The role of logistics industry in the sustainable economic development of Southeast Asian countries
Bibliographic record
Abstract
The purpose of this study is to determine the role of the logistics industry in the sustainable economic development in the context of Southeast Asian countries. This study is quantitative in nature where the data are gathered from the secondary sources. The analysis is carried out with the help of correlation, feasible generalized least square model (FGLS). The outcome of this study confirms the significant impact of LPI on GDP growth, CO2 emission and current health expenditure. Similarly, the significant impact of FDI is found on all the dependent variables of this study. In contrast, the variable of TOP is found to have a significant impact on both CO2 emission and current health expenditure, whereas it makes an insignificant impact on GDP growth. The absence of qualitative data is one of the major limitations of this study. Apart from that, the limited scope of this research on Southeast Asian countries is another limitation.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".