WCAG 2.0 Semi-automatic Accessibility Evaluation System: Design and Implementation
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.
Bibliographic record
Abstract
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.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.032 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it