‘Then I Met This Lovely Police Woman’ Young People's Experiences of Engagement with the Criminal Justice System
Bibliographic record
Abstract
Abstract Young people's voices detailing how they experienced engagement with the criminal justice system following child sexual abuse, what was helpful or unhelpful and how services can be improved to minimise secondary victimisation and maximise the potential for healing are largely absent from the research literature. This paper draws on semi‐structured interviews with a culturally diverse sample (n = 47) of young people aged 14 to 25 across Ireland and Canada about their experiences of disclosure and engagement with systems. Data were collected pertaining to experiences engaging with law enforcement personnel using thematic analysis with a trauma‐informed lens. The research identified three key themes: the importance of feeling safe through kindness, transparency and being believed; the importance of having a say; and the importance of timely court processes. The study builds on the small body of qualitative research illustrating young people's lived experiences of engaging with the criminal justice system and provides empirical support for promoting a trauma‐informed approach in how police engage with young people. Guidance is offered for police professionals on how to engage with adolescents following sexual abuse.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| 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".