Community science: A typology and its implications for governance of social-ecological systems
Наука, осуществляемая сообществами: типология и ее значение для управления социально-экологическими системами
2020-01-31
SCID: 54.1/4rvw4hmk
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community scienceecosystem-based managementknowledge co-productionsocial learningsocial-ecological systems
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Abstract (AI)
There is an increasing recognition globally of the role to be played by community science –scientific research and monitoring driven and controlled by local communities, and characterized by place-based knowledge, social learning, collective action and empowerment. In particular, community science can support social-ecological system transformation, and help in achieving better ‘fit’ between ecological systems and governance, at local and higher levels of decision making. This paper draws on three examples of communities as central actors in the process of knowledge co-production to present a typology of community science, and to deduce a set of key principles/conditions for success. The typology involves three social learning models in which the community acquires scientific knowledge by (1) engaging with external bodies, (2) drawing on internal volunteer scientific expertise, and/or (3) hiring (or contracting) in-house professional scientific expertise. All of these models share the key characteristic that the local community decides with whom they wish to engage, and in each case, social learning is fundamental. Some conditions that facilitate community science include: community-driven and community-control; flexibility across leadership models; connection to place and collective values; empowerment, agency and collective action; credible trust; local knowledge; and links to governance. Community science is not a panacea for effecting change at the local level, and there is need for critical assessment of how it can help to fill governance gaps. Nevertheless, a considerable body of experience globally illustrates how local communities are drawing effectively on community science for better conservation and livelihood outcomes, in a manner compatible with broader trends toward ecosystem-based management and local stewardship.
Key Findings
1
Across all models, local communities control whom they engage, while social learning remains fundamental to knowledge co-production.
2
Communities may engage external scientific bodies, rely on internal volunteer expertise, or hire professional scientific expertise.
3
Community science can improve conservation and livelihood outcomes and support ecosystem-based management, but it is not a universal solution and requires critical assessment of governance gaps.
4
Successful community science depends on community control, place-based values, empowerment, collective action, trust, local knowledge, leadership flexibility, and governance connections.
5
The paper develops a typology of community science based on three social learning models for acquiring scientific knowledge.
Research Object
community science in local communities and social-ecological systems
Research Subject
typology, social-learning models, success conditions, and governance implications of community science
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2020-01-31
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