Criminological Study on Criminal Activities Human Trafficking in the Nusa Tenggara Timur Region (NTT), Indonesia
Bibliographic record
Abstract
The rise of trafficking of women and children in the Nusa Tenggara Timur region, Indonesia. Research method, descriptive qualitative, consisting of primary data obtained through field studies using interview techniques, secondary data from literature. The results research of criminological on human trafficking are transnational crimes that have come to the attention of countries in the world. This crime is caused by the factors of poverty, low education, difficult employment opportunities, culture in society. According to human trafficking data from 2012 to 2016 there were 643 cases, consisting of 263 cases of labor, 310 cases of sexual abuse, 65 cases of default and 5 cases of selling babies. And as many as 754 victims, consisting of 418 adult women, 218 girls, 115 adult men and 3 boys. This prevention must begin with the inculcation of moral values and character in children, where this task is carried out by families such as parents at home and teachers at school. The Indonesian National Police as a guardian of security and order in society can make efforts to instill awareness about the dangers of crime in human trafficking.
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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 | 0.000 | 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 | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".