Part time farming in Manitoba
Bibliographic record
Abstract
Part time farmers have long been a factor in the development of agriculture in Manitoba, yet working on the farm and off the farm has been officially discouraged by federal tax statutes, while at the same time the province has been encouraging the creation of more jobs in rural, and primarily farming, communities. This study makes use of a utility maximization approach to modeling part time farming behavior and applies this model to data derived from the Census responses of Manitoba farmers in 1986 and 1991. The impact of a differential tax rate for on farm income and off farm income is modeled as well as the impact of output prices, autonomous transfers, general price levels and factor input prices, and the impact of the off farm wage. The comparative statics are calculated and a series of policy elasticities are computed for each policy instrument defined above. The data support the use of a logarithmic form of estimation in which the Cobb Douglas functional form is applied to both utility and production. In addition, constant returns to scale is assumed which, while removing some of the reaction conditions from the analysis, enables the direct testing of the model with the data available. The data support the use of estimated relationships for policy interpretations. The theoretical signs of the comparative static analysis and the reduced form of the model generally confirm the theoretically expected signs, but also indicate that shifts in utility function parameters may well explain the behavior of part time farmers in Manitoba inasmuch as the production function parameters are found to be stable...
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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 | 0.000 | 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 | 0.000 | 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".