Investigating the factors on attracting resources for urban development in Vietnam
Bibliographic record
Abstract
This study is carried to analyze the factors influencing the attracting resources for urban development in a case study in Vietnam. The research findings show that factors such as human resources, local policies, infrastructure system, local advantages, and international integration were the most influential factors on the ability to attract resources. At the same time, the study carried out the forecast of the need to use resources for urban development of Phuc Yen city in Vietnam. The resources forecasted in the study are human resources and financial resources. For human resources, with the data collected through surveys and evaluation of enterprises - an important subject promoting the socio-economic development of the city, the authors assessed the adaptive capacity of this human resource to serve the development goals of the urban. As for financial resources, the study predicts the demand for capital for industry, agriculture, and services of Phuc Yen City by 2030. The research findings are the basis for proposing solutions to support and promoting the attraction of resources for urban development of Phuc Yen City, Vietnam.
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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 | 0.000 | 0.001 |
| 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 | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".