An exploratory evaluation of a model of care for youth who are at risk of sexual exploitation and human trafficking
Bibliographic record
Abstract
Abstract The sexual exploitation of children and youth remains a critical issue within the child welfare system, despite the limited availability of models of care to support these vulnerable individuals. The START with the YOUTH (STAR‐Y) program adopts a preventative approach, offering personalized care and wraparound support to youth exhibiting at‐risk behaviours. This paper employs a case study methodology using both thematic and content analyses to longitudinally assess the effectiveness of this exploratory program. This evaluation encompasses a comprehensive assessment of various factors associated with the risk of sexual exploitation among program participants. Throughout the program's extended duration (originally planned for one year), predefined risk factors, including concerning Internet behaviours, were monitored and analysed. Qualitative data were gathered through interviews and observations, focusing on the experiences of both the youth and their foster parents. The results highlight the program's successful implementation, with youth enrollment (N = 3) demonstrating a reduction in sexual exploitation risk factors over time, including a decrease in behaviours such as concerning Internet usage. The importance of wraparound support and the foster parent‐youth relationship in mitigating risk and nurturing resilience became evident. This exploratory evaluation serves as the initial phase of a comprehensive assessment aimed at understanding how to effectively support youth within this population, including those at higher risk, such as those possibly involved in sex trafficking. The study's findings provide valuable insights into strategies for mitigating the risk of sexual exploitation among vulnerable youth, informing future endeavours to develop and implement similar programs within the child welfare system.
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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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".