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Record W4403567035 · doi:10.1353/ces.2024.a939615

Public Attitudes Toward Immigrants and Immigration in Smaller Canadian Communities

2024· article· en· W4403567035 on OpenAlexvenueaboutno aff
Victoria M. Esses, Alina Sutter, Leah Hamilton, Antoine Bilodeau, Paolo Aldrin Palma, Aurélie Lacassagne, Keith Neuman, Danielle Gaucher

Bibliographic record

VenueCanadian ethnic studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationPublic opinionDemographic economicsPolitical scienceEthnologySociologyPoliticsLawEconomics

Abstract

fetched live from OpenAlex

Abstract: Canadian immigration programs are increasingly emphasizing regionalization in order to contribute to the population base of smaller Canadian communities and to address local labour market needs. Despite frequent Canadian national surveys of public attitudes toward immigrants and immigration, however, little is known about the warmth of the welcome presented to immigrants in regions outside of the large metropolises. The current study involved a representative survey of attitudes toward immigrants and immigration in eleven smaller communities across Canada, including Kamloops (BC), Wood Buffalo (AB), Prince Albert (SK), Brandon (MB), Thunder Bay (ON), Greater Sudbury (ON), Saint-Hyacinthe (QC), Bathurst (NB), Charlottetown (PEI), Cape Breton (NS), and St. John's (NL). The study also examined the extent to which individual demographic characteristics and two community variables – the size of the community and the immigrant share of the community population – predicted these attitudes. While there were differences between the surveyed communities, overall, residents of these communities were relatively satisfied with Canada's immigration levels, were quite willing to believe that refugee claimants are "real" refugees and that the Federal Government has control over who can immigrate, and supported bringing in immigrants who have the work skills that the country needs. They were less sure of the integration of immigrants into Canadian society in terms of adopting Canadian values. Younger, female, White and highly educated residents of these communities were more likely to hold positive immigration attitudes. Furthermore, immigrant respondents were more likely to hold positive attitudes toward immigration and less likely to believe that immigrants are not adopting Canadian values and that the government has lost control over who can immigrate. At the community level, residents in communities in which immigrants constitute a higher share of the population were more likely to express negative attitudes toward immigrants and immigration. Overall, the findings provide some optimism for the positive reception that immigrants are likely to receive in smaller Canadian communities. They also demonstrate, however, that attitudes in these communities are not uniform and provide information for community leaders and policy-makers about who is most likely to benefit from interventions to promote more positive attitudes. Résumé: Les programmes d'immigration canadiens mettent de plus en plus l'accent sur la régionalisation afin de contribuer à la base démographique des petites communautés canadiennes et de répondre aux besoins du marché du travail local. Malgré les fréquentes enquêtes nationales canadiennes sur les attitudes du public à l'égard des immigrants et de l'immigration, on sait peu de choses sur la chaleur de l'accueil réservé aux immigrants dans les régions situées en dehors des grandes métropoles. La présente étude a consisté en une enquête représentative des attitudes à l'égard des immigrants et de l'immigration dans onze petites collectivités du Canada, notamment Kamloops (BC), Wood Buffalo (AB), Prince Albert (SK), Brandon (MB), Thunder Bay (ON), le Grand Sudbury (ON), Saint-Hyacinthe (QC), Bathurst (NB), Charlottetown (IPE), Cape Breton (NÉ), et St John (TN&L). L'étude a également examiné dans quelle mesure les caractéristiques démographiques individuelles et deux variables communautaires - la taille de la collectivité et la proportion d'immigrants dans la population de la collectivité - permettaient de prédire ces attitudes. Bien qu'il y ait des différences entre les collectivités étudiées, dans l'ensemble, les résidents de ces communautés étaient relativement satisfaits des niveaux d'immigration du Canada, étaient tout à fait disposés à croire que les demandeurs d'asile sont de « vrais » réfugiés et que le gouvernement fédéral a le contrôle sur les personnes qui peuvent immigrer, et soutenaient l'arrivée d'immigrants qui ont les compétences professionnelles dont le pays a besoin. Ils étaient moins convaincus de l'intégration des immigrants dans la société canadienne en termes d'adoption des valeurs canadiennes. Les résidents de ces collectivités, plus jeunes, de sexe féminin, de race blanche et ayant un niveau d'éducation élevé, étaient plus susceptibles d'avoir une attitude positive à l'égard de l'immigration. En outre, les répondants immigrants étaient plus susceptibles d'avoir des attitudes positives à l'égard de l'immigration et moins susceptibles de croire que les immigrants n'adoptent pas les valeurs canadiennes et que le gouvernement a perdu le contrôle sur les personnes qui peuvent immigrer. Au niveau communautaire, les résidents des communautés dans lesquelles les immigrants constituent une part plus importante de la population étaient plus susceptibles d'exprimer des attitudes négatives à l'égard des immigrants et de l'immigration. Dans l'ensemble, les résultats permettent d'être optimiste quant à l'accueil positif que les immigrants sont susceptibles de recevoir dans les petites collectivités canadiennes. Ils démontrent également que les attitudes dans ces collectivités ne sont pas uniformes et fournissent des informations aux dirigeants communautaires et aux décideurs politiques sur les personnes les plus susceptibles de bénéficier d'interventions visant à promouvoir des attitudes plus positives.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.769
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.235
GPT teacher head0.355
Teacher spread0.120 · 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 designNot applicable
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".

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Citations0
Published2024
Admission routes2
Has abstractyes

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