Evaluating the Frequency, Co-occurrence, and Psychosocial Correlates of Childhood Multiple Victimization
Bibliographic record
Abstract
The current study was designed to contribute to our growing understanding of childhood multiple victimization (i.e., exposure to more than one type of victimization), which has been found to be the reality among most victimized children. Caregivers of school-aged children (N = 213) completed an online and anonymous questionnaire that assessed the victimization experiences (lifetime) and psychosocial functioning of their child, as well as collecting information on a number of socio-demographic factors. Results provide support for the ubiquitous nature of childhood multiple victimization (86.9%), as well as the common cooccurrence of lifetime victimization experiences (M exposure = 6.58). Findings highlight the important association between victimization exposure and psychosocial functioning (e.g., anxiety, depression, aggression, posttraumatic stress). The practical and theoretical implications for the prevention of childhood victimization are also discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".