Stability indicators, child welfare provisioning and trajectory into university for care-experienced youth
Bibliographic record
Abstract
Purpose Children and youth who enter the care system have lower educational outcomes and university participation rates than their peers. This study aims to understand trend exceptions by examining the background of care-experienced undergraduates attending a research-intensive university in Canada. Design/methodology/approach Informed by social affordance theory, this study examined the presence of four indicators of stability (home, household occupants, school and legal status) during participants’ final three years of secondary education. Care-experienced undergraduates (N = 30) completed an online questionnaire. Associations between stability indicators, child welfare involvement in the final year of high school, educational outcomes and routes into higher education were analysed. Findings Stability across three to four indicators was experienced by 40% of participants, while 47% reported changes across three to four indicators. Only 20% had a change of school as compared to 47%–60% for other indicators. During their final year of high school, 73% of participants were supported by the child welfare system, with 50% being supported via a support program specifically for 16- to 18-year-olds. Stability scores were significantly lower for this latter subgroup compared to those who spent time in foster or group care and those who did not receive child welfare support during the final year of high school. Ninety percent of participants graduated from high school, 67% with the grades required to attend university. Three trajectories into undergraduate study were identified but could not be predicted using regression models. Originality/value This paper focuses on what has supported progression into a research-intensive university for care-experienced young adults and highlights the role of support programs for 16- to 18-year-olds.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".