Urban Residents’ Religious Beliefs and Influencing Factors on Christianity in Wuhan, China
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we conducted an empirical analysis of the reasons for belief in Christianity in Wuhan, China. The data in this paper is from Chinese Urban Research Center for Ethnic and Religious Affairs Management, collected in 2015. We focus on the group characteristics of Christians in urban areas, and its influencing factors. It is found that the Christians in Wuhan are typically older, female, and less educated. Other patterns we have found include powerful influence by family members and friends, pragmatic reasons for following Christianity, family parties as a common way of religious assembly, and discretional admission and exit. Logistic regression is employed here to analyze the determinants of Christian belief. Gender, age, marital status, average annual income, education degree, and health conditions have significant effects on believing in Christianity.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it