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Record W4253095926 · doi:10.32920/ryerson.14647053

Seeing fashion through sound

2021· preprint· en· W4253095926 on OpenAlexaffabout
Jenni Lin Armstrong

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsExhibitionVisitor patternSound (geography)ClothingVisual artsArtifact (error)Wearable computerCompromiseMultimediaComputer scienceArtSociologyHistoryAcousticsArtificial intelligence

Abstract

fetched live from OpenAlex

The 2005 Accessibility for Ontarians with Disabilities Act (AODA) has legislated museums to amend tangible and intangible barriers within their curatorial practices by 2025. In this study, a Métis researcher-practitioner explored artistic ways that museums might curate direct and accessible experiences with artefacts through wearable technology. Utilizing a practice-led creative process, non-traditional aboriginal regalia was developed and displayed in a multimedia installation. The artifact was inspired by the Ojibwe Jingle Dress and dance, which empower and heal through sound. To augment the exhibition experience, a wearable audio system enhances sound from the Jingle Dress and touchless elements, such as electromagnetically induced sound, created an environment where visitor interaction would not compromise artefact preservation. A sound experience was only accessible if a visitor learned how to respectfully interact with the artefact. Both artefact and installation serve as recommendations for museums to effectuate inclusive exhibition experiences and address AODA requirements.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.006
Scholarly communication0.0070.004
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.003

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 head0.094
GPT teacher head0.265
Teacher spread0.171 · 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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