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Toward a Best Practices Model for Web Accessibility in E-Government Portals

2025· article· W4417169834 on OpenAlex
Mohammed Rida Ouaziz, Laila Cheikhi, Alain Abran

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Language
FieldSocial Sciences
TopicDigital Accessibility for Disabilities
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsWeb accessibilityBest practiceWeb Accessibility InitiativeService (business)Web standardsKey (lock)Web application

Abstract

fetched live from OpenAlex

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.

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)0.005
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.503
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0020.006
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.145
GPT teacher head0.426
Teacher spread0.281 · 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

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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