A Framework to Assess State Support of Organic Agriculture
Bibliographic record
Abstract
ABSTRACT Support for organic farming varies from state to state, and there have been few attempts to document what types of support currently exists. This research assesses regionally specific and relevant support available to organic farmers at the state level. This exploratory study develops a framework of ten key categories of organic agricultural support: (1) Leadership, (2) policy, (3) research, (4) technical support, (5) financial support, (6) marketing and promotion, (7) education and information, (8) consumer issues, (9) inter-agency activities, and (10) future developments. Data from state departments of agriculture, land grant universities, extension services, and other state-level agencies provide the basis for a numerical assessment of support in each category. State assessments are based on the number of activities, availability of information, and attention from personnel for each of the ten categories. A pilot study of Minnesota and Illinois was conducted to verify the utility of the framework and to explore the variation of support available within a region. This assessment framework is a valuable tool for farmers, researchers, state agencies, and citizen groups seeking to document existing types of organic agricultural support and discover topics that need more attention.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".