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Record W4401463061 · doi:10.1353/ces.2024.a934428

Ethnicity and Trust: How Trustful are Chinese Canadians?

2024· article· en· W4401463061 on OpenAlexvenueaboutno aff
Cary Wu, Rex Wang

Bibliographic record

VenueCanadian ethnic studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicRacial and Ethnic Identity Research
Canadian institutionsnot available
Fundersnot available
KeywordsEthnic groupSociologyPolitical scienceAnthropology

Abstract

fetched live from OpenAlex

Abstract: Trust is not always lower among racial and ethnic minorities. The between-ethnicity differences in trust largely depend on the reference category. The within-ethnicity differences are often overlooked. In this study, we examine both social trust in others and political trust in governmental institutions among Chinese Canadians, one of the largest ethnic groups in Canada. We adopt a multidimensional comparative approach and analyze four major Chinese groups – Canadian-born Chinese, Mainland Chinese, Hong Kong Chinese, and Taiwan Chinese. Drawing on data from the Canadian Democracy Checkup Surveys (2020 and 2021), we show that Chinese Canadians stand out as one of the most trusting people in comparison to many other ethnic and racial groups. Specifically, overall, they possess a comparable social trust level to White Canadians and display higher political trust. However, their trust also varies based on birthplace. Hong Kong-born Chinese exhibit significantly lower social trust than White Canadians. Canadian-born and Mainland Chinese are politically more trusting as compared to Whites. Within the Chinese groups, the Hong Kong-born show the lowest social trust and trust in the federal government, while Mainland Chinese Canadians demonstrate the highest social trust. These trust patterns align well with birthplace origins, highlighting the importance of exploring the cultural roots of both social trust and political trust. Résumé: La confiance n'est pas toujours plus fragile parmi les minorités raciales et ethniques. Les différences entre les ethnies en matière de confiance dépendent largement de la catégorie de référence. Les différences au sein des ethnies sont souvent dérisoires. Dans cette étude, nous examinons à la fois la confiance sociale envers autrui et la confiance politique envers les institutions gouvernementales parmi les canadiens d'origine chinoise, l'un des plus grands groupes ethniques du Canada. Nous adoptons une approche comparative multidimensionnelle et analysons quatre principaux groupes chinois - les chinois nés au Canada, les chinois de la métropole, les chinois de Hong Kong et les chinois de Taïwan. En nous basant sur les données des enquêtes Bilan de la démocratie canadienne (2020 et 2021), nous montrons que les canadiens d'origine chinoise se distinguent comme l'un des peuples les plus confiants par rapport à de nombreux autres groupes ethniques et raciaux. Plus précisément, dans l'ensemble, ils possèdent un niveau de confiance sociale comparable à celui des canadiens blancs et affichent une confiance politique plus élevée. Cependant, leur confiance varie également en fonction du lieu de naissance. Les chinois nés à Hong Kong montrent une confiance sociale significativement plus faible que les canadiens blancs. Les chinois nés au Canada et les chinois de la métropole ont une confiance politique plus élevée par rapport aux canadiens blancs. Au sein des groupes chinois, les chinois nés à Hong Kong démontrent la confiance sociale et la confiance dans le gouvernement fédéral les plus faibles, tandis que les chinois de la métropole assument une confiance sociale plus élevée. Ces schémas de confiance correspondent bien aux origines géographiques, soulignant l'importance d'explorer les racines culturelles tant de la confiance sociale que de la confiance politique.

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)0.002
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 score0.575
Threshold uncertainty score0.708

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.149
GPT teacher head0.435
Teacher spread0.286 · 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".

Quick stats

Citations2
Published2024
Admission routes2
Has abstractyes

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