2022 Trafficking in Persons Report: Honduras
Bibliographic record
Abstract
In the last five years, Honduras has experienced severe human trafficking issues, with domestic and foreign victims exploited both within the country and internationally. Honduran women and children are particularly vulnerable to sex trafficking, not only locally but also in nations like Belize, El Salvador, Guatemala, Mexico, Spain, and the United States. There's a specific targeting of vulnerable groups, including LGBTQI+ individuals, migrants, internally displaced persons (IDPs), persons with disabilities, child laborers, children of migrants, and residents of crime-controlled areas. The COVID-19 pandemic has amplified risk factors such as family instability, unemployment, and limited healthcare access, worsening the trafficking situation. Exploitation often occurs within victims' homes or communities, sometimes involving relatives or acquaintances. Trafficking forms also include forced labor, with adults and children coerced into street vending, begging, domestic work, drug trafficking, and various roles in the informal sector. This issue extends beyond Honduran borders, notably to Guatemala, Mexico, and the U.S. Children, especially those from Indigenous and Afro-descendant groups, including Miskito boys, face forced labor risks in various industries. Homeless children are especially susceptible to both sex and labor trafficking. Urban areas see criminal networks, including gangs, forcing girls into sex trafficking and children into criminal activities, though there's a reported rise in such gang activities in rural locales. The digital age sees traffickers increasingly using social media to lure victims with deceptive job offers, continuing to prey on vulnerable groups. Honduras is also a hotspot for child sex tourism, with offenders primarily from Canada and the U.S. Moreover, migrants in transit from various continents through Honduras to the U.S. are highly susceptible to trafficking exploitation. Compounding the issue, corruption and official complicity within Honduras have been known to facilitate these trafficking crimes, indicating systemic challenges in addressing the problem.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".