Sending Vietnamese Rice Farmers Back to School: Further Evidence on the Impacts of Farmer Field Schools
Bibliographic record
Abstract
This study evaluates the impact of farmer field schools (FFS) on knowledge, insecticide use, and yield using a nonconsecutive, two‐year panel data that allows one to control for nonrandom selection. Regression analysis using a difference‐in‐difference approach indicates FFS training did not result in statistically significant impacts on insecticide use and yield over the period of time examined. However, there is some evidence that FFS had an “initial” knowledge impact, but it was not sustained over time. Retraining FFS graduates may be an attractive option to help maintain knowledge and improve performance over time, but we do not find empirical evidence on the effectiveness of this strategy based on a small sample of retrained farmers. La présente étude examine l’impact du programme Champ‐École‐Paysan (CEP) (Farmer Field Schools – FFS) sur l’acquisition des connaissances, l’utilisation d’insecticides et le rendement, à l’aide de données de panel non consécutives recueillies sur une période de deux ans et permettant de maîtriser la sélection non aléatoire. Une analyse de régression utilisant la méthode de différence de différences a révélé que la formation offerte dans le cadre du programme CEP n’a pas eu d’impact statistiquement significatif sur l’utilisation d’insecticides ni sur le rendement au cours de la période visée par l’étude. Toutefois, il semble que le programme CEP a eu un impact sur l’acquisition des connaissances au début, mais que cet impact n’a pas été soutenu au fil du temps. Le recyclage des participants au programme CEP peut constituer une option intéressante pour le maintien des connaissances et l’amélioration du rendement au fil du temps. Par contre, l’étude d’un petit échantillon de producteurs recyclés n’a pas fourni de preuve empirique permettant de croire à l’efficacité de cette stratégie.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".