Exploring how social capital and learning are related to the resilience of Dutch arable farmers

CONTEXT Enhancing farm resilience has become a key policy objective of the EU's Common Agricultural Policy (CAP) to help farmers deal with numerous interrelated economic, environmental, social, and institutional shocks and stresses. A central theme in resilience thinking is the role of the unknown, implying that knowledge is incomplete and that change, uncertainty, and surprise are inevitable. Important strategies to enhance resilience are exploiting social capital and learning as these contribute to improved knowledge to prepare farmers for change. OBJECTIVE This paper explores how social cap... Mehr ...

Verfasser: Slijper, Thomas
Urquhart, Julie
Poortvliet, P. Marijn
Soriano, Bárbara
Meuwissen, Miranda
Dokumenttyp: Artikel
Erscheinungsdatum: 2022
Verlag/Hrsg.: Elsevier
Schlagwörter: S Agriculture (General) / SB Plant culture
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-27057107
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://eprints.glos.ac.uk/10681/

CONTEXT Enhancing farm resilience has become a key policy objective of the EU's Common Agricultural Policy (CAP) to help farmers deal with numerous interrelated economic, environmental, social, and institutional shocks and stresses. A central theme in resilience thinking is the role of the unknown, implying that knowledge is incomplete and that change, uncertainty, and surprise are inevitable. Important strategies to enhance resilience are exploiting social capital and learning as these contribute to improved knowledge to prepare farmers for change. OBJECTIVE This paper explores how social capital and learning relate to farm resilience along the dimensions of robustness, adaptation, and transformation. METHODS We study the resilience of Dutch arable farmers from the Veenkoloniën and Oldambt using a combination of four methods. Qualitative data from semi-structured farmer interviews, focus groups, and expert interviews are combined with quantitative data from farmer surveys. The qualitative data are analysed using thematic coding. Non-parametric tests are used to analyse the quantitative data. Based on methodological triangulation, we mostly find convergence in our qualitative and quantitative datasets increasing the validity of our findings. RESULTS AND CONCLUSIONS The results reveal that social capital and learning help farmers to adapt and are, in certain cases, also related to robustness and transformations. Robust farmers often learned by exploiting farmers' informal social networks, primarily relying on bonding social capital to acquire knowledge about agriculture or develop financial skills. Farmers undertaking adaptation are characterised by bonding and bridging social capital obtained by formal and informal networks, are early adopters of innovation, and have high self-efficacy. Combinations of bridging and linking social capital from formal networks could foster farmers to learn new ideas and critically reflect on current farm business models. These learning outcomes relate to farm transformations. ...