An Exploratory Study of Victim Resistance in Child Sexual Abuse: Offender Modus Operandi and Victim Characteristics
Bibliographic record
Abstract
The use of self-protection strategies and related situation in rape has been studied by several scholars. The circumstances in which children are more likely to resist sexual victimization have, however, not been studied. This study examines the association between offence-related factors-specifically, the preoffence situation, the modus operandi strategies adopted by offenders, and victim characteristics-and victim resistance in sexual offences against children.The sample consisted of 94 adult offenders convicted of having committed a sexual offence against a child (or adolescent) of 16 years of age or younger and who agreed to provide confidential self-report data concerning their offending behavior and victim resistance actions. Victim resistance strategies were regrouped into three categories, namely, physical resistance, forceful verbal resistance, and nonforceful verbal resistance. The total number of resistance strategies was also used in the analyses. Overall, the age of the victim was found to be related to nonforceful verbal resistance, and violence was related to all forms of resistance.Younger girls were found to be more likely to employ nonforceful verbal resistance than older girls and to use a greater number of strategies as well. To provide reliable knowledge to build on for reducing the risk of child sexual abuse, this study suggests the need for prevention programs to include empirical findings regarding the circumstances in which children are more likely to resist sexual victimization.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".