The Relationship Between Grand River Dairy Farmers' Quality of Life and Economic, Social and Environmental Aspects of Their Farming Systems
Bibliographic record
Abstract
During early 1997, after focus groups, interviews and a mail survey were administered to a random sample of Grand River watershed dairy farmer in the Grand River watershed of southwestern Ontario. This paper summarizes the main results of the study. We concluded that these farmers have achieved a very good average quality of life. Their farming systems display good productivity, excellent viability and stability and moderate average environmental protection-all important elements of sustainability. This is mainly because they have steady incomes as a result of their supply managed system, excellent cattle genetics, strong family relationships and spirituality. If they had to leave their dairy farms they would miss the open space and country living more than anything else. There is some concern that international free trade agreements may threaten supply management to which the majority attribute their stable and reasonably good incomes. Environmental protection may also be at risk for many dairy farmers. For instance, their present manure management system is a limiting factor preventing as many as a third of them from expanding their herds in addition to such other barriers as the high price that they must pay for the milk quota that they must purchase.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".