Fetus Trafficking in Viet Nam – The New Criminal Method of Human Trafficking
Bibliographic record
Abstract
When it comes to basic rights of the fetus, including the right to life, theoretical studies around the world on human rights of the fetus still have not reached an agreement on approaches and explanation. Criminal law at the international and national levels still leaves the possibility of protecting the unborn child. Viet Nam’s criminal law is no exception to this trend. In addition, Viet Nam is currently facing human trafficking with new methods and tricks. Children are bought and paid for while still in the womb, then born abroad and given to traffickers. Children are only protected by criminal law for human trafficking if they are born, alive, and detected by the authorities. While the act of trafficking in fetuses is often easily detected by the authorities right from the stage of purchasing and paying, it is not feasible to prosecute this act for human trafficking under the criminal law of Viet Nam. This reduces the criminal law’s ability to suppress crime, at the same time, leaves many fetuses unprotected. Should criminal law be left outside the legal mechanism to protect children while in the fetal stage? This article suggests considering fetus trafficking as a form of human trafficking and to criminalize fetus trafficking. Criminal law should recognize fetus trafficking as a sign of crime or an early stage in the criminal process of human trafficking, because children need special care and protection, including appropriate legal protection before and after birth, due to their physical and mental immaturity.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".