The effects of labour migration on rural household production in inland China: Do landform conditions matter?
Bibliographic record
Abstract
Abstract The large‐scale rural to urban migration, generating sizable remittances, is often considered as an important means to help reduce poverty in rural China. However, penury is still stubbornly haunting the mountainous rural areas of inland China where numerous rural–urban migrants originate. Neglected in the current literature, the landform conditions are vital to explain the diverse effects of labour migration on rural household production in China. By adopting a revised simultaneous equation model, this study explores empirically how variations in regional landform conditions configure the effect of labour migration on rural household production using the data from our 2013 survey of migration intentions among rural labourers in China. The results show that remittances exert a substitution effect on agricultural production of rural households in the mountainous areas but have a promotive effect in the plain and hilly areas. Labour cutback imposes a less negative influence on agricultural production of rural households residing in the plain and hilly areas than in the mountainous areas. The effects of remittances and labour cutback on nonagricultural production of rural households are positive and negative, respectively, although these effects are insensitive to the variation in landform conditions. As a consequence, local wage level of rural households is more difficult to be improved by labour migration in the mountainous areas. Therefore, it is likely to lead to excessive labour migration and poverty trap.
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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 | 0.000 | 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 | 0.001 | 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".