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Record W2903089316 · doi:10.5539/ies.v11n12p140

Evaluation of Web Accessibility of Higher Education Institutions in Chile

2018· article· en· W2903089316 on OpenAlexvenueno aff
Rocío Fernández Piqueras, José Francisco Cervera Mérida

Bibliographic record

VenueInternational Education Studies · 2018
Typearticle
Languageen
FieldComputer Science
TopicE-Learning and Knowledge Management
Canadian institutionsnot available
Fundersnot available
KeywordsWeb accessibilityLegislationInclusion (mineral)Web Accessibility InitiativeWorld Wide WebWeb standardsThe InternetPolitical scienceUniversal designHigher educationPublic relationsBusinessComputer scienceInternet privacySociologyWeb developmentWeb intelligenceSocial scienceLaw

Abstract

fetched live from OpenAlex

The aim of this study is to assess the web accessibility concerning the websites of Chilean universities which are listed in The World University Rankings. Web accessibility is a fundamental factor in achieving a true educational inclusion. It is especially important in the light of the current trend of expanding not only the online content, but also online learning. What makes this even more essential is the Chilean legislation which under Law 20422 establishes the regulations regarding equality of opportunity and social inclusion of people with disabilities. The analysis has been conducted on the basis of the international standard set by the World Wide Web Consortium (W3C), version WCAG 2.0. Evaluation methodology called WCAG-EM created by the same entity, has been applied in the analysis. Various automatic web accessibility evaluation tools have also been used, apart from manual verifications. The study reveals that the websites of Chilean universities have hardly complied with the regulation and that there are barriers and difficulties of access for the elderly and/or people with disabilities.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.174
GPT teacher head0.481
Teacher spread0.307 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2018
Admission routes1
Has abstractyes

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