The role of energy intensity, green energy transition, and environmental policy stringency on environmental sustainability in G7 countries
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
Abstract The increase in energy intensity and energy depletion may lead to faster depletion of natural resources and increased environmental impacts. The green energy transition can improve environmental quality by reducing the pressure on natural resources and the carbon footprint. At this point, public environmental regulations are significant for environmental sustainability. On the one hand, the environmental policy stringency imposes high environmental taxes on polluting activities and, on the other hand, provides R&D support to clean technologies. This study examines the impact of energy intensity, energy depletion, green energy transition, and environmental policy stringency on load capacity factor in G7 countries from 1990–2020 using common correlated effects mean group and augmented mean group panel long run estimators. The study's robust results show that i) energy intensity has a negative impact on environmental sustainability in Germany, Italy, and the USA, ii) energy depletion has a negative impact on environmental sustainability in Canada and France, and iii) green energy transition has a positive impact on environmental sustainability in Japan. G7 countries must reverse the adverse effects of energy intensity and energy depletion by accelerating the transition to green energy. These countries with significant fiscal capacity should use environmental policy instruments that include environmental taxes. Graphical abstract
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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