Bibliographic record
Abstract
In this study, we used the gravity model to identify factors affecting Vietnam’s tuna exports to major import markets, including the United States, Canada, Japan and European countries, and then to find the solutions with sufficient scientific and practical basis to promote the development of the tuna export industry in the future. This research’results show that an increase in factors including domestic tuna production, exchange rates, population of the importing country and geographical distance leads to increase the scale of Vietnam’ tuna exports, with the exchange rate playing the most important role, while the import tax rate is the significant barrier that reduces Vietnam’s tuna exports. In order to develop the tuna export sustainably in the future, Vietnam must maintain tight control over the domestic tuna resources, avoid overexploitation, and instead focus on enhancing product quality. Furthermore, it is critical to focus on satisfying the conditions of commitments in signed free trade agreements, actively analyzing the market and paying attention to trade promotion policies, growing trade connections with importing countries.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.021 | 0.033 |
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; both teacher heads agree on what is shown here.
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".