Analysis of the Development and Countermeasures of the Street Stall Economy with Chinese Characteristics
Bibliographic record
Abstract
The spread of COVID-19 has impeded China's economic development, and the street stall economy has significant implications for the economic development. Since Premier Li Keqiang voiced his support for the development of the street stall economy, it then has swept the nation and captured the public's attention. However, some academics have criticized the street stall economy due to its inherent shortcomings. This paper concentrates on the origin and development status of China's street stall economy, as well as its characteristics and existing problems. In addition, the paper examines the management of street stall economies in Korea and the Netherlands in order to draw on relevant and valuable experience, and concludes by proposing countermeasures for the current development of the stall economy in China. Standardizing the administration of the stall economy in China and promoting its healthy and sustainable development can be greatly aided by adopting the best practices of other countries' stall economies and combining them with the Internet's way of thinking.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".