MétaCan
Menu
← Back to cohort
Record W4404022241 · doi:10.7202/1113946ar

Audio described comics in the museum

2024· article· en· W4404022241 on OpenAlexvenueno aff
Dimitris Asimakoulas

Bibliographic record

VenueMeta Journal des traducteurs · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicComics and Graphic Narratives
Canadian institutionsnot available
Fundersnot available
KeywordsComicsArtAudio visualVisual artsComputer graphics (images)MultimediaComputer scienceLiterature

Abstract

fetched live from OpenAlex

Audio Description is typically used to describe the visual aspects of various cultural products in the creative industries: performed plays, films, sports matches, art gallery and museum items. Such descriptions offer alternative sensory input for blind or partially sighted audiences and have been the staple of research in Audiovisual Translation Studies. There are, however, rather few studies focusing on museum environments and none that examine the niche area of comic art. This article addresses such a gap in two ways. First, it explores comics from an audiovisual translation/accessibility perspective. Second, it reports findings from a pilot study of accessible comic art where the views of selected professionals (curator, comic artists, audio describer) were collected, descriptions for three comics were commissioned and the responses of blind visitors to a comic art museum were gauged. The audio described comics—not without their limitations, as will be shown—are the result of a contingent collaboration of actors in the space of the museum.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.008
Scholarly communication0.0050.003
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.080
GPT teacher head0.260
Teacher spread0.181 · 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 designQualitative
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueMeta Journal des traducteurs→Same topicComics and Graphic Narratives→French-language works237,207→