An experimental approach to farmer valuation of African rice genetic resources
Bibliographic record
Abstract
Abstract Genebanks serve as both providers of valuable traits for breeding programs and repositories of diverse crop genetic material representing society's agricultural heritage. In this study, we use a Becker‐DeGroot‐Marschak mechanism to elicit the willingness‐to‐pay of rice farmers in Côte d'Ivoire for small amounts of African rice ( Oryza glaberrima ) landraces held by the genebank of the Rice Biodiversity Center for Africa, and for seed of newly developed ARICA rice varieties bred using genebank materials. Using a field experiment, we additionally investigate how randomized exposure to and experimentation with small amounts of African rice landrace seed or seed of advanced rice varieties developed by AfricaRice affect how smallholder rice farmers value these novel genetic resources. Surprisingly, we find that farmers generally value having access to African rice landraces at approximately the same level as for advanced rice varieties (and far above market rates for improved seed), and that those farmers who grew landrace seed in the offseason were willing to pay more than those who did not. Our results demonstrate the additional value provided by the conservation of African rice landrace varieties (apart from their use in breeding) and highlight the importance of experimentation in the adoption process.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".