Trade Globalization, Financial Globalization and Inequality Within South-East Europe and CIS Countries
Why this work is in the frame
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Bibliographic record
Abstract
This paper contributes to the empirical literature by investigating trade globalization and financial globalization as channels of inequality within South-East Europe and the Commonwealth of Independent States (CIS) countries from 1992 to 2007. In addition, the paper uses KOF (2010) index to measure the overall impact of globalization on income inequality in South-East Europe and the CIS countries. To overcome the limitations of the least squares dummy variables (LSDV) model, Parks method is used. The paper has two results. The first result is that both trade globalization and financial globalization deepen the income inequality within South-East Europe and the CIS countries. The second result is that the overall impact of globalization have adverse effect on inequality within South-East Europe and CIS countries from 1992 to 2007. These results support the hypothesis that globalization widens the income inequality within countries.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| 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 it