Religions of Latino Immigrants in Canada: The Demographic Landscape of Religious Denominations
Bibliographic record
Abstract
ensus data, this paper focuses on the demographic landscape of religious denominations present in the Latino immigrant population of Canada aged 15 years old and over. Census respondents born in 19 Spanish and Portuguese-speaking countries of Latin America constituted the target population of the study. The data reveal a strong pattern of increasing intra-Christian group diversity. While Roman Catholics dominate this landscape (48%), there have been significant shifts between 2001 and 2021. A declining share of Roman Catholic adherents has been accompanied by greater numbers of immigrants reporting being unaffiliated with any religious group and/or expressing secular views on religion (23% in 2021). Many Latinos also reported being affiliated with "Renewalist" and "Mainline" Protestant denominations (21% in 2021). Females were majorities in denominational groups while males were the majority in the unaffiliated group. Most members of the denominational groups were found to be residentially concentrated in the provinces of Ontario and Quebec. Recent immigrants arriving in Canada were more visible among adherents of Non-Christian religions and the Unaffiliated group. Immigrants from Southern cone countries and Mexicans were over-represented among Roman Catholics, Central Americans among "Renewalist" faiths, Argentinians among the Jewish faith and Brazilians among adherents to "Mainline" Protestant faiths as well as Non-Christian faiths. Putting together all census findings, the 2021 census data suggests that there are significant religious polarizations currently taking place in the Latino immigrant population of Canada. The polarizations present in male and female adherents were effectively visualized through biplots generated by principal components multivariate analysis of the census data.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".