THE ROLE OF PUBLIC/PRIVATE PARTNERSHIP IN DEVELOPMENT OF TRANSPORT INFRASTRUCTURE: EVIDENCE FROM VIETNAM
Bibliographic record
Abstract
Transport infrastructural development is considered a significant driver of economic growth and has therefore, gained the attention of scholars and practitioners alike. With this hindsight, the current article examines the impact of public/private partnerships on the development of transport infrastructure in Vietnam. The current research uses population growth, economic growth, and foreign direct investment (FDI) as the control variables to predict transport infrastructure development in Vietnam. This study has used a secondary source of data collection i.e. the World Bank Indicators (WDI) database. Data thus extrapolated covers the period from 1981 to 2020. This study has used the Augmented Dickey-Fuller (ADF) test to test the stationarity of the constructs and the error correction model (ECM) to test the nexus among the variables. The results reveal that public/private partnership, population growth, economic growth and FDI have a positive association with the development of transport infrastructure in Vietnam. These outcomes can guide the regulators while developing policies related to transport infrastructural development.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".