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Record W4293056336 · doi:10.3138/ctr.191.018

Across Cyberspace and Time Zones: How <i>Ways of Being</i> Explores Performances of Self in Material and Digital Spaces

2022· article· en· W4293056336 on OpenAlexvenueaboutno aff
Stephanie Fung, Jeff McGilton

Bibliographic record

VenueCanadian Theatre Review · 2022
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsnot available
Fundersnot available
KeywordsLivenessCyberspaceSociologyAttendanceCitizen journalismAestheticsImplementationMedia studiesFeelingAnonymityVisual artsComputer scienceArtThe InternetComputer securityPsychologyWorld Wide WebPolitical scienceSocial psychologyLaw

Abstract

fetched live from OpenAlex

After watching the same show over the course of three separate performances, Stephanie Fung and Jeff McGilton come to their own conclusions about Ways of Being, the final instalment in the Kingston-based Kick and Push Festival 2021. Presented live by Toronto-based Clayton Lee and Kraków-based Michael Rubenfeld, the performance was an investigation of connectivity across geographical space and time zones, using a participatory structure to subtly investigate our ways of being. The participatory nature of the piece informed its undeniable feeling of liveness, changing and developing with whoever was in attendance. Fung and McGilton consider how this work-in-progress invokes an understanding of presence, performances of self, and (re)connection through creative implementations of emerging technologies.

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)0.004
metaresearch head score (Gemma)0.004
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 score0.165
Threshold uncertainty score0.327

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0140.046
Scholarly communication0.0200.008
Open science0.0020.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.015
GPT teacher head0.232
Teacher spread0.217 · 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
Published2022
Admission routes2
Has abstractyes

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