Sexual Assault Case Attrition: The Voices of Survivors
Bibliographic record
Abstract
Sexual assault case attrition is pervasive within the criminal justice process. Despite initiating a police report following sexual victimization, many survivors make the decision to withdraw their police report and do not proceed with charges. Attrition of sexual assault cases at the point of entry to the criminal justice system is problematic for survivors as justice is not achieved and connections to support services are lacking. As such, the purpose of this research was to explore the first-hand account of sexual assault survivors who withdrew their report of sexual assault after disclosing the victimization to the police. Qualitative research was used to explore the experience of 14 sexual assault survivors who met the inclusion criteria for the study. Data collection included open-ended interviews that were audio-recorded, transcribed, and entered into NVIVO for analysis. Colaizzi’s analytic method was used to analyze the data and resulted in the identification of three themes related to the decision not to pursue charges and a fourth theme describing the overall essence of the decision-making process. These themes included: (1) Overwhelming Police Process, (2) Police Communication about Charging/Process, (3) Loss of Faith in Justice System, and (4) No Hope. These findings provide insight from survivors supporting the saliency of the disclosure experience and the power of police communication. A trauma-informed police response during sexual assault disclosures is recommended based on the critical importance of supporting survivors, improving the investigative process, and holding perpetrators accountable. This approach may decrease attrition and improve justice for victims.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".