A Research on Potential Land-Deprived Peasants’ Intention on the Old-Age Care Issue in the Urban Planning Area: A Case Study Based on 53 Peasant Groups in Daxing Town of Ya’an City
Bibliographic record
Abstract
With the speedy development of urbanization in China, most of people in China, including some of developed countries, have increasingly and closely concerned about the old-age care issue of the potential land-deprived peasants in urban planning area of China. By analyzing the peasants’ questionnaires, the paper focused on the old-age care issue of potential land-deprived peasants and formed the conclusions and offered some suggestions on the urban planning, urban construction, urban management and the aftercare of land-deprived peasants. The investigations about the potential land-deprived peasants’ intention on the old-age care issue were carried out by means of 101 households’ sampling survey in 53 peasant groups of 8 villages of Ya’an city. Though the statistics analysis of SPSS software, results indicated that the traditional old-age care ways provided by their sons and daughters have stepped into the predicament, and the potential land-deprived peasants urgently need to develop socialized old-age care mode. At the same time, results also indicated there are several key influencing factors on the intention of the old-age care of the potential land-deprived peasants such as peasants’ cultural quality, the absence of government and peasants’ traditional values.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".