Bibliographic record
Abstract
1. Property rights in the Chinese economy: contours of the process of change Andrew G. Walder and Jean C. Oi Part I. Enterprise Ownership in Village Communities: 2. Collective enterprise and property rights in a Sichuan village: the rise and decline of managerial corporatism Gregory A. Ruf 3. Local institutions and the transformation of property rights in Southern Fujian Chih-Jou Jay Chen 4. The role of local government in creating property rights: a comparison of two townships in Northwest Yunnan Xiaolin Guo 5. The evolution of property rights in village enterprises: the case of Wuxi Kung James Kai-Sing Kung Part II. Rural Shareholding Reforms and Their Impact: 6. Shareholding cooperatives: a property rights analysis Eduard B. Vermeer 7. Local elites as officials and owners: shareholding and property rights in Daqiuzhuang Nan Lin and Chih-Jou Jay Chen 8. The regional evolution of ownership forms: shareholding cooperatives and rural industry in Shanghai and Wenzhou Susan H. Whiting Part III. The Transformation of Public Property in the Urban Economy: 9. Backyard profit centers: the private assets of public agencies Yi-Min Lin and Zhanxin Zhang 10. Bargained property rights: the case of China's high-technology sector Corinna-Barbara Francis 11. Producing property rights: strategies, networks, and efficiency in urban China's nonstate firms David L. Wank Notes Index.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".