Exploring Farm Succession and Transition Challenges and Opportunities on Wolfe Island
Bibliographic record
Abstract
This research aims to identify the following: what challenges and prospects face farm succession and transition on Wolfe Island? And: how might farm succession and transition influence the future of alternative farming on Wolfe Island? Wolfe Island is situated at the entrance of the St. Lawrence River from Lake Ontario, acting as a natural boundary between Kingston, ON and Northern New York State. The majority of farming on the Island is generational beef, corn, grain, and soy farms. Farm succession/transition involves one inheriting the previous owner’s rights and ownership of a piece of land. I used the generativity framework to address these questions, which examines efforts to guide the next generation. Eight interviews and a focus group identified future agricultural pursuits on Wolfe Island. The interviews were categorized into two groups of participants: generational and new farmers. Five generational farmer interviews consisted of the current farmer(s)/farm owners in the family along with an adult relative of the next generation; this structure allowed me to observe dynamics across generations. The three new farmer interviews, involving individuals who have been farming on Wolfe Island for under ten years, allowed for new agricultural perspectives to be obtained. Four interviewees took part in the focus group, where topics surrounding sustainable farming on the Island, including farm livelihoods, environmental health, and local food systems, were discussed collaboratively. Thematic analysis and a combination of inductive and deductive reasoning were used to identify the key ideas and trends emerging across the interviews and focus group. The findings identified how generativity is present regardless of clear or unclear lines of succession or being a new farmer and how strong community connections are the foundation of a robust farming community and integral for the sharing of agricultural knowledge. This research also revealed the challenges farmers face when operating a farm, such as high production costs, and demonstrates how agriculture programs and policies, such as appropriate succession planning guides and supports for new and young farmers, could help mitigate the decline of the farming industry.
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 | 0.002 | 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 | 0.008 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".