Labor Trafficking (CCJS)

involuntary labor (force, fraud, coercion) vs. labor trafficking of minors vs. debt as blackmail

about 10k victims, domestic labor, ago, traveling sales, and food service as well as illicit industries

withholding pay, excess hours, threatening to report to authorities, verbal abuse, and denying needs

closes the tarif act loophole that allows for importation in cases where demand cannot be satisfied

H-1B Visas > For graduate-level experts in certain positions that companies cannot source domestically
H-2A > Temporary/seasonal agricultural jobs
H-2B > Temporary/seasonal non-agricultural jobs
J-1 > Exchange visitors, e.g. nannies, teachers, students, summer camp. work, etc.
A3 > Diplomat visas, which protect holders from American laws > diplomatic immunity
H-2A and 2B visas are the most likely to be victims

Globally, forced labor is most common across eastern Europe, central Asia, and south/central Africa. Estimated 16.4 million victims (4.3 million children) generating $51.2 billion yearly, mostly as domestic work, agro/forestry and fishing, and construction, manufacturing, mining, and utilities (children more frequently in this industry, as well as in lower-income countries)

Institutional > Social instability, political conflict/corruption, natural disaster
Community > Discrimination, region (rural/isolated)
Family > Poverty, educational access, food insecurity
Individual > Age (risk varies on region > higher income = adults, low income = children),
gender (domestic work = women, more generally men)

you can’t suppress demand. people can not buy sexual services, people can’t really not buy things made with forced labor

prevention and protection, very individualized vs. fair treatment, supply chain exposure, etc.

Financial Services > looking at traffickers' money trails, monitoring for generally suspicious activity, and specific partnerships with IT companies and financial businesses and institutions
Big Data > large scale data available via the internet that can display patterns that indicate trafficking e.g. emergency room data, maps, images online, security feeds, missing persons reports, etc. network analysis (examines their interactions to determine connections to traffickers)

Local law enforcement, the least likely to encounter victims, are the least likely to have training. More training needed at all levels, lack of law enforcement presence More training for prosecutors
Fear of consequences for self-ID
Perception of corruption and mistrust of the law
Physical isolation, e.g. rural areas, vessels, etc.

Increases in prosecution of civil labor violations > not trafficking itself, but can uncover trafficking, and if the case is not strong enough, there is another option
Involve healthcare providers! likely viewed as less corrupt or safer
Name and Shame > publically expose business practices

can overlap, but it must pass the force, fraud, coercion test to be considered trafficking. pursuing unfair labor practices can make prosecuting trafficking easier

compulsion must be done by someone other than parents

migrants slightly more, but this applies so everyone. globally men make up the majority, but it is far more balanced than sex trafficking and more complex in that it varies by industry (age does too, and by region)

human rights: too individualized, too many services too thin on the ground for too many different industries and situations
labor: too focused on the law, and not enough on people and services for victims

money quickly withdrawn from accounts after deposition
movement of many people in and out of a small residential dwelling
regular use of specific ATMs by specific people