What do we really know about the impacts of improved grain legumes and dryland cereals? A critical review of 18 impact studies
Bibliographic record
Abstract
Improved grain legume and dryland cereal (GLDC) varieties hold potential to intensify smallholder agriculture and improve livelihoods in semi-arid regions of sub-Saharan Africa and South Asia. To assess the empirical evidence base for these potential benefits, we review 18 GLDC impact studies and identify gaps in current knowledge on GLDC impacts. Results from this synthesis reveal that all five reasonably well-identified adoption studies estimate significant, positive effects of improved GLDC adoption on yields, profits, or household welfare. Another well-identified study focuses on nutritional impacts of improved GLDC consumption and measures positive effects on iron-deficiency in school children. Macro-level welfare estimates based on economic surplus models (eight of the 18 studies) are largely invalidated because of their dependence on poorly-identified household-level impact estimates. Four additional studies rely on correlations and expert interviews. Overall, impact studies focus on chickpea and groundnut, as opposed to other GLDC crops. Studies are geographically concentrated in Ethiopia, India, and Tanzania, and are heavily focused on estimating economic impacts, with few studies assessing potential environmental, nutritional or social impacts. Recommendations are offered to improve methodological approaches in future impact assessments of GLDC crops.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | high |
| grok | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| opus | Meta-epidemiology (broad) Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedLabeled directly by 3 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".