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Record W1987497859 · doi:10.3828/bjcs.2012.03

Cross-cultural and transnational identity: a case study of Bulgarian immigrants in Canada

2012· article· en· W1987497859 on OpenAlexaboutno aff
Diana Yankova, А.С. Андреев

Bibliographic record

VenueBritish Journal of Canadian Studies · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicDiaspora, migration, transnational identity
Canadian institutionsnot available
Fundersnot available
KeywordsBulgarianEmigrationDiasporaImmigrationMulticulturalismAcculturationIdentity (music)National identityGender studiesPolitical sciencePerceptionSociologyPsychologyLaw

Abstract

fetched live from OpenAlex

After highlighting concepts such as diaspora, acculturation and integration of immigrants, transnational identity, and multiculturalism policy, the authors present results from a case study of 16 Bulgarian emigrants to Canada. The aim is to investigate what changes have taken place in their perception of national and self-identity, and to what extent these changes are dependent on factors such as age, education, reasons for emigration and length of stay. The participants were interviewed as to what bonds they have retained with their country of origin in terms of observation of traditions, range of social contacts and participation in the Bulgarian community in Canada, and what ideas, customs and behavioural modes they have absorbed from the host country. Their responses provide insight into what it feels to be a transnational citizen in today's increasingly globalising world.

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)0.002
metaresearch head score (Gemma)0.004
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.285

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0360.007
Scholarly communication0.0050.002
Open science0.0020.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.065
GPT teacher head0.359
Teacher spread0.293 · 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

Citations4
Published2012
Admission routes1
Has abstractyes

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