Adoption of Total Mixed Ration Practice and Profitability: The Case of Ontario Dairy Farms
Bibliographic record
Abstract
This thesis examines determinants of the adoption of total mixed ration (TMR), and the effects of the adoption of TMR on the farm level productivity and profitability of Ontario dairy farms. A sample of 320 farm level data from 2004-2008 is taken from the Ontario Dairy Farm Accounting Project (ODFAP). A probit model is estimated to examine the factors affecting the adoption of TMR; and the propensity score matching analysis is used to explore the influence of the use of TMR on sample farm’s productivity and profitability. Results from the probit model show that farmer’s age, herd size, region, breed type and feeding system have significant effect on the adoption of TMR. In turn, the adoption of TMR feeding practice has positive influence on both farm productivity and profitability. Under the propensity score matching method, the use of the TMR feeding practice has an economically significant effect on farm profits (i.e., for average farm with approximately 73 cows, the use of TMR feeding practice increases farm profits by CAD$37,091.30/year approximately) and a statistically significant increase in milk production by 1075.41 hl/cow per year.
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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".