Understanding the Role and Contributions of the Incubator Farm Program in Creating the Next Generation of Farmers in the United States and Canada
Notice bibliographique
Résumé
The farming sectors in the United States and Canada has seen a steady decline in the number of farmers since the end of World War II. However, this issue did not gain widespread attention until the early 2000s when the farmer population hit a low of 2% of the total population in both countries. Recognition of this phenomenon led to initiatives to address farmer succession and renewal. Incubator farm programs – defined as land-based farmer training and support programs – are one such type of initiative that specifically focuses on developing entry pathways for people from outside the farm sector. The goal of this study is to critically assess incubator farm programs (IFPs) as a new farmer support strategy that helps overcome structural barriers and enhances the agency of new farmers. This dissertation examines the incubator farm as a place-based entity influenced by the surrounding environment and explores its contribution to the farm succession landscape. In doing this, I use a number of approaches and methods. First, a quantitative survey (n=63) provides a high-level view of the programmatic space, including the population it serves and seeks to reach, the geographical settings of primary activity where opportunity and demand have met, and how the services provided empower beginning farmers. I then used a Sustainable Livelihoods Approach to tease out the assets that beginning farmers need to possess to be successful and analyzed (n=5) case studies to understand how IFPs helped build these assets and further empower beginning farmers. Finally, a single in-depth case study utilizes participant observation methods to unpack the relationship of an IFP to its locale. In undertaking this dissertation, I was able to better understand the inner nature of IFPs, a space that I have been connected with over the last 12 years. I unpacked the support and services provided and how IFPs contributed to building the capabilities of new farmers. By analyzing an IFP as a pragmatic place-based initiative I was able to delve deeper into the dynamics of IFPs and their locale. This dissertation also contributes to a better grasp of the IFP as a non-traditional entry pathway into farming, and its contributions to creating a new generation of farmers.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».