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Record W7018809223

Do Afghan Youth Think of Migrating to other Countries under the Taliban Regime?

2022· other· en· W7018809223 on OpenAlexaboutno aff

Bibliographic record

VenueMunich Personal RePEc Archive (Munich University) · 2022
Typeother
Languageen
FieldSocial Sciences
TopicPolitics and Conflicts in Afghanistan, Pakistan, and Middle East
Canadian institutionsnot available
Fundersnot available
KeywordsAfghanSeekersRefugeePower (physics)Youth unemployment
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.937
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.026
GPT teacher head0.260
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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