Fitting a square peg in a round hole: Applying U.S. farm policy to organic farms
Bibliographic record
Abstract
The suite of U.S. federal farm programs available to organic farmers includes conservation programs through the Environmental Quality Incentives Program (EQIP) and Conservation Stewardship Program (CSP), risk management through crop insurance, and the Organic Certification Cost Share Program (commonly referred to as Organic Cost Share or just Cost Share). Of these programs, the Organic Cost Share is the most widely used. Many organic farmers do not enroll in conservation programs or purchase crop insurance. The underutilization of federal farm programs by organic producers is well known in the organic community, but there is a lack of systematic evidence about the rationale for not applying for or using programs. Using qualitative data collected through structured interviews, we find that many organic producers want to participate in the Organic Cost Share, EQIP, CSP, and crop insurance. Many are successful, but others face institutional, cultural, and programmatic barriers that prevent them from participating. A key recommendation from this study is the creation of specialized, highly trained crop insurance and conservation agents with expertise in organic farming systems to facilitate the application process and program use for conservation programs and crop insurance. The Organic Cost Share Program would have more impact if its funds were used to support beginning organic farmers in addition to small-scale farm operators.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".