Impact of Political Connection on Farming Households’ Performance of Tea Production in Vietnam
Bibliographic record
Abstract
Purpose: This paper aims to investigate the impacts of political connections on farming households’ performance, especially in tea production. Methodology/Approach: The Box-Cox methodology is applied using the primary data surveyed on 244 tea farming households in Vietnam. Findings: The findings show the significant role of political connection on improving farming households’ income, particularly to members of the Communist Party, Youth Union and Farmer’s Union. However, the interaction effects of Farmer’s Union, Youth Union, Veteran’s Union and Communist Party with land has negatively significant impact on farming household income. Practical Implications: The evidences point out the capacity of improving tea producers’ income could be really potential implying most of existing related policies which should be adjusted. Originality/Value: This is the first research examining the impact of political connection on agricultural performance, especially in tea production. The impacts are estimated in de-tail; such as participating more on Veteran’s, Farmer’s, Youth Union and Communist Party may reduce time on cultivating; as a result, cultivated land could be reduced. Basing on these findings, we also suggest some appropriate policy implications related to the issue how to improve income of tea production households.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".