A comparative analysis of environmental sustainability in G20 nations using a comprehensive framework
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Environmental Sustainability is pivotal among global concerns and refers to the prudent utilization of resources satisfying the present generation’s needs while preserving the comparable needs of future generations. This pioneering study develops and compares the ‘composite environmental sustainability index’ (CESI) for G20 nations from 1990 to 2022, using the OECD-based ‘principal component analysis’ (PCA) technique. The CESI incorporates sixteen indicators across five dimensions (water, air, natural resources, energy and waste, and biodiversity), grouped into three sub-indices aligned with nine SDGs. The CESI scores range from 1 (lowest sustainability) to 5 (highest). Results show that Saudi Arabia, South Korea, and the United States are the worst-performing countries, while Brazil, Canada, and Turkiye are the top-performers. Over the years, Germany and France have shown consistent improvement, whereas Indonesia, Turkiye, India, and China have declined. However, based on the 2022 rankings, Brazil, Germany, and France rank highest in environmental sustainability, while Saudi Arabia, China, and South Africa rank lowest. The analysis reveals that countries exhibiting decreasing trends are mostly emerging economies, while improvements are more common in advanced economies. This study offers a comprehensive overview of environmental sustainability in the G20 and provides insights for policymakers to identify critical indicators for the right sustainable policies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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