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• W2896661912 abstract "There is a well-known folk tale about six blind men who go to see an elephant. Each man touches a different part of the animal, so each believes the elephant to be a different type of creature. Rather than pooling their knowledge to create a complete picture, they argue, and, as John Godfrey Saxe puts it, “Though each was partially in the right…all were in the wrong.”* This fable is now a cliche because humans so often get embroiled in ideological disputes, arguing not over facts per se, but over interpretations of facts as shaped by their own values, preferences, and prior beliefs. Science is supposed to settle disputes over the elephant, but for complex socioecological systems like fisheries, we are asking the blind men to describe a whole zoo—or perhaps an aquarium—with its human visitors and caretakers as well, a difficult task even for those who are willing to cross ideological or disciplinary divides. Given the diversity and complexity of fisheries systems, carefully prepared, large-scale databases are useful for piecing together a more complete picture of sustainability (1, 2). In PNAS, Asche et al. (3) analyze one of the more comprehensive large- N fisheries datasets to date. Their Fisheries Performance Indicators (FPIs) measure social as well as economic and ecological variables, which should help to strengthen the three pillars of sustainability in fisheries governance.Large datasets that measure a diverse set of attributes are important for several reasons. First, much of the discussion over fisheries governance is shaped by different values regarding outcomes. We see this in the long-standing debates over rights-based management, particularly the use of individual transferable quotas (ITQs) and other mechanisms … [↵][1]1Email: d.g.webster{at}dartmouth.edu. [1]: #xref-corresp-1-1" @default.
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• W2896661912 date "2018-10-19" @default.
• W2896661912 modified "2023-10-15" @default.
• W2896661912 title "Strengthening sustainability through data" @default.
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• W2896661912 doi "https://doi.org/10.1073/pnas.1816077115" @default.
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