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Record W2015278544 · doi:10.3109/09638288.2010.514018

Employment status and work characteristics among adolescents with disabilities

2010· article· en· W2015278544 on OpenAlexaff
Sally Lindsay

Bibliographic record

VenueDisability and Rehabilitation · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsHolland Bloorview Kids Rehabilitation Hospital
Fundersnot available
KeywordsPsychologyWork (physics)RehabilitationYoung adultAge groupsGerontologyDevelopmental psychologyMedicineDemographySociology

Abstract

fetched live from OpenAlex

PURPOSE: Little is known about the work experiences of youth as they transition to adulthood. The purpose of this study is to explore the characteristics associated with disabled youth who are employed and the types of employment they are engaged in. METHOD: Data were analysed using the 2006 Participation and Activity Limitation Survey. Youth aged 15-29 and 20-24 were selected to explore the characteristics of adolescents who are employed and where they are working (n=2534). RESULTS: Several differences in who was employed and the characteristics of their employers were noted between the two age groups. Geographic location played a more significant role for employment among youth (15-19 year olds) with mobility impairments compared to other disability types. Employed youth from both age groups had their disability a long time while few people who were recently diagnosed were working. Transportation was a significant predictor of employment for both age groups. Young adults (20-24) worked more hours per week, in different industries, and more of them were self-employed compared to the 15-19 year olds. Employment status and work characteristics also differed by type of disability. CONCLUSIONS: Rehabilitation and life skills counsellors need to pay particular attention to youth who may need extra help in gaining employment.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.295
Teacher spread0.281 · 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

Citations54
Published2010
Admission routes1
Has abstractyes

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