Trajectories of academic performance in sexually abused children and potential correlates
Bibliographic record
Abstract
Background: Childhood sexual abuse (CSA) is associated with detrimental consequences in children, including lower academic performance. However, studies have rarely explored the diversity of longitudinal academic profiles among CSA victims. Objectives: The objectives of this study were (1) to identify trajectories of academic performance in CSA victims and (2) to explore potential correlates of these trajectories. Participants and settings: The study involved 738 Canadian children between the ages of 5 and 14 who had experienced CSA and their non-offending parent and their teacher. Methods: At three different assessment times, spaced 6 months apart, the child’s teacher was invited to complete a questionnaire regarding the child’s academic performance. Measures of potential correlates of the trajectories were assessed by teacher (child’s behavior problems), parents (children’s experience of peer victimization) and children (coping strategies). Results: The three-trajectory model was selected as the final model. The High functioning trajectory (42%) included children who exhibited high academic performance at the first assessment but decreased slightly over time. The Low and Increasing trajectory (16%) identified children whose academic results were initially low but improved over time. Finally, the Moderate and Stable trajectory (42%) comprised children with an average academic performance over time. Compared to the other two groups, children in the High functioning trajectory were less likely to report peer victimization and show externalizing and internalizing behavior problems as assessed by caregiver and teacher. They were also younger and living in more socially and economically advantaged backgrounds. Conclusions: These results emphasize the crucial role of available resources in a child’s environment and their protective effect on their academic adaptation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".