Discrimination and other barriers to employment for teens and young adults with disabilities
Bibliographic record
Abstract
PURPOSE: Having a disability is a barrier to securing and maintaining employment. Most research has focussed on employment barriers among adults, while very little is known about young people's experience finding paid work. METHOD: Young people aged 15-24 were selected from the 2006 Participation and Activity Limitation Survey to explore the barriers and discrimination they experienced in seeking employment (n = 1898). RESULTS: Our findings show that teens and young adults with disabilities encountered several barriers and discrimination in seeking paid employment. The types of barriers that these young people encountered varied by age and type of disability. There were fewer yet different types of barriers to working that were encountered between the two age groups (teens and young adults). Several socio-demographic factors also influenced barriers to working. Severity of disability, type and duration of disability, level of education, gender, low income, geographic location and the number of people living in the household all influenced the kind of barriers and work discrimination for these young people. CONCLUSIONS: Rehabilitation and life skills counsellors need to pay particular attention to age, type of disability and socio-demographic factors of teens and young adults who may need extra help in gaining employment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".