Human Trafficking: A Case of Deceived Aspiring Emigrants in Punjab
Bibliographic record
Abstract
Exploratory in nature, the study conducted on 120 deceived aspiring emigrants from purposively selected two districts of Doaba region in Punjab revealed that most of the respondents had education only up to school level. Majority of those who applied for visa to foreign countries belonged to general caste. Most of the respondents wanted to go to Canada but on travel agent's suggestion opted for other countries. It was found that more than half of the respondents came to know about fraud within six months of applying for visa, whereas one third came to know within a year that they had been cheated of fraudulent travel agents. The amount they lost in fraud varied from 50 thousand to five lakhs. There is an urgent need to aware the public about fraudulent cases through mass media. Government should formulate a specialized unit at the national level as agents from several states collaborate in their operation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".