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Record W2113256746 · doi:10.5539/cis.v5n6p73

WCAG 2.0 Semi-automatic Accessibility Evaluation System: Design and Implementation

2012· article· en· W2113256746 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueComputer and Information Science · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Accessibility for Disabilities
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceWeb accessibilityArabicWork (physics)World Wide WebEvaluation methodsSystems designHuman–computer interactionMultimediaWeb standardsSoftware engineeringWeb service

Abstract

fetched live from OpenAlex

The current state of web accessibility evaluation systems is encouraging, yet not sufficient. Many evaluation systems were developed for evaluating websites based on WCAG 2.0 recommendations, however, their effectiveness is somewhat incomplete. Specifically, web accessibility evaluation systems, not being able to handle a website language poses a series of challenges for web accessibility evaluation. This paper details the design and implementation of Level A WCAG 2.0 semi-automatic accessibility evaluation system capable of processing Arabic websites. The system builds on previous work in this area and overcomes the problem encountered while dealing with Arabic websites. Our system evaluation shows that, in fact, there are considerable differences between our system and other accessibility evaluation systems, in terms of having distinct evaluation results.

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.

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)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.789
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.032
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 head0.051
GPT teacher head0.381
Teacher spread0.330 · 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