Rural‐to‐Urban Migration, Family Resilience, and Policy Framework for Social Support in China
Bibliographic record
Abstract
China's internal rural‐to‐urban migration has impacted the country in economic, social, and cultural terms. Despite the increasing number of families involved in migration, little is known about how migrant families as a unit adapt to new environments from rural to urban settings. Policy making needs to be informed to address migrant families' needs. This article investigates how Chinese families experience transitions resulting from migration, exploring their use of formal and informal support to achieve adaptation and the process of making evolving choices for their children. We begin with a brief introduction to the literature on family resilience and its relation to Chinese migrant families. Then we provided an analysis of Chinese social policies most central to the experiences of rural‐to‐urban migrant families. After a brief description of methodology, we present our findings starting with a migrant family story to provide an anchor for the following discussion on how current policies can impede or facilitate migrant families' resilience. Our conclusion is that lack of social support leaves migrant Chinese families vulnerable when coping with enormous social, cultural, and economic transformations. Family constitutes the basis of Chinese society; therefore, a policy framework on social support is important to support these families and foster family resilience.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 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".