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Increase or Decrease? The Impact of the International Migratory Event on Immigrant Religious Participation

2008· article· en· W2122610059 on OpenAlexaboutno aff
Phillip Connor

Bibliographic record

VenueJournal for the Scientific Study of Religion · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Society, and Development
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationReligiosityDemographic economicsEvent (particle physics)SociologyWork (physics)Political scienceSocial psychologyPsychologyEconomicsLaw

Abstract

fetched live from OpenAlex

Immigrant religiosity has recently become a hot topic both in academia and in the public arena. For years, a debate has existed as to whether there is an increase or decrease of immigrant religious participation surrounding the migratory event. Some argue that the act of migration spurs an increase in immigrant religious participation, while others contend that migration is a disruptive event and decreases immigrant religious participation. In addition to contextual factors, a number of micro‐level factors may explain this change in religious participation: sex, family composition, religious affiliation, and employment status. This article uses longitudinal data from Quebec, Canada surveying nearly 1,000 immigrants during the 1990s. Results indicate that immigrant religious participation decreases substantially as compared to the average level of religious participation among the same immigrants prior to their migration. Besides religious affiliation, most of the micro‐level factors hypothesized to explain this change in religious participation prove statistically insignificant. The lack of significant results for micro‐level factors points to environmental factors that may be at work.

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)0.005
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 score0.123
Threshold uncertainty score0.244

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.044
GPT teacher head0.365
Teacher spread0.321 · 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

Citations88
Published2008
Admission routes1
Has abstractyes

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