Evaluation of the Effect of Farmer Input Support Program (FISP) on Small-Scale Farmers in the Kara Region of Togo
Bibliographic record
Abstract
The government of Togo reintroduced Farmer Input Support Program (FISP) as one of its Poverty Reduction Strategies (PRS) in 2002. Since the introduction of the program, the studies that evaluate its effects on income have focused either on fertilizer or seed component, but not on both, which made it a challenge to find out what improvements in small-scale farmers’ productivity can be attributed to FISP as a whole. Using Propensity Score Matching technique with collected data from 150 randomly surveyed households in the Kara region of Togo, the authors of the study estimated the impact of FISP on beneficiary households’ output from maize production. The results show that FISP augmented household annual maize income by 30.8% and total household income by 13.9% for both 2016/17 and 2017/18 cropping seasons. However, even though FISP is achieving its objective of improving small-scale farmers’ income, this increment is still not large enough to take households above the poverty line, and the effects of FISP to reduce overall poverty is also limited.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".