Causal Relationship Among Carbon Dioxide (CO2) Emissions, Renewable Energy, Population and Economic Growth in Bangladesh: An Empirical Study
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
Developing countries face environmental degradation crisis due to the consumption of nonrenewable energy for economic development induces ecological destruction. However, the consequences of environmental deterioration can no longer be overlooked. Using data from 1990 from 2018, this study scrutinized the long-run equilibrium along with the trend among consumption of renewable energy, carbon dioxide emissions, Population, and economic growth in Bangladesh. This study reveals the significant cointegration of renewable energy with controlled variables using the ARDL bound test. Also, ECM with ARDL unrestricted version enables us to decide the speed of adjustment is 27.647% addressed for short-run elasticity in the long run. Stability and further diagnostic tests are performed for model post estimation and validation. Also, it needs further steps from the government side to promote renewable energy that boosts economic development.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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