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Record W3177122581 · doi:10.1145/3450741.3465266

Stories Incarnate

2021· article· en· W3177122581 on OpenAlexafffund
Marisa Samek, Tudor Tibu, Richard Lachman, Ali Mazalek

Bibliographic record

VenueCreativity and Cognition · 2021
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsToronto Metropolitan University
FundersOntario Ministry of Research and InnovationCanada Foundation for Innovation
KeywordsComputer science

Abstract

fetched live from OpenAlex

Providing embodied, interactive experiences for live audiences in traditional performance venues remains an ongoing challenge in the live entertainment industry. This paper presents a proof-of-concept performance piece which engages a seated audience in an embodied, interactive storytelling experience during a live circus show. We used a research-through-design methodology, with the goal of creating a piece in which the audience's actions and the way they collaborate determine the outcome of the performance. We describe our design process and informal evaluation of the piece. We conclude with considerations for designing embodied, interactive storytelling experiences for live audiences that provide a sense of agency and communion, as well as reflections on research through design for live performance.

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)0.005
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 score0.076
Threshold uncertainty score0.253

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0060.006
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0760.016

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 head0.036
GPT teacher head0.297
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
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
Published2021
Admission routes2
Has abstractyes

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