The Study of Living Conditions and Perceived Needs for Social Security among Clergy in China: A Case Study of Guanzhong Qinling Area
Bibliographic record
Abstract
This study used quantitative and qualitative data collected in the Guanzhong Qinling area of China to examine living conditions and perceived needs for social security among men and women of the clergy. The survey finds that most respondent clergy are Buddhists. When the clergy have economic difficulties, their main types of support include self-support (28.8%), help from other believers (25.6%), and assistance from other community residents (18.4%). When the clergy are old, they tend to live alone (25%), receive institutional care from religious organizations (19%), and receive support from other believers (18%). When the clergy are ill, they will often select self-treatment (primarily the use of traditional Chinese medicine [25%], and spiritual healing [25%], including meditation, prayers, and psychotherapy) and receive treatment at hospitals (20%). The study found that the clergy perceived their needs for social security as either great (19.7%) or modest (36.5%). Very few clergy (10%) indicate the absence of social security needs. Most clergy believe that the key social security priorities should be medical care (34%), elderly care (29%), and charitable assistance (21%).
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".