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Record W7006425922

Translating Scientific Content into Accessible Formats with Visually Impaired Learners:
\nRecommendations and a Decision Aid Based on Haptic Rules of Perception

2020· other· en· W7006425922 on OpenAlexfundno aff

Bibliographic record

VenueOCAD University Open Research Repository (OCAD University) · 2020
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaInternational Development Research Centre
KeywordsHaptic technologyPerceptionDomain (mathematical analysis)GraphicsFocus (optics)Visual perceptionHaptic perceptionVisually impaired
DOInot available

Abstract

fetched live from OpenAlex

Students with visual impairments (VI) miss out on science because of inaccessible visual graphics (such as pictures and diagrams) of the phenomena that are the focus of curricula. My project examines how efforts to translate these into non-visual representations, such as raised line graphics, tend to be less effective than expected because they are perceived using “rules” of haptic perception by VI learners but developed using “rules”' of visual perception by sighted designers. In response, I introduce my recommendations, in the form of a decision aid, informed by a series of interlinked concatenated studies consisting of user testing, workshops, and co-design sessions composed of multi-disciplinary teams that included VI educators, learners, inclusive designers, musicians, and domain experts from engineering and the cognitive neuroscience.

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), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.784
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.003
Science and technology studies0.0020.002
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
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 head0.100
GPT teacher head0.329
Teacher spread0.229 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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