Toward a Best Practices Model for Web Accessibility in E-Government Portals
Bibliographic record
Abstract
E-government portals are crucial for public service delivery, yet ensuring their accessibility for all citizens, including individuals with disabilities, remains a pressing challenge. This study addresses this issue by proposing an accessibility-based E-Government Portals Best Practices Model (E-GPBPM). The research begins by establishing a comparative analysis of the three most cited accessibility guidelines in the literature: WCAG, Section 508, and E-MAG. As WCAG 2.0 is the most established and comprehensive standard, it was selected for further analysis. Subsequently, a mapping study was conducted to investigate the extent to which the existing E-GPBPM covers the WCAG 2.0 accessibility guideline. This involved a detailed mapping of the model's best practices against the WCAG 2.0 success criteria. The results show that the WCAG criteria comprehensively align with the E-GPBPM's specific goals and practices within the web content category. Finally, an accessibility-based version of the EGPBPM is proposed to foster inclusive access to digital public services.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".