The dynamics of family farming in North Huron County, Ontario. Part I. Development trajectories
Bibliographic record
Abstract
Recent structural shifts towards enlargement and intensification in the farm sector in Canada have drawn attention to the changing relationship between farming and the rural community. While some developments in farming are implicated in increasing conflict with communities, others may be fostering the need for stronger linkages. A more nuanced understanding of change in both the family farm and community sectors would contribute to a better appreciation of these evolving linkages. This paper explores contemporary change on the farm side, with attention to the nature and causes of diversity in a local family farming system. Data from a survey of family farms in northern Huron County, Ontario, were used to document variations in farm development trajectories and to explore the interactive importance of factors relating to the farm economy, the farm business and the household. The research invokes a pathways conceptualisation and the theory of business and family life cycles in attempting to characterise and attribute change. Revealed trajectories range from aggressive engagement in expansion, diligent efforts to ‘hang on’ and forced or voluntary contraction. In addition, the paper presents two brief farm history case studies as a means of demonstrating the interaction of farm business and household factors through the lived experience of farm families. Revealed diversity in family farm business trajectories suggests an increasingly differentiated set of linkages and dependencies between farm and community.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".