Mature Women Beyond Foster Care: Narratives on Fractors contributing to Subjective Well-Being and Life-Sustaining Skills
Bibliographic record
Abstract
Studies show that African American children enter foster care at a higher rate and remain in foster care longer. The numbers of Black children in foster care increases in any given year. Studies found that even when controlling for risk and poverty, race affects the decision of whether to provide services or remove children from their families. Although poverty may serve as an indicator of risk, when race is included, it changes the decision threshold. African American women who aged out of foster care and are living self - sustaining lives are small in number and there is an absence of research on their experiences after leaving care. Although there is a plethora of research on the disproportionate overrepresentation of African American children in the child welfare system, there is a dearth of research on adult women who are leading productive lives despite the challenges of having been in foster care. Studies show that adolescent girls lack the skills to navigate their independence after emancipation, become pregnant, and end up on welfare, thereby continuing a cycle of Child Protective Service involvement for their own child(ren). Some girls resort to prostitution or gang involvement as a means to earn money to support themselves. In California, 67% of females who emancipated from the child- welfare system had at least one child within 5 years of leaving care. Although the statistics show poor outcomes for adolescent girls after leaving care, this study hopes to provide a picture of different outcomes. This study examined factors that influenced the motivation, perseverance, and development of life-sustaining skills and personal and interpersonal influences associated with subjective well-being after emancipating from foster care, and the accomplishment of educational goals. The results of the study found that positive mother-child relationships, support from trusted adults, independence, and self- reliance contributed to motivation to persevere. Additional findings included the determination to improve one's life and perceived achievement of goals despite adversities, contributing to subjective well-being in adulthood. Recommendations suggested the inclusion of foster youth in the decisions made for them, prioritizing their needs prior to placement with relatives.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.012 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".