MétaCan
Menu
Back to cohort
Record W2885296185 · doi:10.1111/nana.12429

Religiosity or racism? The bases of opposition to religious accommodation in Quebec

2018· article· en· W2885296185 on OpenAlexaffabout
Yannick Dufresne, Anja Kilibarda, André Blais, Alexis Bibeau

Bibliographic record

VenueNations and Nationalism · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicMulticulturalism, Politics, Migration, Gender
Canadian institutionsUniversité de MontréalUniversité Laval
Fundersnot available
KeywordsOpposition (politics)AntipathyMulticulturalismEthnocentrismReligiosityAccommodationImmigrationSociologyPopulationGender studiesRacismPolitical scienceLawAnthropologyPsychologyPoliticsDemography

Abstract

fetched live from OpenAlex

Abstract Though Canada is internationally lauded for the success of its multiculturalism policies, debates about immigrant integration have arisen in recent years. These debates have turned on the extent to which religion should be accommodated in the public sphere. They have also been disproportionately concentrated in the French‐speaking province of Quebec. This paper asks whether this disproportionality is due to the Quebec population being particularly unfavourable to religious accommodation and, if so, whether this disfavour is grounded in racial antipathy toward newcomers or in the province's unique religious history. The findings show that while opposition to religious accommodation is higher in Quebec, and higher among francophones, it is rooted more in the low level of religiosity of the francophone population than in racial animus. These results emphasise the importance of correctly conceptualising distinctions between ethnocentric and culturally based sources of group conflict in multicultural settings such as Canada.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.240

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.003
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.105
GPT teacher head0.429
Teacher spread0.323 · 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 designObservational
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
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueNations and NationalismSame topicMulticulturalism, Politics, Migration, GenderFrench-language works237,207