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Dancing in the City

2016· reference-entry· en· W2483343426 on OpenAlexaffabout
Jessica Jacobson-Konefall

Bibliographic record

Venuenot available
Typereference-entry
Languageen
FieldPsychology
TopicDiversity and Impact of Dance
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsIndigenousSociologyDanceColonialismConsciousnessIdentity (music)AnthropologySociocultural evolutionAestheticsMedia studiesVisual artsGeographyArtEcologyPsychologyArchaeology

Abstract

fetched live from OpenAlex

Terrance Houle’s screendance work, Landscape, treats Indigenous aesthetics as a site of the social in Canadian society, and explores the practice of civic consciousness in the domains of dance and new media art. This involves the social geography of Calgary as a Canadian city, the relationship of Indigenous peoples and their powwows to colonial settlers in Calgary, screendance practices, and what Mohawk scholar Taiaike Alfred calls “regeneration” of Indigenous identity. Indigenous media and dance aesthetics, meanwhile, function as practices of cultural resurgence in creative contention with the settler city—what Bernard Stiegler calls geotechnics, which produce spaces "geo-graphically," where “perception and cognition fuse with the writing (graph) of the land (geo).” Technical apparatuses—such as screendance—differentially mediate civic life to produce such sociocultural ecologies. Houle approaches decolonization across spatial and psychosocial realms in the city through creative contention, using screendance to create resurgent Indigenous ecology, and staging and transforming relations of civic consciousness in Calgary.

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)0.000
metaresearch head score (Gemma)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.333
Threshold uncertainty score0.662

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0250.009
Scholarly communication0.0120.003
Open science0.0010.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0500.005

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 head0.071
GPT teacher head0.331
Teacher spread0.260 · 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
Published2016
Admission routes2
Has abstractyes

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