Nankai school: The experience of adapting economics to Chinese conditions in the 1920s–1930s
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Bibliographic record
Abstract
Using the example of the activities of the Nankai Institute of Economics in the second quarter of the twentieth century, the article analyses the problem of adapting Western economic theories to the study of the Chinese economy. At the heart of the program of sinicization of economic research and education proposed by the Nankai school was the work of collecting and systematising reliable information on the Chinese economy. In the second half of the 1920s, Nankai University became a leader in China in conducting socio-economic surveys, compiling index numbers of prices, studying selected industries and rural regions. The founders of the Nankai school. He Lian and Fang Xianting were educated in economics in the United States; up until the late 1940s, the Nankai Institute of Economics was highly dependent on American grant support. This did not prevent them from setting the objectives of “knowing China” and “serving China” by combining foreign theories and methods with an understanding of the real economic situation based on reliable quantitative data. The task of “localization” of economics stimulated writing of pioneering university textbooks that explained general theoretical concepts through Chinese examples. Focus on solving China’s problems led the economists to abandon copying ready-made foreign prescriptions. During the two decades of activity in the Republican period the Nankai school made major achievements in collecting factual material on Chinese economy and adapting courses, its legacy has become an important starting point of the contemporary policy of sinicization of economics in the PRC.
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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 | 0.001 | 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 | 0.001 |
| 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 it