Confidence, Training and Challenges for Canadian Child Advocacy Center Staff When Working with Cases of Online and In-person Child Sexual Exploitation
Bibliographic record
Abstract
Child Advocacy Centers are interdisciplinary hubs that play a vital role in responding to child maltreatment, especially sexual abuse. Sexual abuse cases increasingly involve an online component, but no studies have examined the experience of Child Advocacy Center staff in dealing with online sexual exploiftation. This study surveyed 37 staff at five Child Advocacy Centers in Alberta, Canada to understand their ability to recognize and respond to concerns about online and in-person sexual exploitation of their clients. The majority of respondents (54%) dealt with cases that involved grooming, luring, sexual abuse and child sexual abuse imagery (also known as child pornography) in the last year. Staff were equally confident in their ability to recognize and respond to grooming, luring, sexual abuse and child sexual abuse imagery. However, staff were more likely to have formal training in identifying sexual abuse and less likely to encounter difficulties in responding to sexual abuse relative to grooming, luring or child sexual abuse imagery. Clinicians used similar therapies when working with youth impacted by sexual abuse versus child sexual abuse imagery. Given that most Child Advocacy Center staff in our sample dealt with online child sexual exploitation, additional training in this area may be warranted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".