"Ensuring Legacy Data Access & Dissemination: Occupational Coding In The General Social Survey"

SES-1123510加州大学伯克利分校的Michael Hout和国家民意研究中心/NORCPeter Marsden，哈佛大学和国家民意研究中心/NORC确保遗产数据的访问和传播：一般社会调查中的职业代码摘要在过去的30年里，技术、商业和政府实践的变化极大地改变了美国的职业结构。我们的项目为了解新职业对当前经济和当代社会的影响提供了基础，并保存了记录这些根本性历史变化的独特数据关键。具体地说，该项目更新了从1970年代到现在的综合社会调查(GSS)中的职业和行业数据。该项目有几个目标。它们与国家科学基金会最近的主要建议相吻合，这些建议鼓励大型基础设施数据来源，如全球监测系统，以促进更多的数据获取和传播。这可以通过根据定义良好的协议提供数据和元数据来实现，这将允许数据访问、搜索、下载和文档的理想模式。该项目还满足了NSF的挑战，即将历史或遗留数据和元数据改造为机器可读。一旦保密和披露问题得到解决，这可能会打开大量数据用于传播和分析。为了实现这一目标，该项目将(1)取回GSS受访者？从GSS浪潮早期的实物问卷手稿中对他们的工作活动、职业和行业进行详细的逐字描述，(2)将它们转换为机器可读的形式，(3)重新编码以反映美国人口普查制定的2010年职业和2007年行业类别，以及(4)将社会经济分数和声望评估等外部数据附加到重新编码的类别中。数字化职业信息并在此过程中记录职业和行业类别的智力价值在于，它使研究人员能够随着时间的推移充分利用GSS中记录的职业和行业信息的潜力。这样做将提高GSS作为社会不平等、流动性和其他领域的比较和当代研究资源的价值，并保留其作为描述两代人以来美国社会趋势的历史数据库的日益增长的价值。通过将手写文本转换为机器可读文本来确保这些遗留数据的寿命，该项目还开发了一个逐字描述档案，允许未来的研究人员使用其他标准对其进行编码，包括可能在未来十年内推出的美国人口普查标准。广泛影响GSS是一个公共资源，也是一个科学资源。公众媒体，特别是报纸，广泛使用GSS。通过提高GSS中职业和行业信息的质量，并确保这些信息在一段时间内以一致的方式编码，该项目将帮助记者和公民了解社会趋势和模式。此外，高中和大学广泛使用GSS作为一种教学工具。当数据尽可能准确和准确地反映职业和行业之间的当代差异时，教师和学生将从该项目将产生的新数据产品中获得更多。

SES - 1123510Michael Hout, University of California, Berkeley, and National Opinion Research Center/NORCPeter Marsden, Harvard University and National Opinion Research Center/NORCEnsuring Legacy Data Access & Dissemination: Occupational Codes in the General Social SurveyAbstractIn the past thirty years, changes in technology, business, and government practice have substantially altered the American occupational structure. Our project provides a foundation to understand the consequences of new occupations on the current economy and contemporary society, and to preserve unique data key to documenting these fundamental historical changes. Specifically, this project modernizes the occupational and industry data in the General Social Survey (GSS) from the 1970s to the present time. The project has several goals. They dovetail recent key NSF recommendations that encourage large infrastructure data sources such as the GSS to facilitate increased data access and dissemination. This can be done by presenting data and metadata according to a well-defined protocol, which will allow desirable modes of data access, search, downloads, and documentation. The project also meets the NSF challenge to retrofit historical or legacy data and metadata to become machine readable. This will possibly open up vast amount of data for dissemination and analysis once issues of confidentiality and disclosure are resolved. To accomplish this goal, this project will (1) retrieve GSS respondents? detailed verbatim descriptions of their work activities, occupations, and industries from the physical questionnaire manuscripts from early GSS waves, (2) convert them into machine-readable form, (3) recode them to reflect 2010 occupation and 2007 industry categories developed by the U.S. Census, and (4) attach external data such as socioeconomic scores and prestige assessments to the recoded categories. The intellectual merit of digitizing occupational information and recoding occupational and industry categories in the process is that it enables researchers to use the full potential of the occupation and industry information recorded in the GSS over time. Doing so will enhance the value of the GSS as a resource for comparative and contemporary research on social inequality, mobility, and other fields and preserve its growing value as a historical database describing trends in U.S. society over two generations. Ensuring the longevity of such legacy data by converting hand-written text into machine-readable text, the project also develops an archive of verbatim descriptions that will allow future researchers to code them using other standards, including U.S. Census standards that may become available in upcoming decades.Broader ImpactsThe GSS is a public resource as well as a scientific one. Public media, especially newspapers, make extensive use of the GSS. By improving the quality of occupational and industry information in the GSS and ensuring that it is coded in a consistent way over time, this project will help journalists and citizens make sense of social trends and patterns. Also, high schools and colleges make extensive use of the GSS as a teaching tool. Teachers and students will get more out of these exercises from the new data products this project will produce when data reflect contemporary distinctions among occupations and industries as accurately and precisely as possible.