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Record W3041115891 · doi:10.1007/s10803-020-04603-3

Employment, Education, and Income for Canadians with Developmental Disability: Analysis from the 2017 Canadian Survey on Disability

2020· article· en· W3041115891 on OpenAlexafffundabout
Patrick Berrigan, Craig William Michael Scott, Jennifer Zwicker

Bibliographic record

VenueJournal of Autism and Developmental Disorders · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsUniversity of Calgary
FundersSinneave Family FoundationUniversity of Calgary
KeywordsPsychologyAutismPublic healthSpecial educationDevelopmental psychologyGerontologyMedicinePedagogy

Abstract

fetched live from OpenAlex

This study assessed needs and outcomes for people with developmental disability (DD) to understand the socioeconomic status of this group prior to implementation of the Accessible Canada Act in June 2019. The 2017 Canadian Survey on Disability (CSD) was used to analyze data for a sample of individuals with self-reported disability. Data related to employment, education, income, housing, caregivers, and use of government benefits is reported. Compared to the general Canadian public, persons with DD are less likely to: finish high-school or post-secondary education; participate in the labor force or be employed; and earn on average less/year in total income. To align with recent accessibility legislation, significant progress is needed to address disparities for people with DD.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.336
Threshold uncertainty score0.633

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 studies0.0010.001
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 head0.030
GPT teacher head0.298
Teacher spread0.268 · 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 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

Citations27
Published2020
Admission routes3
Has abstractyes

Explore more

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