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Record W4282935862 · doi:10.1111/cars.12385

Why is trust lower in Quebec? A cultural explanation

2022· article· en· W4282935862 on OpenAlexaffabout
Cary Wu, Andrew Dawson

Bibliographic record

VenueCanadian Review of Sociology/Revue canadienne de sociologie · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Capital and Networks
Canadian institutionsYork University
Fundersnot available
KeywordsModernization theoryHumanitiesCultural revolutionPolitical scienceEthnologySociologyPhilosophyLaw

Abstract

fetched live from OpenAlex

In this article, we provide a cultural explanation of a long-standing trust puzzle in Canada-Quebecers trust much less than their fellow Canadians. Specifically, we develop a novel approach to empirically assess the historical influence of the Catholic Church, using the Quiet Revolution (a period of abrupt modernization in Quebec) as a natural experiment. We find that older cohorts socialized prior to the Quiet Revolution are significantly less trusting-a distinctive trend that is most pronounced among Catholics. Conversely, in the rest of Canada older cohorts are more trusting, following the trend commonly found in other countries. Furthermore, measures of both religious beliefs and modernization account for a large part of the birth cohort trust gap in Quebec. The findings suggest that low trust in Quebec is rooted in the province's Catholic cultural heritage, but that the legacy of the Quiet Revolution is gradually changing the trust culture.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.031
Threshold uncertainty score0.221

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0050.003
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.048
GPT teacher head0.294
Teacher spread0.246 · 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 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

Citations5
Published2022
Admission routes2
Has abstractyes

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