Do Afghan Youth Think of Migrating to other Countries under the Taliban Regime?
Bibliographic record
Abstract
Migration of Afghans, particularly the young generation made headlines, when the Taliban took power in Afghanistan. Many countries including the USA, Germany, UK, Canada and Australia brought major changes in assessing documents of Afghan asylum seekers at risk. This paper studies the opinion of Afghan youth migrating under the Taliban regime. We surveyed 280 youth in Balkh and Samangan provinces of Afghanistan. The respondents were selected using convenience and snow balling sampling strategies. The administrated questionnaire consisted of three main segments such as demographic characteristics, financial condition and migration. The findings expose that 91% of the respondents think of migrating to other countries. Furthermore, they confirmed insecurity, unemployment, dissatisfaction with the Taliban and exposing restrictions on women activities by the Taliban as the key drivers of their desire to emigrate. The majority of the youth surveyed (83%) consider regular migration channels in particular family reunion, study visa, humanitarian and labor visas. Even so, 17% of young people think of migrating through irregular channels. A significant proportion of the respondents (40%) selected Germany as a de-sired country of their destination among other options. This paper makes recommendations for improving the job market and providing better security services to discourage young people from leaving the country.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".