Non-Conventional Migration: An Evolving Pattern in South Asia
Bibliographic record
Abstract
The circumstances prevailing in South Asia (SA) have led to a plateauing migration stream that has resulted in several categories of migrants. The underlying factors driving migration have been identical in all the countries of SA. In recent years, however, poverty, conflicts, political and religious persecution, natural disasters and climate change have emerged as the most prominent drivers. External migration flow from SA has more than doubled between 2000 and 2015. This is a dynamic region, with millions (over 38m in 2017) of people crossing borders, both intra-regionally and extra-regionally. In recent years, wealthy citizens from SA have begun to move out of their countries with the intention of settling down elsewhere. This tendency has raised concerns among the policy makers because they create the grounds for reverse remittance flows. This research is meant to identify and contribute to the discourse of a new category of migrants (non-conventional migration) who are different from those in the conventional migration stream that included economic and forced migration. This research has crucial policy implications for both origin and destination countries.
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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 | 0.000 | 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 | 0.000 | 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".