Marginal Religious Affiliates in Canada: Little Reason to Expect Increased Church Involvement
Bibliographic record
Abstract
Dans cette document, j'utilise les données des entrevues avec vingt et un filiales religieuse au Canada qui assistent aux offices religieux surtout pour des fêtes religieuses et les rites de passage, en demandent pourquoi ils ont cessé de fréquenter sur une base régulière, pourquoi ils continuent à fréquenter une ou deux fois par année, et expriment‐ils tout intérêt à être plus impliqués dans leur groupe religieux, et si oui, quels facteurs pourraient conduire à une implication accrue. Contrairement à Reginald Bibby, et d'autres sources qui expliquent les modèles d'implication aux églises par insistant sur le côté de l'offre du marché religieux, je soutiens que nous devrions nous concentrer d'avantage sur le côté de la demande.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".