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Record W4400115388 · doi:10.1080/1369183x.2024.2363850

In the eye of the beholder: national boundary perceptions and their identity implications across immigrant generations in multinational states

2024· article· en· W4400115388 on OpenAlexaffabout
Antoine Bilodeau, Kristina Bakkær Simonsen

Bibliographic record

VenueJournal of Ethnic and Migration Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsConcordia University
Fundersnot available
KeywordsImmigrationMultinational corporationPerceptionIdentity (music)Boundary (topology)National identityGender studiesSociologyPolitical sciencePoliticsPsychologyLawAestheticsArt

Abstract

fetched live from OpenAlex

The concept of national boundaries has been employed extensively in the social sciences, with most research focusing on the host society's perspective. This study innovates by measuring immigrants’ perceptions of how boundaries of their host nation are drawn and examining how such perceptions impact their national identifications in a multinational context, more specifically in the province of Quebec in Canada. It relies on a stratified sample of first- (n = 1129) and second-generation immigrants (n = 1286) as well as non-immigrants (n = 1472). We show that boundary perceptions impact the availability and attractiveness of different identity options, including identification with Quebec, the country of origin, and Canada. First, while perceptions of ascriptive boundaries to Quebec push first- and second-generation immigrants away from Quebec identity, the reactive effect of strengthening identification with the country of origin and Canada is limited. Second, although the second generation perceives Quebec boundaries as more ascriptive than the first generation, it is not more strongly impacted by their boundary perceptions in their identifications. Third, perceptions of attainable boundaries promote all three national identifications, but only for the first generation. Finally, we demonstrate that attention to boundary perceptions adds important explanatory leverage beyond the impact that discrimination has on national identifications.

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)0.002
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.703
Threshold uncertainty score0.851

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.067
GPT teacher head0.436
Teacher spread0.369 · 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 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

Citations2
Published2024
Admission routes2
Has abstractyes

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