A mixed methods approach to exploring values that inform desirable food-systems futures

Throughout the United States, urban food systems are in suboptimal states that are not operating efficiently or equitably and thus do not support food security for all. Creating transformation to a more sustainable and desirable state first requires acknowledging the different values of diverse grou...

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Autores principales: Rachael Belisle-Toler, Jennifer Hodbod, Chelsea Wentworth
Formato: article
Lenguaje:EN
Publicado: Taylor & Francis Group 2021
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Acceso en línea:https://doaj.org/article/e95a427e33634a50a5b451ef78c2dd71
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Sumario:Throughout the United States, urban food systems are in suboptimal states that are not operating efficiently or equitably and thus do not support food security for all. Creating transformation to a more sustainable and desirable state first requires acknowledging the different values of diverse groups within a city. Then these diverse values can be used to explore pluralistic pathways to futures that maximize benefits for multiple stakeholders. We demonstrate how integrating visioning and Q-methodology can achieve an inclusive understanding of values as priorities for such a food system. Applied in Flint, Michigan, a post-industrial Rust Belt city, this approach can shape the planning process for cities experiencing food insecurity. Qualitative analysis of data from a visioning workshop resulted in sixteen values as priorities for a sustainable and desirable food system. Values as priorities were then ranked in a Q-sort activity, from which three unique groups of ranking patterns emerged, each of which can be interpreted as a vision for a better future. The three visions were a food system with healthy foods that residents are willing to travel for; a food system with convenient, fresh food options for those who cannot travel; and a food system that maintains the community’s food traditions. Our novel mixed methods approach empowers communities by giving them a voice in the planning process but also allows decision makers to create transformation pathways that more accurately reflect the needs of the various subsets of community members who hold diverse visions and priorities.