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Record W2052933180 · doi:10.1353/ces.2010.0040

“Canadian” as National Ethnic Origin: Trends and Implications

2010· article· en· W2052933180 on OpenAlexvenueaboutno aff
Sharon M. Lee, Barry Edmonston

Bibliographic record

VenueCanadian ethnic studies · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsEthnic groupResidenceMicrodata (statistics)ImmigrationCensusGeographyMetropolitan areaDemographyLogistic regressionEthnologySociologyPopulationAnthropologyArchaeology

Abstract

fetched live from OpenAlex

This paper examines the emergence of “Canadian” as a national ethnic origin by conducting: (i) a trend analysis on identifying as “Canadian” using microdata from the 1991, 1996, and 2001 Censuses of Canada; and (ii) descriptive and multivariate analyses to examine characteristics associated with identifying as “Canadian.” The trend analysis reveals large and statistically significant increases in identification as “Canadian.” Several factors, including birth in Canada, French language background, Quebec residence, lower education, younger age, and non-metropolitan residence are associated with identifying as “Canadian.” Estimating logistic regression models for three language groups—Anglophones, Francophones, and English and French bilinguals—for each census show similar (e.g., education, age) and different (e.g., religion, province) effects of explanatory variables for language groups and over time, and also confirm the important role of a French language background. By 2001, for example, Francophones were more than three times as likely as Anglophones to identify as “Canadian.” We discuss possible explanations for the findings, including “Canadian” ethnic identification as a reaction to increased immigration and different meanings of “Canadian” ethnicity for Anglophones and Francophones; several areas for future research; and implications of new national ethnic identities such as “Canadian” for studying ethnicity. Cet article porte sur l’émergence du terme « canadien » au sens d’origine ethnique nationale en menant : 1) une analyse de la tendance à s’identifier comme « canadien » à partir des micro-données fournies par les recensements du Canada de 1992, 1996 et 2001 et 2) des analyses descriptives à plusieurs variables pour étudier les caractéristiques de cette appartenance. L’analyse de la tendance révèle une augmentation importante et statistiquement significative du fait de s’identifier comme « canadien ». Plusieurs facteurs, dont le fait d’être né au Canada, de résider au Québec, de ne pas habiter dans une métropole, et un contexte de langue française, une éducation moins avancée ou un âge plus jeune sont liés à une « canadianité » identitaire. L’estimation des modèles de régression logistique pour les trois groupes linguistiques – Anglophones, Francophones et Bilingues anglais-français – montre que les effets des variables explicatives pour les groupes de langue sont semblables (comme dans le cas de l’éducation et de l’âge) ou différents (comme dans le cas de la religion et de la province) et qu’ils évoluent d’un recensement à l’autre. Elle confirme, par ailleurs, le rôle important du contexte français. En 2001, par exemple, il est trois fois plus probable que les Francophones s’identifieront comme « canadiens » que les Anglophones. Nous examinons les explications possibles de ces résultats, y inclus une ethnicité identitaire « canadienne » en réaction à une immigration en hausse et les différences de sens d’une « canadianité » ethnique chez les Anglophones et chez les Francophones, ainsi que plusieurs champs pour la recherche à venir et les implications de nouvelles identité ethniques nationales, comme la « canadienne », pour les études sur l’ethnicité.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.770
Threshold uncertainty score0.942

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.120
GPT teacher head0.435
Teacher spread0.315 · 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 designTheoretical or conceptual
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

Citations13
Published2010
Admission routes2
Has abstractyes

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