Bibliographic record
Abstract
Communities with large concentrations of migrants, who often live in makeshift and illegal housing, have been common on the margins of large cities in China since the 1980s. Why do so-called "urban villages" persist and even flourish despite repeated government crackdowns? By addressing this question, this article sheds light on a subtle dynamic of city making that has not been fully appreciated by scholarly literature and media reports that have focused on large-scale demolition and eviction in China's rapid urbanization. Drawing from my two years of field research in Hua village, a community on Beijing's fringes in line for land expropriation, I explore how multilateral negotiations between local residents (villagers), migrant tenants, the village committee, and municipal government led to a cyclical movement of temporary housing construction, demolition, and extension. The dynamics of recurring demolishment and reconstruction engendered spaces of suspension, which enabled migrants to enter the urban economy at a low cost. Such spaces, however, offered no formal protection or basis for developing lasting social relations, and always faced the prospect of being demolished, but nevertheless were constantly available and even expanding.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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".