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Record W2016826668 · doi:10.3109/09638288.2014.939775

An ecological approach to understanding barriers to employment for youth with disabilities compared to their typically developing peers: views of youth, employers, and job counselors

2014· article· en· W2016826668 on OpenAlexafffund
Sally Lindsay, Carolyn McDougall, Dolly Menna‐Dack, Robyn Sanford, Tracey L. Adams

Bibliographic record

VenueDisability and Rehabilitation · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsWestern UniversityHolland Bloorview Kids Rehabilitation HospitalUniversity of Toronto
FundersOntario Ministry of Research and Innovation
KeywordsPsychologyQualitative researchDevelopmental psychologySociology

Abstract

fetched live from OpenAlex

PURPOSE: The purpose of this study is to explore the extent to which youth with physical disabilities encounter different barriers to finding employment compared to their typically developing peers. METHODS: This study draws on 50 qualitative in-depth interviews with a purposive sample of 31 youth (16 typically developing and 15 with a disability), and youth employers and job counselors knowledgeable about employment readiness among adolescents (n = 19). We utilize Bronfrebrenner's ecological framework to reveal the complex web of factors shaping youth's labor market outcomes. RESULTS: Only half of youth with a disability were working or looking for work compared to their peers. The findings show this was a result of different expectations of, and attitudes toward, youth with disabilities. For many youth with a disability, their peers, family and social networks often acted as a barrier to getting a job. Many youth also lacked independence and life skills that are needed to get a job (i.e. self-care and navigating public transportation) compared to their peers. Job counselors focused on linking youth to employers and mediating parental concerns. Employers appeared to have weaker links to youth with disabilities. System level barriers included lack of funding and policies to enhance disability awareness among employers. CONCLUSIONS: Youth with physical disabilities encounter some similar barriers to finding employment compared to their typically developing peers but in a stronger way. Barriers to employment exist at several levels including individual, sociostructural and environmental. The results highlight that although there are several barriers to employment for young people at the microsystem level, they are linked with larger social and environmental barriers. IMPLICATIONS FOR REHABILITATION: Clinicians working with youth should promote the development of skills that can lead to improved self-confidence and communication skills for youth. Encourage the development of extracurricular activities and social networking to build these skills and to make contacts for finding employment. Clinicians should support youth with disabilities and their parents in practicing independence skills (such as self-care, self-advocacy and navigating public transportation) they need prior to seeking employment. Vocational rehabilitation professionals should educate youth on how to disclose their condition to a potential employer, how to ask for ask for accommodations and how to market their abilities. Clinicians should help to link youth with disabilities to volunteer opportunities and to employers. Advocate for disability awareness training for employers regarding how to accommodate people with disabilities and the potential they offer in the workplace.

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)0.006
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0070.006
Scholarly communication0.0030.002
Open science0.0010.005
Research integrity0.0010.002
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 head0.110
GPT teacher head0.344
Teacher spread0.234 · 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 designQualitative
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

Citations139
Published2014
Admission routes2
Has abstractyes

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