Care leavers’ employment experiences and outcomes: Choices and Social structures
Bibliographic record
Abstract
• Advances theorizing on employment outcomes of youth transitioning out of the child welfare system. • Identifies multiple social structures leading to poor employment outcomes. • Argues that care leavers’ choices are restricted as they navigate employment due to multiple factors. While young adults who transitioned from out-of-home care (also referred to as care leavers in this article) are globally recognized as a disadvantaged population with increased vulnerability to negative employment outcomes, their voices are underrepresented in research and theorizing on this topic is limited. Drawing on in-depth, semi-structured interviews conducted in Ontario, Canada with 21 young adults ages 19–27 who transitioned from out-of-home care (i.e., foster or residential group) and associated with the child welfare system, this article examines care leavers’ first-hand experiences of poor employment outcomes through a social justice lens (i.e., intersectional individualization). The findings suggest that they had inadequate employment preparation and skills before transitioning out of care and experienced barriers to employment after transitioning. Using a social justice lens by drawing on intersectional individualization theorizing, this article argues that while care leavers try to navigate employment, their multiple, intersecting identities, and invisible experiences as well as structural changes restrict their choices, which together increase their vulnerability to poor employment outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| 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".