Reconstructing Social Segregation in Danwei: An Examination of High-Quality Education Resources’ Impact on Housing Prices in Nanjing, China
Bibliographic record
Abstract
This study investigates the impact of capitalizing educational resources on housing prices. As housing has gradually transitioned from a basic social right to a means of accumulating individual and familial wealth, it has emerged as a significant indicator of social stratification and has increasingly become a crucial tool for the intergenerational reproduction of social class. This paper takes Nanjing, China, as a case study and uses the geographically weighted regression model (GWR) and the hedonic pricing model (HPM) to investigate the impact of high-quality primary schools on housing prices. The results show that high-quality educational resources have become the most significant influencing factor on residential prices in Nanjing. The analysis in the mechanism section further indicates that the uneven distribution of educational resources in China is a continuation of the “danwei” system. Moreover, during the urbanization process, these high-quality educational resources are often leveraged by the government and developers, who see them as essential tools to attract investment and inflate housing prices. Therefore, the current overlap of the school district system and the marketization of housing in China not only intensifies residential segregation within the city, leading to severe residential inequality but also rebuilds social segregation within “danwei” and facilitates its reproduction.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".