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Record W7084233188

Implementing Equal Access to Legal Capacity in Canada: Experience, Evidence, and Legal Imperative – Final Report

2022· article· en· W7084233188 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant and Fungal Interactions Research
Canadian institutionsnot available
Fundersnot available
KeywordsConvention on the Rights of Persons with DisabilitiesPsychosocialLegal researchConventionHuman rightsCapacity buildingSelection (genetic algorithm)Disabled people
DOInot available

Abstract

fetched live from OpenAlex

Many Canadians with disabilities have long been discriminated against in the enjoyment and exercise of their legal capacity, especially people with developmental, cognitive, or psychosocial disabilities. The United Nations (UN) Convention on the Rights of Persons with Disabilities (CRPD) seeks to correct this pervasive discrimination. It recognizes the right to equality in the exercise of legal capacity without discrimination based on disability. This study was motivated by two primary issues: 1) longstanding concerns in the disability rights community about this discrimination; and 2) the findings and recommendations made by the United Nations “Committee on the Rights of Persons with Disabilities,” (UN Committee) which is the independent body of experts monitoring implementation of the Convention. In its April 2017 concluding observations to Canada’s first report on its progress in implementing the CRPD, the Committee found that Canada should take “leadership in collaborating with provinces and territories to create a consistent framework for recognizing legal capacity and to enable access to the support needed to exercise legal capacity.” There is an immense array of law, policy, and program provisions regulating legal capacity in Canada. The research team examined a broad range of these provisions. Given the available time frame and resources for the study, the team chose a representative selection of provisions to analyze in depth. The goal was to uncover themes and commonalities upon which to base an analytic approach to reform.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.773
Threshold uncertainty score0.543

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.067
GPT teacher head0.340
Teacher spread0.273 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2022
Admission routes1
Has abstractyes

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