Bibliographic record
Abstract
This book is unique in covering all important topics of the Chinese economy in depth but written in a language understandable to the layman and yet challenging to the expert. Beginning with entrepreneurship that propels the dynamic economic changes in China today, the book is organized into four broad parts to discuss China's economic development, to analyze significant economic issues, to recommend economic policies and to comment on the timely economic issues in the American economy for comparison. Unlike a textbook, the discussion is original and thought-provoking. It is written by a most distinguished economist who has studied the Chinese economy for thirty years, after making breathtaking contributions to the fields of econometrics, applied economics and dynamic economics and serving as a major adviser to the government of Taiwan during its period of rapid development in the 1960s and 1970s. In the last thirty years, the author has served as a major adviser to the government of China on economic reform and important economic policies and cooperated with the Ministry of Education to introduce and promote the development of modern economics in China, including training hundreds of economists in China and placing many graduate students to pursue a doctoral degrees in economics in leading universities in the US and Canada. These graduates now plays pivotal roles in China and in the US in academics, business or government institutions. The essays, a culmination of the author's expertise in China over five decades, are being widely read in China. When the author became professor emeritus at Princeton, the University named the Econometric Research Program as the Gregory C Chow Econometric Research Program in his honor.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".