Secularization and the Wider Gap in Values and Personal Religiosity Between the Religious and Nonreligious
Bibliographic record
Abstract
Increasing proportions of religious nonaffiliation characterize most Western societies, although the periods over which these increases have occurred and the speed in which they happen do vary. Consequently, some nations now have larger unaffiliated groups and others much smaller ones. What is less well known is if, in areas where unaffiliated groups are larger, the religious “nones” have become more distinct from the actively religious in their attitudes and behavior. In contexts of advanced secularization, to what extent is the gap greater between the actively religious and the nonreligious when it comes to their views on family life and reproduction, for example? In regards to their levels of religiosity and spirituality in their private lives? Are the unaffiliated more liberal in their attitudes and less religious in their private life? This article sheds light on these questions by analyzing data from over 200 North American, European, and Oceanic country subregions included in the 2008 International Social Survey Programme. With hierarchical linear models, I find that, in areas where the unaffiliated form a larger proportion of the population, the differences between the actively religious and the unaffiliated in family values and personal religiosity tend to be greater.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".