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Record W2060269111 · doi:10.5539/ass.v6n11p197

Iranian Diaspora: With focus on Iranian Immigrants in Sweden

2010· article· en· W2060269111 on OpenAlexvenueno aff
Asadulah Naghdi

Bibliographic record

VenueAsian Social Science · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsHomelandImmigrationDiasporaSociologyCommunication sourceFeelingFocus groupRefugeeGender studiesPolitical scienceSocial psychologyPsychologyLaw

Abstract

fetched live from OpenAlex

Based on international data, nowadays, one of the every thirty-five people is living away from his/her homeland. In this respect, the United Nation has called current century an era of greatest human displacement in the history. In the last decades Iran was one of ten top migrant's receiver and sender society. Although there is no precise statistics about Iranians abroad, but according to formal speech, three-five millions of Iranians are dispersed around the world (Diaspora). Thus, studying those social problems by local researchers of social sciences is quite essential, because most of internal researches related on motivations and tendencies (potential immigrants), with a general focus on elites. There have been few studies on the Iranian immigrants and their social issues. This research employs Mixed Methods that integrates questionnaire, narrative interviews, observations, and participant observations. This paper mainly focuses on social problems of Iranian immigrants in Sweden, including employment, marriage, divorce, promoting education after immigration, immigration timing and reasons, satisfaction of life (family, income, and job) and immigrant's attitudes about the behavior of the host society toward them, adaptation, feeling as outsiders, and willingness to return to homeland.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.870
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.294
Teacher spread0.281 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations22
Published2010
Admission routes1
Has abstractyes

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