School and Employment-Related Barriers for Youth and Young Adults with and without a Disability during the COVID-19 Pandemic in the Greater Toronto Area
Bibliographic record
Abstract
Purpose: Youth and young adults are particularly vulnerable to the socio-economic impacts of Coronavirus Disease (COVID-19). The purpose of this study was to explore barriers to school and employment for youth with and without a disability during the pandemic. Methods: This qualitative comparison study involved in-depth interviews with 35 youth and young adults (18 with a disability; 17 without), aged 16–29 (mean age 23). An interpretive, thematic analysis of the transcripts was conducted. Results: Our findings revealed several similarities and some differences between youth and young adults with and without disabilities regarding barriers to school and employment during the COVID-19 pandemic. Key themes related to these barriers involved: (1) difficult transition to online school and working from home (i.e., the expense of setting up a home office, technical challenges, impact on mental health), (2) uncertainty about employment (i.e., under-employment, difficult working conditions, difficulty finding work, disability-related challenges) and (3) missed career development opportunities (i.e., canceled or reduced internships or placements, lack of volunteer opportunities, uncertainties about career pathway, the longer-term impact of the pandemic). Conclusion: Our findings highlight that youth and young adults with disabilities may need further support in engaging in meaningful and accessible vocational activities that align with their career pathway.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".