跨越语境的意义:口述历史、大数据和气候变化

Julia Olson, Patricia Pinto da Silva
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引用次数: 0

摘要

在气候变化社会科学方法中使用口述历史,可以对当地经验和知识的情景化、意义化层面进行丰富而详细的探索。但是,"大数据 "方法已被越来越多地倡导为通过更好地利用大量定性数据源来扩大对单个项目的理解的一种手段。本文利用诺阿之声口述历史档案(NOAA Voices Oral History Archives)这一在线数据库,探讨了此类二次分析所引发的问题,该数据库重点关注被认为特别容易受到气候变化影响的沿海社区和群体。将文本挖掘等更大规模的方法与细读等更传统的方法相结合,揭示了人们谈论环境变化的方式在时间和空间上的差异,强调了记忆和经历是如何形成理解的,以及这些差异在表述和文化铭刻上的微妙之处。通过观察多个文献集,可以发现社区之间的共同理解、争论点和差异,如果脱离上下文,这些理解、争论点和差异可能会被掩盖,这表明了 "小数据 "方法对 "大数据 "的重要性,以充分了解对气候变化等环境变化的深层文化理解、认识和历史。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Meaning Across Context: Oral Histories, Big Data, and Climate Change
The use of oral histories in social scientific approaches to climate change has enabled richly detailed explorations of the situated, meaning-laden dimensions of local experiences and knowledge. But “big data” approaches have been increasingly advocated as a means to scale up understandings from individual projects, through better utilizing large collections of qualitative data sources. This article considers the issues raised by such secondary analysis, using the NOAA Voices Oral History Archives, an online database with a focus on coastal communities and groups thought especially vulnerable to climatic changes. Coupling largerscale methods such as text-mining with more traditional methods such as close reading reveals variations across time and space in the ways people talk about environmental changes, underscoring how memories and experiences shape understandings and the subtlety with which these differences are articulated and culturally inscribed. Looking across multiple collections illuminates those shared understandings, points of contention, and differences between communities that might be obscured if decontextualized, showing the importance of “small data” approaches to “big data” to fully understand the deeply cultural understandings, perceptions, and histories of environmental changes such as climate change.
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