Bibliographic record
Abstract
Nearly thirty years after the fall of the Soviet Union, debates over paths to market liberalization have produced numerous studies across the social sciences. This groundbreaking work from Oleh Havrylyshyn offers a new perspective. Havrylyshyn, a former official in the post-independence Ukrainian government, provides a unique, primary source account of the people and problems at the heart of economic transitions. Grounded in three decades of data, along with experiential research gleaned from nearly thirty countries, this book contains the most up-to-date assessment of economic transitions in post-communist regions. It critically examines questions of gradual versus radical reforms, the relationship between democracy and market liberalization, and how history, individual personalities, and foreign influence determined political choices. Thorough research and accessible style make this work a valuable resource for students and specialists of economics, political science, and history as well as readers generally interested in international studies, government, and business.
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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 | 0.006 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.042 | 0.008 |
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".