Off‐Farm Work, Intensity of Government Payments, and Farm Exits: Evidence from a National Survey in the United States
Bibliographic record
Abstract
The last three decades have witnessed the continued exit of households from primary agriculture in the United States, where the average annual gross exit rate has averaged 10% per year. Understanding exit behavior is one key to future farm structure, management of abandoned land, depopulation of rural areas, and agricultural policy, including government program payments. This study empirically estimates the determinants of exit decisions of farm households. Particular attention is given to the roles of intensity of government payments and off‐farm work decisions of farm couples in the exit decision. Using a large farm‐level survey and controlling for endogeneity, results indicate that farm households with reduced intensity of government payments are more likely to exit farming. Households where the operator spouse works off the farm are more likely to exit farming. Additionally, households with older farmers, with the farm operator and spouse raised on a farm, and households operating farms located in Northern Great Plains are more likely to exit farming.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".