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Record W2144782162 · doi:10.1177/1044207309344562

Analyzing the Impact of Disability Legislation in Canada and the United States

2009· article· en· W2144782162 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Disability Policy Studies · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLegislationBest practicePolitical scienceState (computer science)Public administrationEconomic growthBusinessLawEconomics

Abstract

fetched live from OpenAlex

Experiences with disability legislation are different between Canada and the United States, but both countries have experiences to share regarding trends and best practices, as well as challenges addressing the accessibility of public facilities, housing, and transportation for persons with disabilities. Based on this distinction, a literature review was conducted focusing on the similarities and differences between Canadian and American disability legislation, primarily for trends and best practices that have resulted in positive outcomes for people with disabilities. Three times as much literature exists on U.S. experiences based on disabilities legislation over the past two decades. One major reason is that the United States has federal legislation specific to disabilities (dating back to 1990) and Canada has none. The impact of federal legislation is seen across each American state. Without federal legislation in Canada, the provinces are left to implement their own, often different, practices. This country comparison includes gaps in practices and considerations for improvements.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.035
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.040
GPT teacher head0.389
Teacher spread0.349 · 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