Unfounded Sexual Assault: Women’s Experiences of Not Being Believed by the Police
Bibliographic record
Abstract
One in four women will experience sexual assault in their lifetime. Although less than 5% of sexual assaults are reported to law enforcement, one in five cases reported to police are deemed baseless (by police) and therefore coded as "unfounded." Police officers are in a unique position to act as gatekeepers for justice in sexual assault cases, given their responsibility to investigate sexual assault reports. However, high rates of unfounded sexual assaults reveal that dismissing sexual violence has become common practice amongst the police. Much of the research on unfounded sexual assault is based on police perceptions of the sexual assault, as indicated in police reports. Women's perspectives about their experiences with police are not represented in research. This qualitative study explored women's experiences when their sexual assault report was disbelieved by the police. Data collection included open-ended and semi-structured interviews with 23 sexual assault survivors. Interviews covered four areas including the sexual assault, the experience with the police, the experience of not being believed, and the impact on their health and well-being. Interviews were audio-recorded, transcribed, and entered into NVIVO for analysis. Data were analyzed using Colaizzi's analytic method, resulting in the identification of four themes, including, (a) vulnerability, (b) drug and alcohol use during the assault, (c) police insensitivity, and (d) police process. The women in this study who experienced a sexual assault and reported the assault to police were hopeful that police would help them and justice would be served. Instead, these women were faced with insensitivity, blaming questions, lack of investigation, and lack of follow-up from the police, all of which contributed to not being believed by the institutions designed to protect them. The findings from this research demonstrate that police officers must gain a deeper understanding of trauma and sensitive communication with survivors of sexual assault.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".