Bibliographic record
Abstract
The relaxation of state direct control on the economy after 1984 stimulated China’s economic development greatly. In 1988, China had an “extraordinary development speed, oversized investment and a too fast-growing consumption fund.” The industrial gross output value above township level grew at a rate of 17.7 percent. The total social investment in fixed assets increased from 379.2 billion yuan in 1987 to 475.4 billion yuan in 1988, an increment of 25 percent. The high-speed expansion brought serious inflation. Although in October 1988, the CPCCC decided to “govern, reorganize and reform” the over-heated economy and started to reduce the money supply, the prices still continued to rise rapidly. There were four large-scale panic purchasing rushes and the overall level of annual retail price rose by 18.5 percent in 1988. In the first quarter of 1989, the overall retail price rose by 27 percent, compared to the same period of the previous year ( Chinese Price Statistics Yearbook 1990, p. 3 and 11). The inflation caused a rather short supply of producer goods. Many TVEs suspended their production because of lack of raw materials and energy. “In January and February 1989, electricity was unable to meet the demand. In some regions there was no electricity during daytime at all and electricity came only after 10 o’clock in the evening. Some supplied electricity four days and stopped three days each week. Self-generated electricity was also difficult because it was hard to buy oil, and even coal was seriously short” (Zhang, 1990, p. 349). These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.030 | 0.004 |
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".