Continuing the Conversation on Canada: Changing Patterns of Religious Service Attendance
Bibliographic record
Abstract
David Eagle's article on changing patterns of religious service attendance appeared in the March 2011 issue of Journal for the Scientific Study of Religion. He presented a comprehensive analysis of three data sets that allow social scientists to estimate the rate of religious service attendance in Canada: Project Canada Survey (PCS), the General Social Survey (GSS), and the Canadian Survey of Giving, Volunteering, and Participating (GSGVP). Reginald Bibby initiated the PCS in 1975, 10 years before Statistics Canada began conducting the GSS in 1985, and 22 years before the GSGVP began in 1997. He comments on the Eagle article, cautions scholars to be mindful of important methodological differences across samples, and offers his own analysis of trends in religious service attendance.
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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 | 0.013 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.017 | 0.011 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.009 | 0.014 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".