The Impact of Plant Clinics on the Livelihoods of Bangladeshi Farmers
Bibliographic record
Abstract
The Plantwise programme in Bangladesh was launched in 2015 to build local capacity in plant pest and disease management to enable frontline extension workers to provide practical recommendations to farmers.We assessed the impact of plant clinics on farm productivity and profitability with a focus on cucurbits with fruit fly.A quasi-experimental approach was taken, with a matching design, based on similarity of agro-ecological zone, crops grown and pests and diseases.Results showed an increase in income for plant clinic users growing all types of cucurbits. Key highlights• 61% of plant clinic users reported an increase in their problem-solving ability, compared to 43% of non-users.• Plant clinic users were 90% more likely to use pest control practices than non-users.• Yield was significantly different for all crops apart from sponge gourd.• Gross income is significantly different for all crops.• Net income is significantly different for all crops apart from sponge gourd and ribbed gourd.• Average income for clinic users was about USD 78.99 (33%) higher than for non-users.• About 80% of plant clinics users informed other farmers about the advice received with an average of over 4 people informed by each of these 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".