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Social farming is gaining increasing attention from multiple stakeholders in Europe because it can generate several socioeconomic benefits, for farming households too. The research—which is part of a project carried out by a healthcare authority in the Friuli Venezia Giulia region in order to investigate social farming in the local area—is a first attempt to analyse social farm results and to what extent they are affected by farm assets, as well as by the environment in which farms are embedded. The proposed model is based on the investigation of the causal relationships between “structural”, “relational” and “social farm result” constructs (latent variables), and on the identification of their measurement scales (observed variables). The causal relationships between these three constructs have been tested via a structural equation model calculated with the linear structural relationship method. The findings show that social farm results are mainly influenced by the relational variables (e.g., social and economic relations). On the contrary, the structural variables (e.g., size) do not directly affect the results, but they do have a negative indirect effect on them which is mediated by the relational variables. The findings suggests that alongside structural investment support, it is also important to strengthen relations and networks at local level in order to reinforce social farm results. Overall the findings contribute to the further understanding of the driving forces affecting social farm performance and provide policy makers and practitioners with information for scaling-up social farming

Social farming: a proposal to explore the effects of structural and relational variables on social farm results