The influence of renewable energy and economic freedom aspects on ecological sustainability in the <scp>G7</scp> countries
Bibliographic record
Abstract
Abstract With the exemption of Canada, the G‐7 countries have largely flourished at the detriment of their ecological sustainability bearing in mind that these countries' have remained ecologically deficit for several decades. Given the potential effect of environmental degradation associated with the trend of ecological deficit of these countries, this study attempts to understand the contribution of renewable energy dimensions through the measure of renewable energy efficiency and renewable energy use alongside evaluating the role of the four main aspects of economic freedom. By using empirical tools, the findings revealed that renewable energy aspects contribute to environmental sustainability among the countries through a significant mitigation of their ecological footprint. Importantly, the aspects of economic freedom, that is, government size, legal system and property rights, freedom to trade internationally, and regulation hampers environmental sustainability by increasing the countries ecological footprint. The elasticity of impact of this dimension of economic freedom is in the range of 0.19–0.21 at 1% statistically significant level. However, population of these countries does not show a detrimental effect, rather the finding revealed that population improves environmental quality by a statistically significant degree. Given these revelations, there are deducible policy take home from this study.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".