4.5 Article

The New (Ab)Normal: Outliers, Everyday Exceptionality, and the Politics of Data Management in the Anthropocene

期刊

出版社

ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/24694452.2020.1785836

关键词

climate adaptation; data exclusions; environmental change; extreme events; rarity

资金

  1. Western Water Assessment - U.S. National Oceanic and Atmospheric Administration under Climate Program Office [NA10OAR4310214WWA]

向作者/读者索取更多资源

The Anthropocene affects how we manage the environment in many ways, perhaps most importantly by undermining how past conditions act as baselines for future expectations. In a period when historical analogues become less meaningful, we need to forge new practices and methods of environmental monitoring and management, including how to categorize, manage, and analyze the deluge of environmental data. In particular, we need practices to detect emerging hazards, changing baselines, and amplified risk. Some current data practices, however, especially the designation and dismissal of outliers, might mislead efforts to better adapt to new environmental conditions. In this article we ask these questions: What are the politics of determining what counts as abnormal and is worthy of exclusion in an era of the ever-changing normal? What do data exclusions, often in the form of outliers, do to our ability to understand and regulate in the Anthropocene? We identify a recursive process of distortion at play where constructing categories of abnormal-normal allows for the exclusion of outliers from data sets, which ultimately produces a false rarity and hides environmental changes. To illustrate this, we draw on a handful of examples in regulatory science and management, including the Exceptional Event Rule of the Clean Air Act, beach erosion models for nourishment projects, and the undetected ozone hole. We conclude with a call for attention to the construction of normal and abnormal events, systems, data, and natures in the Anthropocene.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据