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Record W2117909761 · doi:10.1177/000842980503400202

The future of non-Christian religions in Canada: Patterns of religious identification among recent immigrants and their second generation, 1981-2001

2005· article· en· W2117909761 on OpenAlexaffvenueabout
Peter Beyer

Bibliographic record

VenueStudies in Religion/Sciences Religieuses · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicReligion and Society Interactions
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsImmigrationPluralism (philosophy)ChristianityReligious pluralismDominance (genetics)Identification (biology)Ethnic groupReligious diversitySociologyReligious studiesPolitical scienceEthnologyLawAnthropologyEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

This paper addresses the question whether recent immigration to Canada from non-European and mostly non-Christian parts of the world is leading to increasing religious pluralism in Canada, rather than only enhanced ethno-cultural pluralism. Testing Reginald Bibby's hypothesis that, in spite of this immigration, Christianity will continue as the overwhelmingly dominant religious identification in Canada, this article analyzes data from the 1971-2001 decennial censuses. It finds that religious pluralism as measured by number and percent of adherents to major non-Christian religions is increasing and will likely continue to increase because of the composition of continuing immigration. There are, however, also countervailing trends that support continued Christian dominance as well as an increase in no religious identification. These trends include patterns in religious identification over time and the enigmatic effect of rising multiple ethnicity.

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)0.002
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 score0.024
Threshold uncertainty score0.176

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.329
Teacher spread0.301 · 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

Citations15
Published2005
Admission routes3
Has abstractyes

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