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Record W4401375746 · doi:10.3828/jlcds.2024.15

Getting to the <i>Fun Home</i> : A Blind Autoethnography of Graphic Narrative and a Call for Co-Reading

2024· article· en· W4401375746 on OpenAlexaff
Denise Springett

Bibliographic record

VenueJournal of Literary & Cultural Disability Studies · 2024
Typearticle
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsAutoethnographyNarrativeReading (process)Visual artsArtPsychologyMedia studiesAestheticsPsychoanalysisSociologyLiteratureLinguisticsGender studiesPhilosophy

Abstract

fetched live from OpenAlex

The article shares a personal history of a blind reader encountering graphic novels at different times in life. Following a brief review of the low-vision accessible comics and adaptation strategies currently available, it offers a critique of the emphasis placed on high-tech adaptation strategies for idealizing “independent” reading practices. In response to the potentially ableist pitfalls of high-tech adaptation, the article offers “co-reading” as an anti-ableist reading practice which enables access to comics for blind and visually impaired readers while encouraging sighted readers to interrogate ableist assumptions about dis/ability. With reflections on Alison Bechdel’s Fun Home , the author considers why blind readers might be interested in reading a conventionally visual medium; why the privileging of independent reading works to limit accessibility of comics to blind and low vision readers; and last but not least, how the practice of collaborative comics reading—co-reading—offers opportunities to engage in anti-ableist praxis of reading comics.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.149
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.118
GPT teacher head0.475
Teacher spread0.357 · 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.

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

Citations1
Published2024
Admission routes1
Has abstractyes

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