Encouragement from the right source: Evaluating the impact of the 4R Nutrient Stewardship Certification Program in the Ohio Western Lake Erie Basin
Bibliographic record
Abstract
Harmful algal blooms are a considerable environmental issue predominantly caused by runoff of nutrients from agricultural lands. One high-profile set of practices promoted to combat this threat is the 4Rs of nutrient stewardship that concern using the right source of nutrients at the right rate and right time in the right place. While outreach for agricultural conservation is often undertaken by governmental or nonprofit entities, there is increasing interest in engaging agricultural retailers to leverage the trust that already exists between farmers and their agribusiness professionals. The 4R Nutrient Stewardship Certification Program, implemented in the Western Lake Erie Basin (WLEB) in 2014, certifies crop advising companies and agronomy retailers or Nutrient Service Providers (NSPs) to promote best practices in nutrient management. This program has since grown and now exists in six US states and the province of Ontario and Prince Edward Island in Canada. Using a survey of farmers in the WLEB, we investigate the impact of working with certified NSPs over time on farmers' reported 4R-related behaviors. We find evidence that working with a certified NSP has a positive impact on 4R behaviors that is independent of other potential explanations for this change (e.g., farmer concern about nutrient loss, local regulatory efforts, and exposure to general 4R-related outreach). Overall, these results suggest that the 4R Nutrient Stewardship Certification Program is having an independent, positive impact on farmer behavior, and engaging with agricultural retailers and agronomists can be effective at advancing adoption of environmentally impactful nutrient management practices.
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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 | 0.005 | 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 | 0.000 |
| Open science | 0.001 | 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".