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Record W6948955152 · doi:10.5281/zenodo.12697513

SHAPEREADER: A Forward Answer To a Lack of Inclusivity Regarding Visual Disabilities in Comics (and Visual Narratives).

2019· other· en· W6948955152 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Repository and Bibliography (University of Liège) · 2019
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsComicsNarrativeRepertoireExpression (computer science)Multidisciplinary approachAudience responseCenter (category theory)Metis

Abstract

fetched live from OpenAlex

Daniel Jiménez Quiroz (MAAAP '20) is organizing with the support of the Wellness Center at SAIC: SHAPEREADER: A Forward Answer To a Lack of Inclusivity Regarding Visual Disabilities in Comics (and Visual Narratives). The workshop will happen this Tuesday, April 2nd in Sharp 327 between 10 and 12. RSVP to djimen1@saic.edu to save a spot for this event. This is a unique occasion for visually impaired and sighted participants to meet and talk side by side about tactile narratives based on an ad-hoc language. The goal of the workshop is not merely to reflect the community’s expression by a collectively-built story, but to provide the very same genetic material for textual production: a repertoire of empty symbols that can be reiteratively attributed different meanings and functions according to each community’s specific needs, preoccupations and issues. The activity will be conducted by Ilan Manouach (Athens, 1980), a multidisciplinary artist with a specific interest in conceptual comics. https://ilanmanouach.com/ He is currently a Ph.D. researcher at the Aalto University in Helsinki. Manouach is recognized for his contributions to the dialogue of the "reader’s space” and the fluid archives, "beyond all imposed meanings coming from the author or the prevailing readings of certain works." He is a usual contributor to Monoskop and UbuWeb. https://www.facebook.com/100057442870227/posts/2051939518237303/

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Bibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.285
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0190.009
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.002
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 head0.027
GPT teacher head0.297
Teacher spread0.269 · 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 teacher head, not a consensus.

Study designObservational
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
Published2019
Admission routes1
Has abstractyes

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