Sexual assault: women’s voices on the health impacts of not being believed by police
Bibliographic record
Abstract
BACKGROUND: Sexual assault is a prevalent crime against women globally with known negative effects on health. Recent media reports in Canada indicate that many sexual assault reports are not believed by police. Negative reporting experiences of sexual assault have been associated with secondary victimization and trauma among survivors. However, little is known about the impact that being sexually assaulted and not believed by police has on a survivor's health and well-being. The purpose of this study was to explore women's experiences of not being believed by police after sexual assault and their perceived impact on health. METHODS: We conducted open-ended and semi-structured interviews with 23 sexual assault survivors who were sexually assaulted and not believed by police. The interviews explored the self-reported health impacts of not being believed by police and were conducted from April to July, 2019. All interviews were audio-recorded, transcribed, and entered into NVIVO for analysis. Data were analyzed using Colaizzi's analytic method. RESULTS: Analysis revealed three salient themes regarding the health and social impact of not being believed by police on survivors of sexual assault: (1) Broken Expectations which resulted in loss of trust and secondary victimization, (2) Loss of Self, and (3) Cumulative Health and Social Effects. The findings showed that not being believed by police resulted in additional mental and social burdens beyond that of the sexual assault. Many survivors felt further victimized by police at a time when they needed support, leading to the use taking of alcohol and/or drugs as a coping strategy. CONCLUSION: Reporting a sexual assault and not being believed by police has negative health outcomes for survivors. Improving the disclosure experience is needed to mitigate the negative health and social impacts and promote healing. This is important for police, health, and social service providers who receive sexual assault disclosures and may be able to positively influence the reporting experience and overall health effects.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".