Bibliographic record
Abstract
Australia is one of the most multicultural countries in the world, with more than a quarter of the population born overseas. In recent years there have been debates around the best approach to ethnic composition of churches in a context of migration and multiculturalism. Using data from 1,344 churches who participated in the 2016 National Church Life Survey, this paper explores the relationships between ethnic diversity (operationalised as diversity in the countries of birth of attenders) and congregational health and vitality, in terms of religiousness of the congregation, positive evaluation of worship services, bonding within the congregation, visionary leadership and innovativeness, the proportion of the congregation who are youth and young adults, the proportion who are newcomers to church, and growth in the size of the church. Ethnic diversity contributed positively to religiousness, the presence of young people and positive worship evaluation, and negatively to bonding. Analyses were also conducted separately for Anglican, Catholic, Uniting, Baptist and Lutheran churches, indicating that ethnic diversity is particularly important for understanding vitality in Catholic parishes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".