Bibliographic record
Abstract
117 A ruption. For instance, corruption scores for Armenia is 0.31 and 0 for Moldova and Ukraine, while it is around two for the U.S. and Canada. On average, the CIS countries are assigned a corruption score of –0.078 when an average score for the OECD countries is + 1.76 and + 0.07 for the neighboring Eastern Europe and Baltic States. The rule of law has an estimate of –0.013 for the CIS countries, which is very weak in comparison to the score of + 1.51 for the OECD countries. The two measures indicate that the respect of citizens and the state for the institutions that govern economic and social interactions among them is very weak in the CIS countries. The same is true of other indicators of “ruling justly,” with especially wide difference of voice and accountability estimate between the CIS and OECD countries. Thus, there is much room to improve the process by which the government is selected and the capacity by which the state provides public goods and services. Overall, all of the CIS countries need to focus on governance and institutional reforms not only to be competitive in the MCA program in future rounds but also to assure a better quality of life for their citizens. Unfortunately, unlike “investing in people” and some of the “economic freedom” related reforms, there is no quick fix for “ruling justly.” It takes longer time, political commitment and will to initiate governance and institutional reforms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".