Do the NMS-10 Develop Sustainably in the EU? A Kuznets Curve Approach
Bibliographic record
Abstract
Research background: Sustainable development with its three dimensions (economic, social, and ecological) is of key importance to the existence of human civilization. Sustainability is a complex category and in this research, each of its components is analyzed separately and in connection with others. Economic stability is related to the level of real income per capita, indicating the standard of living of a nation; social resilience is shown by income inequality, and environmental sustainability is expressed by the amount of greenhouse gas emissions per person. Purpose of the article: The focus is on the empirical analysis of the nexuses between income inequality, environmental quality, and purchasing power with a view to sustainability in 10 European Union member countries from Central and Eastern Europe, known as the NMS-10. To achieve its purpose, the study derives the original and ecological Kuznets curve for the NMS-10 as a group. The links between income inequality and living standard, on the one hand, and environmental degradation and living standard, on the other hand, are estimated. Methods: The research methodology includes two autoregressions with distributed lag (ARDL) with annual data from Eurostat and Transparency International for the period 2007–2020. Findings & Value added: The obtained empirical results indicate a long-term N-shaped relationship between income inequality and purchasing power in the NMS-10, while living standard affects the quality of the environment in NMS-10 neither in the long term nor in the short term.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".