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A methodological framework for understanding shared social values in deliberative valuation

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  • Mavrommati, Georgia
  • Borsuk, Mark E.
  • Kreiley, Allison I.
  • Larosee, Christopher
  • Rogers, Shannon
  • Burford, Klancey
  • Howarth, Richard B.

Abstract

Deliberative methods elicit social values and provide a framework for explicit representation of value dimensions that go beyond narrow self-interest; these dimensions are obscured by methods that focus on monetary value. The primary objective of this paper is to explore the reasoning behind people's assessments of the value of ecosystem services in a deliberative context. To do so, we collected quantitative and qualitative data from four workshops of residents in New Hampshire's Great Bay watershed in the Northeastern United States. Quantitative data come from participant surveys and expressed group preferences, while qualitative data were derived from transcripts of the group deliberations. This paper aims to understand the process of social value construction by identifying themes of discussion that affected participants' preferences changes over the course of deliberation. We visualized the dynamic process by which participants develop their preferences over time and developed two metrics using applied thematic analysis to better understand how people talk about themes related to ecosystem service tradeoffs. Our results suggest that preferences were formed mainly from ecological and common good considerations. Policymakers could use this insight to support environmental protection strategies and policies, improve environmental decisions, and better allocate resources among competing objectives.

Suggested Citation

  • Mavrommati, Georgia & Borsuk, Mark E. & Kreiley, Allison I. & Larosee, Christopher & Rogers, Shannon & Burford, Klancey & Howarth, Richard B., 2021. "A methodological framework for understanding shared social values in deliberative valuation," Ecological Economics, Elsevier, vol. 190(C).
    • Handle: RePEc:eee:ecolec:v:190:y:2021:i:c:s0921800921002433
    DOI: 10.1016/j.ecolecon.2021.107185
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    2. O'Shaughnessy, Matthew & Schiff, Daniel & Varshney, Lav R. & Rozell, Christopher & Davenport, Mark, 2021. "What governs attitudes toward artificial intelligence adoption and governance?," OSF Preprints pkeb8, Center for Open Science.

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