Research on the Balance Point between Government Intervention and the Free Market
Bibliographic record
Abstract
The changing global economic landscape has once again made the relationship between government intervention and the free market a hot topic in economic research. This paper systematically reviews the theories of the two to analyze the dialectical relationship between them, and studies the evolution process and effectiveness of the relationship between the government and the market under different economic systems by using a combination of literature analysis, case comparison, and quantitative analysis. The article first reviews the theoretical development process from classical liberalism to Keynesianism and then to neoliberalism, then dissects the dual predicaments of market failure and government failure, and also explores the reasonable boundaries of government intervention in areas such as infrastructure construction, externality governance, macroeconomic stability, and income redistribution. Finally, by comparing different models in China, the United States, and the Nordic countries, practical approaches to finding the balance point between government and market are presented. The research shows that the ideal balance point is not fixed but is a process of dynamic adjustment in accordance with the stage of economic development, technological progress, and social demand. To build a good interaction mechanism between an effective market and an active government, the intensity and means of intervention should be flexibly adjusted in accordance with specific national conditions to achieve the best combination of economic efficiency and social equity.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.012 |
| Scholarly communication | 0.004 | 0.010 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".