An Integrated Pest Management Adoption Survey of Sweet Corn Growers in the Great Lakes Region
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
Sweet corn is one of the most common fresh market vegetable crops grown throughout the north central and north east regions of the United States. In 2008, the Great Lakes Vegetable Working Group measured integrated pest management (IPM) practice adoption by growers of this crop using online and hardcopy surveys over a 10-mo period. The survey asked growers from nine states and Ontario, Canada, which pest management practices they used on their farm operation in the following sections: education, preplant, at-plant, in-season, postharvest, scouting, and demographics. Each individual survey question was ranked by a panel of university specialists and designated as a low, moderate, or high IPM valued activity, with points assigned accordingly. On survey completion, the total points accumulated by the grower would place them into one of three categories; low, moderate, or high IPM adopter. Of the 407 respondents, 130 were placed in the low IPM adoption category, 251 were deemed moderate IPM adopters, and 26 were placed in the high IPM category. Some key general attributes of a high IPM adopter include someone who has grown vegetables for at least 10 yr and has a farm >51 acres (67%) and raises between 21-50 acres of sweet corn (44%). Some key general attributes of a low IPM adopter include less experience on smaller acreage, with 56% having grown vegetables for fewer than 10 yr with 57% on farms smaller than five acres.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 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 | 0.000 | 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 it