Educators’ Perceptions of Human Trafficking and Implications for Professional Development
Bibliographic record
Abstract
Around 3.3 million young people are trafficked worldwide, with over half subjected to sexual exploitation (Data and Research on Forced Labour, 2024). However, little research exists on the role of school-based educators in learning about, preventing, and identifying human trafficking. This study examines educators’ knowledge of trafficking both locally and globally. Grounded in critical anti-trafficking frameworks, Schulman’s (1987) framework of teachers’ knowledge, and Bronfenbrenner and Cici’s (1994) Bioecological Model, the study surveyed 205 educators in Central Florida in the United States. Findings show that over 60% had received no training on human trafficking, while 24.3% of those who had training were uncertain about how to report trafficking cases. Educators also expressed a desire for more school-based training and professional development. Implications suggest using critical, pedagogical approaches like Ginwright’s (2018) healing-centred engagement to enhance educators’ understanding and help deter global trafficking networks.
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".