Shock Therapy versus Gradualism: The Central Eastern Europe (CEE) and East Asia Compared-A Review of Literature
Bibliographic record
Abstract
This paper reviews a numbers of policy measures taken by the governments in different countries from CEE to East Asia. The findings suggest that despite a number of discrepancies in the economic transition path and policies to support private sector development and SMEs from country to country, there are two distinct models: The Central and Eastern European “shock therapy” approach and the East Asian “gradualism” approach. The findings also highlight that regardless of the political and cultural context, in the early stage of economic transition process where institutional support and market conditions are not apparent, the state and public sectors play key roles. Despite of different levels of interventions, governments from those countries have taken some institutional measures in encouraging the development of private sector and capital formation, and enabling political flexibility and economic structural flexibility for the development of economic transition from centrally planned to market oriented economy. It is important to emphasize that no matter how those inventions are, but how the state can support economic transition and private sector development through political shifts and economic interventions. It could be concluded that the state has significant importance in encouraging capital formation and capitalist industrialization in CEE and East Asian countries
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".