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Record W2768973396 · doi:10.1080/00323187.2017.1334509

Canadian immigrants at the polls: the effects of socialisation in the country of origin and resocialisation in Canada on electoral participation

2017· article· en· W2768973396 on OpenAlexaffabout
Stephen White

Bibliographic record

VenuePolitical Science · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsCarleton University
Fundersnot available
KeywordsImmigrationPoliticsAffect (linguistics)Political scienceCountry of originPolitical economyDemographic economicsDevelopment economicsSociologyEconomicsLaw

Abstract

fetched live from OpenAlex

Political socialisation plays a crucial but complex role in determining how immigrants adjust to the political environment of their host country. This study examines the effects of initial political socialisation and resocialisation on immigrants’ electoral participation in Canada. It addresses three questions: To what extent does the outlooks that develop from earlier political experiences in the country of origin shape immigrants’ subsequent electoral participation in Canada? To what extent, and how, does subsequent experience with politics in Canada affect electoral participation? And finally, how does initial socialisation in the country of origin condition resocialisation in Canada? The results indicate that not only does resocialisation leave a unique and lasting imprint on immigrant electoral participation in the host country, but also that the nature of resocialisation process in the host country is conditioned by the distinctive political outlooks immigrants acquire under different political regimes in their respective countries of origin.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0060.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.038
GPT teacher head0.364
Teacher spread0.326 · 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 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

Citations18
Published2017
Admission routes2
Has abstractyes

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