State-Led Urbanization in China: Skyscrapers, Land Revenue and “Concentrated Villages”
Bibliographic record
Abstract
Abstract This article examines the rationale behind municipal and local governments' pursuance of urbanization, and the political and socio-economic implications of the policy to move villagers from their farmland into apartment blocks in high-density resettlement areas, or “concentrated villages.” It provides evidence of an increasing reliance by municipal and local governments on land revenues and the financing of urban infrastructure by the governments' land-leasing income. Following their relocation to apartment blocks, villagers complain that their incomes fall but their expenditures rise. Moreover, although they cede rights to the use of their farmland to the government, they are not given access to the state-provided social welfare to which urban residents are entitled. The paltry compensation which they receive for their land is insufficient to sustain them. Displaced or landless peasants are emerging as a distinctly disadvantaged societal group, deprived of the long-term security of either farmland or social welfare. The question of whether or not rural land rights should be freely traded is not as crucial to the future livelihoods of landless peasants as allowing them access to the full range of social welfare afforded to urban residents.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".