Child maltreatment, maladaptive cognitive schemas, and perceptions of social support among young women care leavers
Bibliographic record
Abstract
Abstract The purpose of the study was to evaluate the associations between child maltreatment, cognitive schemas of disconnection/rejection reported in emerging adulthood, and social support perceived in emerging adulthood among young women who have exited placements in residential care. The sample is derived from a longitudinal study conducted with 132 young women who had been placed in residential care during adolescence in Montreal (Canada) in 2008–2009. The present study relied solely on the last measurement wave of this study, which was conducted approximately 5 years (2012–2014) after Wave 1. At this time, participants were out of residential care (mean age = 19.4 years). Results showed that the more severe the retrospective accounts of child maltreatment were, the less social support young women perceived as available to them in emerging adulthood. When the tendency to endorse disconnection/rejection schemas is considered, the direct connection between maltreatment and perceived social support disappears, and we instead see an indirect relationship through these schemas. Findings suggest that programs and services must go beyond identifying social‐support networks for young women care leavers. Considerable effort should be devoted to helping these young women develop the skills they need to build and maintain trusting relationships with significant people around them.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".