Transformation of the Socio-economic Model of China in the Context of a Pandemic
Bibliographic record
Abstract
The article explored the impact of the pandemic and the ensuing quarantine on the Chinese economy and its attractiveness to foreign investors. At the end of the first quarter of 2020, there was a sharp decline in almost all Chinese socio-economic indicators. The year to year decline in GDP, retail sales and exports by 6.8%, 19% and 11.4% respectively, looked especially dramatic. Against that negative background, the question arose, firstly, about the urgent launch of the program to stimulate the economy and, secondly, the need to develop and implement a new model of economic development for the PRC. After a slight delay, the Chinese authorities launched a series of fiscal and monetary measures aimed at supporting the national economy, including: reducing or canceling various payments to the budget (taxes, social security contributions, etc.), reducing loan rates, the ratio of reserve requirements, direct and indirect payments to citizens, etc. Thanks to government support measures, the main socio-economic indicators for the third quarter of 2020 showed growth, although less than Beijing would like. The lack of private consumption by Chinese households remains the main problem. Implementing support measures, the Chinese authorities have unveiled a new strategy for economic development, called «dual circulation», which aims to stimulate domestic private consumption. The authors come to the conclusion that, firstly, despite external and internal challenges, China, as a whole, will be able to achieve the indicative indicators laid down in the 13th five-year plan for the social and economic development of the PRC for 2016-2020. Secondly, the tasks of complete elimination of poverty in the country will be successfully solved and plans for the construction of a society of «moderately prosperous society» will be implemented. Thirdly, China in the short and medium term will retain its attractiveness for foreign investment, but not within the framework of the «investment in the production of goods for export» scheme, but within the framework of «investment in the production of goods for domestic consumption».
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".