Impact of globalization on CO2 emissions in Vietnam: An autoregressive distributed lag approach
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
This study aims at investigating the impact of globalization on CO2 emission in Vietnam. Empirical analysis is performed by employing autoregressed distributed lag approach on time series data for the period of 1990 to 2016. The paper tested the stationary, cointegration of time series data and utilized autoregressed distributed lag modeling technique to determine the short run and long run relationship among CO2 emission, globalization, foreign direct investment, exports, coal consumption per capita and fossil fuels electricity generation. The results show that globalization increases CO2 emission in Vietnam and thus globalization is not beneficial for the long-term environmental health. Exports lowers CO2 emissions in both short run and long run whereas coal consumption per capita and fossil fuels electricity generation raise CO2 emissions. The study further shows that foreign direct investment did not affect CO2 emissions directly in short run as well as in long run.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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