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Blind readers and blind writers

2015· other· en· W4232771998 on OpenAlexaff
Vanessa Warne

Bibliographic record

VenueThe Encyclopedia of Victorian Literature · 2015
Typeother
Languageen
FieldArts and Humanities
TopicHistorical Art and Culture Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsBlindnessReading (process)BrailleMainstreamLiteracyPopulationPsychologyVisual artsSociologyArtOptometryPedagogyPolitical scienceMedicineLawLinguistics

Abstract

fetched live from OpenAlex

The advent of books for blind readers changed, albeit gradually, both the experience of blindness and ideas about blindness. In the decades following James Gall's publication of Britain's first raised‐print book in 1827, many visually disabled Victorians gained access to instruction in finger‐reading skills and they used these skills to read, and also to create, an increasingly varied body of raised‐print material. The development of a print culture for and by blind people transformed the lived experience of visual disability: a growing segment of Britain's blind population were no longer dependent on sighted readers for access to text and institutions that served blind students extended their offerings beyond vocational skills, such as basket making, to include academic study. While the entry into literacy changed the lives of many people with visual disabilities, the proliferation of finger reading also shaped mainstream ideas about visual disability, prompting Victorians to rethink blindness and to reconsider the intellectual potential and sensory experiences of visually disabled people. Major figures in the British history of blind reading include: James Gall, John Alston, and W.H. Levy. Blind authors of note from the period include: Frances Browne, Alice King, James Holman, and W. W. Fenn.

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)0.003
metaresearch head score (Gemma)0.015
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: Other · Consensus signal: Other
Teacher disagreement score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0140.021
Scholarly communication0.0150.008
Open science0.0010.010
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0170.004

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 head0.019
GPT teacher head0.228
Teacher spread0.210 · 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
GenreOther

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
Published2015
Admission routes1
Has abstractyes

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