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The Role of Immigration as a Social Network on Shaping Entrepreneurship Tendency: A Research on Balkan Immigrant Entrepreneurs in Turkey

2012· article· en· W1846437963 on OpenAlexvenueno aff
Ali Taş, Umut Sanem Çitçi, Yusuf Cesteneci Cesteneci

Bibliographic record

VenueCanadian social science · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationEntrepreneurshipSociologySocial network (sociolinguistics)Demographic economicsPolitical scienceEconomicsLawSocial media

Abstract

fetched live from OpenAlex

The main purpose of the current study is to explain immigration concept and the effects of social networks occurring in the grounds of immigration on the entrepreneurship tendencies of immigrant entrepreneurs especially for the sampling of Balkan immigrant entrepreneurs. Keeping this main purpose in mind, interviews were made with 17 Balkan immigrant entrepreneurs. First of all, the data obtained from this research show that social networks occurring in the grounds of immigration are used by immigrant entrepreneurs in a specific way for forming work conception, providing necessary information and support to set up business, supplying with required finance and choosing the staff. Besides, the results of this research display that Balkan immigrant entrepreneurs living in Turkey would rather make use of group dynamics and sources on the basis of individual pragmatism than keep and protect them as a closed social network. Key words: I m m i g r a n t s ; I m m i g r a t i o n entrepreneurship; Social networks; Balkan immigrants

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.056
GPT teacher head0.343
Teacher spread0.286 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations7
Published2012
Admission routes1
Has abstractyes

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