Toward Improved Adoption of Best Management Practices (BMPs) in the Lake Erie Basin: Perspectives from Resilience and Agricultural Innovation Literature
Bibliographic record
Abstract
Phosphorus (P) runoff from agricultural sources is a recognized environmental problem, particularly in regions draining into Lake Erie. This problem may well be exacerbated particularly through increased magnitude and frequency of extreme climatic events (e.g., excessive precipitation and droughts). On the physical sciences side, the recent extensive literature focuses on structural Best Management Practices (BMPs) which have the potential to mitigate both surface and sub-subsurface P losses. Modeling studies show that there is still a lack of adoption of these P-related voluntary BMPs by the farmers. At the same time, and while the social sciences side of the literature on structural BMPs adoption weakly affirms the latter, this paper argues that the literature on resilience and on agricultural innovation can better inform our understanding of the limited adoption of phosphorus related structural BMPs by farmers in the Lake Erie Basin.
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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 | 0.000 |
| 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 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".