Preventing Human Trafficking of Refugees from Ukraine: a Rapid Assessment of Risks and Gaps in the Anti-Trafficking Response
Bibliographic record
Abstract
This article discusses a rapid assessment of risks and gaps in the anti-trafficking response, related to the prevention of human trafficking of refugees from Ukraine in the immediate aftermath of the start of the war (March-April 2022). For this assessment numerous actors have been interviewed from Ukraine and neighbouring countries and a study visit has been organized to Poland in April 2022. This assessment reviews the trafficking risks (and at risk groups) related to the outflow of Ukrainian refugees in Eastern and Central Europe, the extent to which these risks are being addressed by the agencies involved in the humanitarian response and the identification of the possible roles for anti-trafficking organizations. To address the gaps and needs that are identified in the anti-trafficking response in Ukraine and neigbouring countries (Poland, Romania, Moldova, Hungary and Slovakia) several recommendations are made, addressing governments/international organisations, anti-trafficking NGOs and donors, to (I) reduce the vulnerabilities to human trafficking; (ii) to ensure the identification of trafficked persons and accountability of perpetrators; and (iii) to ensure adequate referral and assistance to trafficked persons.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".