The Sum of a Human’s Parts: Global Organ Trafficking in the Twenty-First Century
Bibliographic record
Abstract
filled by a rogue's gallery of miscreants who, for a profit, will dupe the poor to provide organs for the rich.The dark side -namely organ trafficking -is truly horrifying and reveals a murky world of traffickers, duped donors, wily 'body-parts brokers,' corrupt politicians, police and lawyers along with complicit surgeons and hospitals and ill but relatively wealthy organ recipients, so desperate to renew their own gift of life, that they enable the corruption and overlook the suffering caused to others.While this century and the one recently passed have brought the world unprecedented wonders in terms of technology, these eras may later be remembered more for the exacerbation of human misery, the egregious violations of human rights, and economic inequity that brought so much wealth to a few and bare subsistence to so many.The era will also be recalled as one in which progress and regress twinned through a political and social series of crises, wars, revolutions, and recessions.For those chosen by Fate to enjoy a life of comfort, the twentieth and twenty-first centuries provide more possibilities and choices than humans have ever known.Unfortunately, the very industrial and technological wonders that have brought us so many cheap consumer goods and filled our homes with so much 'stuff,' have also, in their production, wreaked havoc on the environment.For the billions whose lot was cast for a life of poverty, this era has brought hunger, famine, disease, air and water pollution, soil depletion, and an inability to exercise many choices to break out of the vicious cycle.Although there is a decline in absolute poverty, there is also an apparent increase in economic inequity, the gap between rich and poor, the chasm that gives endless choice to some and limited options to others.Essentially, the decision to sell a body organ like a kidney is made from a position where there are no alternatives or options.It is a manifestation of dire economic necessity, sometimes a means for an entire family briefly to eat and survive or pay off a debt to an assertive moneylender.Over nine million people die annually because of hunger and malnutrition. 44. Anup Shah, Causes of Hunger Are Related to Poverty, GLOBAL ISSUES (July 8, 2008), http://www.globalissues.org/article/7/causes-of-hunger-are-related-to-poverty.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
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".