Canadian cross-sectional survey of healthcare, social and community service providers’ capacity to respond to sex trafficked persons
Bibliographic record
Abstract
OBJECTIVE: To examine the impact of the extent of education and/or training on sex trafficking among healthcare, social and community service providers and the impact of education and/or training on their capacity to respond to sex trafficked persons. DESIGN: Cross-sectional survey. SETTING: An anonymous, online survey assessing perceptions of, and capacity to respond to, sex trafficking was distributed between February and August 2023 via social media platforms and with professional healthcare, social service and community associations and organisations across Canada to share with their members. PARTICIPANTS: 553 healthcare, social and community service providers. OUTCOME MEASURES: Seven 6-point Likert scale items were used, as part of a larger survey, to measure capacity to respond to sex trafficking. Specifically, respondents were asked to rate their awareness of red flags and capacity to identify, talk to, interview, enhance the safety of, provide appropriate resources or referrals for and collaborate with other professionals to support sex trafficked persons. RESULTS: Although most respondents (86.8%) reported having received some education and/or training on sex trafficking, the vast majority (94.8%) believed that they would benefit from additional education and/or training. Compared with those with no previous sex trafficking education and/or training, those who received less than 5 hours of education and/or training (b=3.56, p<0.0001), 5-15 hours (b=8.03, p<0.0001), and 16 or more hours (b=11.13, p<0.0001) reported higher overall capacity to respond appropriately to sex trafficked persons. CONCLUSIONS: As the number of hours of education and/or training on sex trafficking increased, so did respondents' capacity to respond to sex trafficked persons. These results highlight a need for more education and training to help build capacity among healthcare, social and community service providers in identifying sex trafficked persons and providing appropriate care. Appropriately trained service providers can better support sex trafficked persons' complex needs and potentially mitigate adverse outcomes.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".