1 CHINA’S ECONOMIC PERFORMANCE: HOW FAST HAS GDP GROWN; HOW BIG IS IT COMPARED WITH THE USA?*
Bibliographic record
Abstract
In the past two decades, China has been the world’s fastest growing economy. In 1982, it overtook Germany as the world’s third largest economy; in 1992, overtook Japan as the second biggest economy. In 2003 its GDP was about 73 per cent of that in the USA. It seems likely that it will overtake the USA, and become number one before 2020. The above estimates were made by converting China’s GDP and that of the other countries in their national currencies, using a PPP (purchasing power parity) converter, rather than the exchange rate. As the Chinese currency is greatly undervalued, the difference between PPP and exchange rate conversion is unusually large. With exchange rate conversion, Chinese GDP appears to have been only 15 per cent of that in the USA in 2003. Very frequently, there is significant error in assessing China’s comparative performance when such exchange rate comparisons are used. This happens in journalism, in political discourse and also amongst some economists who regard Japan as the second largest economy although it now has a GDP less than half the Chinese. In 2003, German GDP was about a quarter of that in China. Estimation of the PPP converter for China is described in Maddison (1998)
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".