Fungicide resistance and misinformation: A game theoretic approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Fungicide resistance is a serious problem for agriculture today. This analysis provides additional insight into the strategic behavior of farmers when their fungicide use generates a negative intertemporal production externality in the form of fungicide resistance. We find that when farmers encounter this type of externality, they choose fungicide levels that exacerbate fungicide resistance. We examine a compensation mechanism in which a farmer reduces fungicide use in exchange for a transfer. This mechanism reduces fungicide use; however, misinformation about the severity of fungicide resistance generates distortions. We find that one‐sided misinformation could lead a farmer to choose socially optimal fungicide levels, which makes the compensation mechanism less necessary. In addition, we show that when both farmers are misinformed, the mechanism could lead farmers to choose fungicide levels below the socially optimal level depending on their pessimistic beliefs about the severity of fungicide resistance.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it