Lessons for Succession Planning in Rural Canada: A Review of Farm Succession Plans & Available Resources in Haldimand County, Ontario
Bibliographic record
Abstract
For local economic developers, succession planning is becoming a more prominent issue due to the aging population and workforce. This is especially true in rural communities like Haldimand County where the economic base is farming, as the average age of farmers continues to increase while fewer youth are entering the profession. Promoting workforce development through succession planning will increase the likelihood that capable and skilled farmers are filling retiree’s positions which will improve economic stability and reduce the risk of farm business failure. This research uses qualitative methods to assess whether or not farmers in Haldimand County are aware of the succession planning process, determine if adequate resources are available to help farmers with the succession planning process, and identify any challenges farmers experience during the succession planning process that are not addressed through the available resources. A list of recommendations on how to mitigate these obstacles is also provided, in hopes that succession planning will become more accessible and utilized. Keywords: Succession planning, farming, agricultural, rural development, workforce development, rural Ontario ------------------------------------------------------------------- Titre: Leçons de planification de la relève dans le Canada rural: un examen des plans de la relève et des ressources disponibles d'une ferme dans le comté de Haldimand, en Ontario. Résumé Pour les promoteurs économiques locaux, la planification de la relève devient une question de premier plan du fait du vieillissement de la population et de la main d'œuvre. Cela est particulièrement vrai dans les communautés rurales comme le comté de Haldimand où la base économique est l'agriculture, alors que l'âge moyen des fermiers continue d'augmenter tandis que peu de jeunes rentrent dans la profession. Promouvoir le développement de la main d'œuvre à travers la planification de la relève augmentera la probabilité des fermiers aptes et compétents de combler les postes de retraités qui amélioreront la stabilité économique et réduiront le risque d'échec d'entreprise agricole. Cette étude utilise des méthodes qualitatives pour évaluer si les fermiers du comté de Haldimand sont conscients ou non du processus de planification de la relève, déterminer si des ressources adéquates sont disponibles pour aider les fermiers dans le processus de planification de la relève et identifier tout défi que peut rencontrer un fermier durant le processus de planification de la relève qui n'est pas traité à travers les ressources disponibles. Une liste de recommandations sur la manière d'atténuer ces obstacles est aussi fournie, dans l'espoir que la planification de relève devienne plus accessible et utilisée.
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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.012 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".