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Implementing UN CRDP Through Human Interface Equivalencies (HIEs) With Semantic Interoperability

2022· book-chapter· en· W4281926114 on OpenAlex

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

VenueAdvances in educational technologies and instructional design book series · 2022
Typebook-chapter
Languageen
FieldComputer Science
TopicText Readability and Simplification
Canadian institutionsEnGlobe (Canada)
Fundersnot available
KeywordsInteroperabilitySemantic interoperabilityComputer scienceInterface (matter)Context (archaeology)Software engineeringKnowledge managementWorld Wide WebGeography

Abstract

fetched live from OpenAlex

The introduction of the UN CRDP provided the first common international basis of legal and regulatory requirements for individual accessibility as a human right. The international ISO/IEC standard committee in the field of e-learning (i.e., ISO/IEC JTC1/SC36) responded by developing an international standard ISO/IEC 20016-1 to address semantic interoperability requirements of language accessibility, in the form of human interface equivalents (HIEs). The authors identify and summarize key aspects of this ISO/IEC 20016-1 standard including fundamental principles governing individual accessibility requirements, based on the UN CRDP doing so in an ITLET and commitment exchange context. The concept of semantic interoperability (in an ITLET context) is defined and supports the same through the constructs of level and degrees of semantic equivalency. It is based on best practices of translation theory, applied linguistics, and existing applicable international standards, which already address various aspects of language accessibility requirements in a generic manner.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.365
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.004
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.280
Teacher spread0.254 · 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