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

“确保遗留数据访问

• 批准号: 1123510
• 负责人: Michael Hout
• 金额: $ 50万
• 依托单位: National Opinion Research Center
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-15 至 2016-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1123510&HistoricalAwards=false
• 关键词: Ensuring; Legacy; Data; Access; &amp

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.

SES -1123510 Michael Hout，加利福尼亚大学，伯克利分校，国家舆论研究中心/Norcpeter Marsden，哈佛大学和国家舆论研究中心/NORCENSUNSRING LEGACY数据访问与传播：过去三十年来，一般社交调查局的职业代码在过去的三十年中，政府实践的变化，美国的商业和美国实践的变化已经实质性地改变了美国的实践。我们的项目为了解新职业对当前经济和当代社会的后果提供了基础，并保留了记录这些基本历史变化的独特数据关键。具体而言，该项目将从1970年代到现在的一般社会调查（GSS）中的职业和行业数据现代化。 该项目有几个目标。他们为NSF的最新关键建议提供了帮助，该建议鼓励大型基础设施数据源（例如GSS），以促进增加数据访问和传播。 这可以通过根据定义明确的协议显示数据和元数据来完成，这将允许所需的数据访问，搜索，下载和文档模式。 该项目还符合NSF挑战，以改造历史或传统数据，并符合元数据，以使机器可读。 一旦解决了机密性和披露问题，这可能会打开大量数据进行传播和分析。为了实现这一目标，该项目将（1）检索GSS受访者？从早期GSS浪潮中的身体问卷手稿中对其工作活动，职业和行业的详细逐字描述，（2）将它们转换为可读机器的形式，（3）将其转化为反映2010年的职业和2007年由美国普法员开发的2007年行业类别，以及（4）附加外部数据，例如社会研究评估和PRESTIGE CORESED CORESED CORESED CORESED COREDECTIGES COREDED RECODEDSED。在此过程中，数字化职业信息以及重新编码职业和行业类别的智力优点在于，它使研究人员能够随着时间的推移使用GSS中记录的职业和行业信息的全部潜力。 这样做将提高GSS的价值，作为对社会不平等，流动性和其他领域的比较和当代研究的资源，并保留其不断增长的价值作为描述两代美国社会趋势的历史数据库。该项目还通过将手写文本转换为可读的文本来确保此类遗产数据的寿命，还开发了逐字描述的档案，该档案将使未来的研究人员使用其他标准来对其进行编码，其中包括在接下来的几十年中可能可用的美国人口普查标准。公共媒体，尤其是报纸，广泛使用GSS。通过提高GSS中职业和行业信息的质量，并确保其随着时间的推移以一致的方式编码，该项目将帮助记者和公民了解社会趋势和模式。此外，高中和学院广泛使用GSS作为教学工具。当数据能够尽可能准确，精确地反映出职业和行业之间的当代区别时，教师和学生将从新数据产品中获得更多这些练习。