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Record W4405354328 · doi:10.54097/jvfk9468

Disability Rights Legislation Comparison: China and Canada

2024· article· en· W4405354328 on OpenAlexaboutno aff
Yisa Liu

Bibliographic record

VenueJournal of Education Humanities and Social Sciences · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationChinaEnforcementFace (sociological concept)Inclusion (mineral)Government (linguistics)Political sciencePublic administrationHuman rightsLaw and economicsBusinessLawEconomic growthSociologyEconomicsSocial science

Abstract

fetched live from OpenAlex

This paper makes a comprehensive comparative study of disability rights legislation in China and Canada. The report carefully examines the differences between the two countries in terms of the definition of disability, the legal basis for protection, and existing legislation. Through in-depth case studies, it reveals the challenges encountered in the realization of the rights of persons with disabilities. Then, it puts forward the corresponding solutions. A comparison shows that while China has made great progress in this area, Canada's system appears to be more mature and more centered on disability rights. However, both countries face challenges that require the joint efforts of the government, society and the people. This paper aims to provide valuable insights and feasible suggestions for strengthening the legal protection and realization of the rights of persons with disabilities in both countries. It stressed the importance of a comprehensive legal framework, strong law enforcement, public awareness and equal opportunities to ensure the full inclusion of persons with disabilities in society and guarantee their equal rights.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.673
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.054
GPT teacher head0.359
Teacher spread0.305 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations0
Published2024
Admission routes1
Has abstractyes

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