Factors Affecting the Income of Vietnamese Peasants: A Case in Tra Vinh Province
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Studying the factors affecting the income of Vietnamese peasants: A case in Tra Vinh province, by data collection method of 170 peasants’ households in 4 districts: Cau Ngang, Cang Long, Chau Thanh and Tieu Can in Tra Vinh province, Vietnam. The authors use multivariate regression analysis method. The study has found the factors such as gender of households’s heads, ages of households’ heads, education levels, the number of family members, dependency rates, application of technical advances, production areas affecting the income of peasants in these areas. Since then, the study has implied a policy to improve the income of peasants. For example, it could be very important for us to focus on training science and technology in agriculture, diversify crops and livestock in agriculture, improve techniques and enhance education levels to increase income for peasants in Tra Vinh province in the future.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 it