Understanding change in family farming, development trends and community linkages in Huron County
Bibliographic record
Abstract
Family farming has traditionally been the principal unit of agricultural systems and an important contributor to the social and economic vitality of rural communities. In recent decades, both agriculture and rural communities have been changing in accordance with wider processes of change. Such changes are thought to potentially threaten the persistence of family farming and result in the deterioration of farm-community linkages. Recent research has demonstrated that family farmers are able to survive through the adoption of a variety of adjustment strategies, yet few studies have examined the reasons for or factors influencing family farmers choice of strategies, or the resulting implications that such changes in family farming pose for farm-community relationships. The purpose of this thesis is to describe and interpret current trends in family farming in Ontario through empirical investigation of farm business development trajectories, the reasons prompting farmers to pursue them, and the potential implications for farmers interaction with their rural community. The research was conducted in the summer of 1999 involving 70 telephone interviews with family farmers in Huron County, along with a subsequent set of in depth personal interviews. The results confirm that a range of business development strategies are being followed, and reveal a variety of circumstances and motivations prompting family farmer's decisions, while they continue to be active contributors to the social and economic vitality of their rural community.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".