A Million Piece Jigsaw Puzzle: Transition Experiences of Foster Youth Accessing Higher Education through Community College
Bibliographic record
Abstract
A college education offers people social and economic benefits, yet youth from foster care backgrounds are less likely than their peers to attain a college education, which places this already vulnerable population at higher risk for a lifetime of living on the margins of society. Foster alumni face multiple obstacles to accessing and persisting in higher education. To facilitate and support the success of this frequently overlooked population, professionals in higher education need to understand these obstacles. Little is known about the experiences of youth with foster care backgrounds as they transition into and through higher education. Although existing research has reported the academic, health, and social effects of having been in foster care, little is known about why foster alumni do not persist in higher education. This study used student-development theory, specifically Schlossberg's transition theory, Tinto's theory of student departure, and Bourdieu's work on social and cultural capital to provide a conceptual framework through which to view the lived experiences of youth with foster care backgrounds. Because, for many youths with foster care backgrounds, the pathway to the baccalaureate degree is through a community college, this study examined and explored the transition experiences of foster alumni about to begin or currently enrolled at an Oregon Community College. The study explored the factors that challenge and facilitate foster alumni persistence towards the attainment of a college degree.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".