloetzel

Bibliographic record

VenueNew Theatre Quarterly · 2010
Typearticle
Languageen
FieldPsychology
TopicDiversity and Impact of Dance
Canadian institutionsnot available
Fundersnot available
KeywordsDanceSpace (punctuation)Perspective (graphical)Visual artsWork (physics)SociologyAestheticsArtEngineeringComputer science

Abstract

fetched live from OpenAlex

Site-specific performance relies on the terms space and place as markers for discussing a performance's engagement with a site. However, practitioners and researchers are often disgruntled by the limitations such terms impose upon site-specific performance – as was Melanie Kloetzel, in the creation of The Sanitastics, a site-specific dance film created in the Calgary Walkway System. In this article, Kloetzel examines how theorists have struggled with space and place in the last four decades and how bringing in the perspective of the body allows us to reassess our assumptions about these terms. As she analyzes her creative process, she discovers the restrictions as well as possibilities in space and place, but she also notes the need for Marc Augé's idea of non-place to clarify her site-specific efforts in the homogenized, corporate landscape of the Walkway System. Kloetzel is an associate professor at the University of Calgary and the artistic director of kloetzel&co, a dance company founded in New York City in 1997 that has presented work across North America. Her site-specific films have been shown in Brazil, Belgium, Canada, and the United States, and her anthology with Carolyn Pavlik, Site Dance: Choreographers and the Lure of Alternative Spaces, was published by the University Press of Florida in 2009.

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 score0.010
Threshold uncertainty score0.028

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 studies0.0080.019
Scholarly communication0.0100.004
Open science0.0010.009
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.023
GPT teacher head0.256
Teacher spread0.233 · 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

Citations8
Published2010
Admission routes1
Has abstractyes

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