寻找卓拉/当元数据不够时:通过统计建模拯救黑人女性的经历

Q2 Social Sciences
Nicole M. Brown, R. Mendenhall, Michael L. Black, M. V. Moer, K. Flynn, Malaika Mckee, A. Zerai, Ismini Lourentzou, Chengxiang Zhai
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引用次数: 1

摘要

本研究使用统计主题模型对HathiTrust和JSTOR数据库中的80万份文档进行了分析,以确定与非裔美国女性相关的书籍、诗歌、报纸和期刊中的话语类型。我们研究了1746年至2014年间出现的一系列对话,揭示了对非裔美国女性的见解。我们确定了一种元数据修订方法,用于拯救150份关于黑人妇女的文件,这些文件要么以前没有编目,要么以这样一种方式编目,即黑人妇女的经历要么丢失,要么被抹去。这个项目对计算的使用是独一无二的,因为它允许对如此庞大的数据集进行定量调查,同时绘制定性评估图表,以确定文本是否以及如何捕捉非裔美国妇女的经历。使用一种称为“中间阅读”的技术,对文本的适用性进行验证。这种搜索、识别、救援和恢复(SeRRR)策略可以帮助信息管理者在数字化记录中更容易获得黑人女性的声音。SeRRR策略将允许学者使用一种带有元数据的“呼叫与响应”形式来理解黑人女性的生活(和死亡)经历,就像爱丽丝·沃克在寻找佐拉·尼尔·赫斯顿时所做的那样。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
In Search of Zora/When Metadata Isn’t Enough: Rescuing the Experiences of Black Women Through Statistical Modeling
Abstract This study used statistical topic modeling to examine 800,000 documents within HathiTrust and JSTOR databases to identify the kinds of discourses in books, poetry, newspapers, and journals related to African American women. We examined a range of conversations that emerged, between 1746 and 2014, revealing insights about, and from African American women. We identified a metadata revision methodology that served to rescue 150 documents for or about Black women that were either not previously cataloged or cataloged in such a way that Black women's experiences are either lost or erased. This project’s use of computation is unique in that it allows for the quantitative surveying of such a large dataset while charting a qualitative assessment to determine if and how texts capture the experiences of African American women. Using a technique called ‘intermediate reading’, texts are verified for their applicability. This strategy of search, recognition, rescue and recovery (SeRRR) may aid curators of information in making Black women’s voices more accessible within the digitized record. The SeRRR strategy will allow scholars to use a form of ‘call and response’ with metadata to understand the lived (and death) experiences of Black women as Alice Walker did during her search for Zora Neal Hurston.
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来源期刊
Journal of Library Metadata
Journal of Library Metadata Social Sciences-Library and Information Sciences
CiteScore
2.00
自引率
0.00%
发文量
13
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