Chinese Consumption Structure: Impacts of the Global Financial Crisis and Contem Measures to Take
Bibliographic record
Abstract
The global financial crisis sprang from the Wall street have swept all the world, the financial markets and real economies in developed countries are badly affected. As the world's third largest economy, china can not sit idly. Affected by the crisis, in 2008 China's economic growth began to decline from the peak and declined quarter by quarter, the annual growth rate was 8% of the troika that promtes economic growth, exports have declined as the overall demand of USA hampered, and the long period of high investment that have no room to grow, only the relative shortage of domestic demand have the room for improvement. The Chinese government has recognized the importance of the domestic demand for the economic development, and rapidly adjust the macroeconomic policy, from the "double anti-"to maintain growth, expand domestic demand, adjust the structure, and introduced a 4 trillion supporting economic stimulus plan and the "Top Ten Industry Promotion Plan". In the context of the financial crisis, what will the chinese consumption structure change ?and what can we do to make the government's economic stimulus policy really improve the country`s consumption structure, and thus to promote the ecnomic development ? these issues become particularly important.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".