Bridging the Digital Divide: A Comparative Policy Framework for Web Accessibility in Peru and Reference Nations
Bibliographic record
Abstract
This paper presents a comparative analysis of web accessibility policies, focusing on Peru and reference cases from Canada, Australia, and Uruguay. Using a qualitative methodology that combines expert interviews, documentary analysis, and technological surveillance, the study identifies normative, institutional, and cultural barriers that hinder digital accessibility in Peru. While Peru still relies on outdated guidelines based on WCAG 1.0 without enforcement, the benchmark countries show advanced governance models aligned with WCAG 2.1 and 2.2. The findings highlight the need for updated standards, centralized monitoring, and inclusive design strategies adapted to intercultural and rural contexts. Based on international best practices, the paper proposes a policy framework for bridging the digital divide in Peru through regulatory reform, oversight, and progressive incentives, contributing to the regional debate on inclusive digital transformation and laying the foundations for future research.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".