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Record W80460004

Expendable People: Slavery in the Age of Globalization(1)

2000· article· en· W80460004 on OpenAlexaboutno aff
Kevin Bales

Bibliographic record

VenueJournal of international affairs · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Maritime and Colonial Histories
Canadian institutionsnot available
Fundersnot available
KeywordsShadow (psychology)GlobalizationState (computer science)PhenomenonConfusionPolitical economyWorld War IISociologyLawPolitical scienceHistory
DOInot available

Abstract

fetched live from OpenAlex

Once officially abolished, slavery was transformed: adopted as an illicit enterprise, it has mirrored changes in the general economy. No longer viewed as property, people today are seen merely as disposable inputs into production. Slavery continues around the world, but not in the way that most of us think of it. Since its wide abolition in the late 19th century, slavery has slipped easily into the shadow economy. Having done so, it began to change and develop in ways much more fluid and less visible than when it was legally regulated. In this article, I will illuminate the current state of slavery in the world. I will also demonstrate how new forms of slavery have evolved rapidly into a globalized economic pursuit since the Second World War. I will then examine two case studies of slavery as it is practiced in Mauritania and Sudan, addressing the difficult question of slave `redemption' in Sudan and shedding light on this problem by contextualising it historically and socially Finally, I will look at some possible approaches to confronting slavery in this century. The history of slavery spans most of human history and has taken many forms. While slavery continues today in a much-changed way, our understanding of it tends to be stuck in the 19th century The common perception of slavery as the ownership of people has led to confusion about what constitutes slavery today. To add to this confusion, none of the 300 laws and international agreements written since 181S to combat this phenomenon have defined it in exactly the same way. This has resulted in a hodgepodge of terms and definitions covering chattel slavery, debt bondage and forced prostitution, as well as such divergent conditions as incest, organ harvesting and prison labor. I define slavery as the complete control of a person for economic exploitation by violence or the threat of violence. The remarkable variety of human exploitation discussed below suggests, however, that there are gray areas even in this strict definition. My aim is to discuss only the social and economic relationships that constitute enslavement, even if this means excluding a discussion of prison labor, child labor or terribly exploited workers who are still free to leave their employers. Using this definition of slavery as a guideline, my best estimate of the number of slaves in the world today is 27 million. Where are all these slaves? An estimated 15 to 20 million are bonded laborers in India, Pakistan, and Nepal. The remainder is concentrated in Southeast Asia, Northern and Western Africa, and parts of South America, though slavery can be found in almost every country in the world including the United States, Japan, and many European countries. Today's total slave population is greater than the population of Canada and nearly five times greater than the population of Israel. Most slaves tend to be used in simple, non-technological and traditional work. The largest proportion works in agriculture. Slaves are also used in many other kinds of work: brick making, mining and quarrying, textiles, leather working, prostitution, gem and jewelry making, cloth and carpet making, domestic servitude, forest-clearing, charcoal making and working in shops. While much of their work is aimed at local sale and consumption, slave-made goods filter throughout the global economy. For example, carpets, fireworks, jewelry, metal goods, steel (made with slave-produced charcoal), and foods such as grains, rice and sugar are exported directly to North America and Europe after being produced using slave labor. In countries where slavery and industry co-exist, cheap slave-made goods and food keep factory wages low and help make everything from toys to computers less expensive. In addition, transnational companies, acting through subsidiaries in the developing world, take advantage (often unwittingly) of slave labor to increase dividends to their shareholders. Slavery, like many illegal activities, adapts rapidly to changing legal, economic and social conditions. …

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.011
Scholarly communication0.0060.006
Open science0.0010.006
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.009
GPT teacher head0.272
Teacher spread0.263 · 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
GenreEmpirical

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

Citations55
Published2000
Admission routes1
Has abstractyes

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