Industrial Policy, Industrialization and Economic Development of Kyrgyzstan
Bibliographic record
Abstract
Kyrgyzstan pursued the market-based reform in the process of transition. Based on the literature review and statistical data covering 1990s-2010s, this paper explains economic development and industrialization of Kyrgyzstan in its transition process. The government of Kyrgyzstan promoted several priority sectors including agriculture, mining, energy, garment and agro-processing industry by industrial policy measures. There is little evidence that Kyrgyzstan has a comparative advantage in agriculture. Gold mining is expected to be depleted by 2020s. Kyrgyzstan appears to be competitive in hydroelectricity generation and agro-processing industry. Although the garment industry has led the manufacturing sector, it has been losing the foreign investors’ attention. Therefore, it is necessary for Kyrgyzstan to think of the next stage of economic development with the new industrial-led economic development strategy. The government of Kyrgyzstan may benefit from promoting value-added industries. For such value-added industries to develop, strengthening infrastructure particularly in human capital would be critical.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".