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Record W2284732444

Call it what it is: slavery.

2014· article· en· W2284732444 on OpenAlexaboutno aff
Ron Soodalter

Bibliographic record

VenuePubMed · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsnot available
Fundersnot available
KeywordsLootingTortureLawCapitalismBlack marketCurrencyInvestment (military)Political scienceHuman rightsBusinessEconomics
DOInot available

Abstract

fetched live from OpenAlex

Most Americans do not know that victims of trafficking are right here, suffering in the dark. Trafficking is practiced in many forms and in places you'd least expect. The simple truth is, humans keep slaves; we always have. This is capitalism at its worst. Before the Civil War, slaves cost a lot. In the 1850s, a slave sold for around $1,200. In today's currency, that comes to somewhere between $40,000 and $50,000. This level of investment predisposed the owners to take care of their human property, at least to the extent that their longevity and their productivity were ensured. Today's slave can be bought for as little as $100. This price tag makes the modern slave not only affordable, but also disposable. Further, trafficking comes with a bundle of other crimes, including kidnapping, document fraud, assault, torture, rape and sometimes homicide. According to a U.S. State Department study, some 17,000 foreign nationals are trafficked into the United States from at least 35 countries and enslaved each year. Some victims are smuggled into the U. S. across the Mexican or Canadian borders; others arrive at our major airports daily, carrying either real or forged papers. Victims from Africa, Asia, India, Latin America and the former Soviet Union come on the promise of a better life, with an opportunity to work and prosper in America. Many arrive in the hope of earning enough money to support or send for their families. In order to pay for the journey, they use their life savings, or go into massive debt to people who will take advantage of them. Instead of opportunity, they find bondage. They can be found — or more accurately, not found — in all 50 states, working as farmhands, domestics, sweatshop and factory laborers, gardeners, workers in the restaurant, construction and sex industries. These people are not poorly paid employees, working at jobs they might not like. They are workers who are unable to leave and forced to live under the constant threat of violence. Although today's term may be human trafficking, by both historical and legal definition, these people are slaves. What is particularly infuriating is the fact that the crime of trafficking almost always goes unpunished. When the U.S. government and the media address the subject of human trafficking, they tend to focus on sexual exploitation, whose victims are subjected to serial rape, physical injury, psychological damage, and constant exposure to sexually transmitted diseases. Most of the less sensational forms of slave labor are right under our noses. Domestics and nannies account for a significant number of America's slaves. Agriculture is another major area of human trafficking. There are unknown numbers of victims of forced labor growing and picking our fruit and vegetables. They come here looking for steady work and a decent wage. Instead, they are enslaved by crime syndicates, families or individuals in such states as Colorado, New York, North and South Carolina, Georgia, California and Florida.... Keywords: Human trafficking Language: en

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.039
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.008
Scholarly communication0.0100.011
Open science0.0010.006
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0390.014

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.

Opus teacher head0.025
GPT teacher head0.268
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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