Peran Perempuan dalam Mengembangkan Usaha Mikro Kecil dan Menengah dalam rangka menuju Masyarakat Ekonomi ASEAN di Kota Tangerang Selatan
Bibliographic record
Abstract
This article describes the efforts to prevent the practice of women trafficking in Nusa Tenggara Timur (NTT). Data shows that NTT is one of the provinces with a high level of human trafficking practices. This happens because several problems, such as: poverty, low education, weak law enforcement, lack of availability of employment and injustice in the social, political and economic fields. In addition, the strong network of human trafficking mafia actors in the rural areas. This condition is exacerbated by the tradition of the community which places women as second class. Women are often victims of poverty and other social problems. Using case study methods and process tracking analysis, this article argues that with socialization, building cooperation with traditional leaders (tokoh adat), a campaign to eliminate discrimination against women, empower Balai Latihan Kerja and build gender-based products can prevent the practice of trafficking in women in NTT. Key Words: Prevention, Women Trafficking, Nusa Tenggara Timur
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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) | 0.014 | 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".