Disclosure and non-disclosure of childhood sexual abuse in Australia: Results from a national survey
Bibliographic record
Abstract
BACKGROUND: Little population-based evidence exists about prevalence of lifetime disclosure and non-disclosure of child sexual abuse (CSA). Evidence is lacking about disclosure by girls and women compared with boys and men, and gender diverse individuals. It is unclear if disclosure is more common in contemporary society, and if disclosure is influenced by abuse severity and perpetrator type. OBJECTIVE: We aimed to identify prevalence of lifetime disclosure of CSA, and prevalence by gender, age group, abuse severity and perpetrator. PARTICIPANTS AND SETTING: The Australian Child Maltreatment Study collected information about CSA victimisation from a nationally representative sample of 8503 individuals aged 16 and over; 28.5 % (n = 2348) experienced CSA and provided information about disclosure. METHODS: We generated national estimates of lifetime CSA disclosure, compared results by gender and age group, and identified differences by severity and perpetrator. RESULTS: Prevalence of lifetime CSA disclosure was 54.8 %, and prevalence of non-disclosure was 45.2 %. Disclosure was more common for women (60.3 %) than men (42.2 %). Disclosure was more common among those aged 16-24 (70.5 %) than those aged 25-44 (61.9 %) and 45 and over (46.2 %). Prevalence was similar across four CSA sub-types (47.2 %-58.2 %). Disclosure varied across perpetrator classes. CONCLUSIONS: Population-wide, almost one in two people who experience CSA had not disclosed. Men and those aged 45 and over were less likely to disclose. Increased disclosure by younger participants indicates progress in societal understanding of CSA. However, continued widespread non-disclosure indicates further efforts are needed to support those with lived experience of CSA to seek assistance.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".