Green or gas in OPEC member countries: a linear and asymmetric investigation of energy–growth nexus
Bibliographic record
Abstract
Abstract This study employed a combination of linear and nonlinear models to investigate the energy–growth nexus of OPEC member countries from 1960 to 2018 in a country‐specific form. It questioned the environmental friendliness of the energy initiatives of OPEC member countries as major producers and exporters of crude oil. Primary evidence of the study shows energy dependence among OPEC member countries supporting the growth hypothesis. We also found complementarity in fossil fuel and renewables as inducers of growth in 70% of the studied countries and found greater growth influence of fossil fuel in the case of 16% of the studied countries. In a country like Congo, we found greater influence from renewable energy, while Gabon's status was indeterminate. The dynamic profile of the energy–growth nexus evidenced by the error correction representations in their linear and asymmetric forms shows that growth adjusts nonlinearly to energy use in about 39% of the investigated OPEC member countries, and linearly in 61% of the countries. It can be said from our findings that global initiatives on green energy are gaining grounds in a preponderance of OPEC member countries.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| 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) | 0.004 | 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".