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Record W4393317393 · doi:10.1080/14794713.2024.2329829

Eye-tracking digital music creation and performance: disability and ableism

2024· article· en· W4393317393 on OpenAlex
Christian Riegel, Katherine M. Robinson, Tait Larsen, Patrick Larsen

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal of Performance Arts and Digital Media · 2024
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsCampion CollegeUniversity of Regina
FundersCanada Foundation for Innovation
KeywordsAbleismTracking (education)AestheticsComputer sciencePsychologySociologyArtPedagogyGender studies

Abstract

fetched live from OpenAlex

This paper focuses on the developmental process of eye trackers as accessible digital musical instruments (ADMIs) by outlining collaborative research that develops digital art and music creation and performance tools. These tools require eye movements only and are of interest to individuals with all types of mobility and particularly provide music-making options to users with limited mobility. Research grade and gaming eye-tracking technology is adapted with custom software to enable music creation and performance using eye movements only. The relationship of ableism to disability and the role of digital technology to counter the negative social forces of ableism are considered. Because eye-tracking art and music creation tools are rare outside research lab contexts, all users with the ability to move one eye – regardless of other physical ability – have pre-existing capability, which makes this work especially exciting in a disability context.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.847
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.005
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.032
GPT teacher head0.299
Teacher spread0.267 · 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