TY - CONF
T1 - Trans-local reflexive learning for urban food system transformation: developing an approach while doing it
AU - Luger, Jonathan
AU - van der Meij, MG
AU - Regeer, BJ
PY - 2023
Y1 - 2023
N2 - In the last decade, on a global scale, many local initiatives have emerged aimed at multi-actor urban food system transformation. The challenges that actors in the initiatives face in their attempts to transform the local food system are ideally scaffolded by reflexive learning, for example by reflecting on own practices but also through in-depth knowledge exchange with actors from comparable initiatives. However, such knowledge exchange is hard to arrange due to time and availability of the actors, their geographical distance, and the need to tailor the learning method so that learning needs of the one are matched with lessons learned of the other and vice versa. This study aimed to work towards time and distance independent translocal reflexive learning on transforming urban food systems, through a reflexive action oriented research approach. Researcher took the role of interviewers as well as translators and facilitators of the learning. Data was gathered and learning was facilitated by means of dialogic timeline interviews and workshops with (at least) coordinating actors of 15 urban food system transformation initiatives across Europe. In three cases, these interviews and workshops were held with multiple stakeholders in those initiatives - and representatives of another similar initiative - so as to create an equal playing field for responsible and reflexive urban food system transformation. Combined deductive and inductive transcript and researcher note analysis yielded insights in the activity logic of these initiatives, amongst which various strategies to address commonly experienced transformation challenges, as well as insights into the value of the learning approach. We conclude the study with recommendations for improved facilitation of time and place independent reflexive translocal learning between actors who coordinate urban food system initiatives and their stakeholders, and further research directions.
AB - In the last decade, on a global scale, many local initiatives have emerged aimed at multi-actor urban food system transformation. The challenges that actors in the initiatives face in their attempts to transform the local food system are ideally scaffolded by reflexive learning, for example by reflecting on own practices but also through in-depth knowledge exchange with actors from comparable initiatives. However, such knowledge exchange is hard to arrange due to time and availability of the actors, their geographical distance, and the need to tailor the learning method so that learning needs of the one are matched with lessons learned of the other and vice versa. This study aimed to work towards time and distance independent translocal reflexive learning on transforming urban food systems, through a reflexive action oriented research approach. Researcher took the role of interviewers as well as translators and facilitators of the learning. Data was gathered and learning was facilitated by means of dialogic timeline interviews and workshops with (at least) coordinating actors of 15 urban food system transformation initiatives across Europe. In three cases, these interviews and workshops were held with multiple stakeholders in those initiatives - and representatives of another similar initiative - so as to create an equal playing field for responsible and reflexive urban food system transformation. Combined deductive and inductive transcript and researcher note analysis yielded insights in the activity logic of these initiatives, amongst which various strategies to address commonly experienced transformation challenges, as well as insights into the value of the learning approach. We conclude the study with recommendations for improved facilitation of time and place independent reflexive translocal learning between actors who coordinate urban food system initiatives and their stakeholders, and further research directions.
UR - https://ist2023.nl/
M3 - Poster
ER -