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Record W3034403951 · doi:10.11575/prism/37311

A profile of students with special needs who transitioned between Government of Alberta disability programs

2019· article· en· W3034403951 on OpenAlexaboutno aff
Ruiting Jia, Hitesh Bhatt, Xinjie Cui

Bibliographic record

VenueOpen MIND · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)BusinessPublic relationsMedical educationPolitical sciencePublic administrationMedicine

Abstract

fetched live from OpenAlex

The child to adult transition can be especially challenging for youth with disabilities. This report examined special needs service use patterns of Albertans with disabilities (15 to 23 years old) when they transitioned from child to adult disability supports during 2005/06 to 2010/11. Analyses focused on transition pathways between two support programs for youth with disability in Alberta: child disability supports (the Family Support for Children with Disabilities program) and adult disability supports (the Persons with Developmental Disabilities program). This report found that 6% of Albertan students with special needs received child disability services at some point between 2005/06 and 2008/09, 55% of whom (the majority of which had multiple disabilities) later transitioned to adult disability services at some point between 2005/06 and 2010/11. In contrast, 3% of non-child disability support students transitioned to adult disability supports in the same period. This report also found that special needs students with different transition patterns had different service use patterns. These findings provide policy-relevant evidence that service providers can use to improve transitions for youth with disabilities.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.438
Threshold uncertainty score0.882

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.041
GPT teacher head0.352
Teacher spread0.312 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2019
Admission routes1
Has abstractyes

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Same venueOpen MINDSame topicDisability Education and EmploymentFrench-language works237,207