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Record W4248816009 · doi:10.5206/tba.v1i1.7941

Speciation Dance

2020· article· en· W4248816009 on OpenAlexvenueno aff
Michelle Margaret Wilson

Bibliographic record

Venuetba Journal of Art Media and Visual Culture · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsnot available
Fundersnot available
KeywordsDanceAestheticsSociologyAnthropocentrismEnvironmental ethicsVisual artsArtPhilosophy

Abstract

fetched live from OpenAlex

tba Submission Video Link https://vimeo.com/188828000 Artist Statement As an artist I approach my practice as a conduit for imagining alternate political and personal realities in which the non-human animals are afforded relational and differentiated rights of membership in a multispecies community. The intention of such work is to stir the moral imagination of my viewer. By not simply raising indignation at abuse and neglect, not presenting (yet again) an image of the animal other as a passive victim, my purpose is to envision the animals we are entangled with as neighbours, friends and members of disparate communities. Speciation Dance is a new media installation work that challenges established relationships between human and nonhuman animals. It represents a progression in my attempts to abandon the presumptive act of speaking for the animal other. Rather, this work joins animal and human voices in hopes of decentering the anthropocentrism inherent in art making. Project Description: Speciation Dance A small but strategic desire exists within humanity to preserve certain charismatic animal species from extinction; this has led to a dance both epic and intimate, which paradoxically attempts to maintain natural wildness by crafting an elaborate system of interspecies dependency. This contradiction is most visible in the conservation of whooping cranes. This species has come to emblemize the extreme commitment humans have made to the management of creatures we ourselves have driven to near nonexistence. In the performative video work, Speciation Dance, I focus on slippages in identity for both human-surrogate-mates and animals in captive breeding programs. In these relationships scientists and conservation workers don cobbled together costumes and assume monastic vows of silence to prevent their charges from becoming too accustomed to humans. But perhaps more importantly, these orniphiles (bird lovers) encourage the crane to imprint upon their bird persona. When a creature imprints upon an individual outside of their species it disrupts speciation, the inbred impulse to be attracted only to one's own kind. Imprinting on a human distorts animal identity; seeing itself as human an animal will have no desire to copulate with its own species. As the performers in Speciation Dance transform into bird/people we hear ornithologist George Archibald describing his cross-species relationship with a crane named Tex. George and Tex’s story inspired this piece, and George’s narrative, assembled from found audio recordings, gives humor and context to the work. In this 6-minute two-channel video work, I am documenting two professional dancers from the Nova Dance Collective as they flirt with becoming-animal. Stepping into the role of a liminal being, neither human nor bird, they perform as humans-come-whooping cranes. Dipping, leaping, strutting and extending prosthetic heads to the sky, they attempt to relate to each other through the embodied language of both species. Trying to court and arouse one another, the performers convey the beautiful absurdity of such a futile act.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.741
Threshold uncertainty score0.369

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0070.003
Open science0.0020.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.7410.456

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 head0.034
GPT teacher head0.349
Teacher spread0.315 · 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.

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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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