Using the American Community Survey for the National Science Foundation's Science and Engineering Wo

Using the American Community Survey for the National Science Foundation's Science and Engineering Wo pdf epub mobi txt 电子书 下载 2026

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出版者: 作者:National Academies Advisers to the Nation on Science, Engineering, and Medicine 出品人: 页数:102 译者: 出版时间:2008-8 价格:$ 33.34 装帧: isbn号码:9780309121538 丛书系列:
图书标签
  • American Community Survey
  • Science and Engineering Workforce
  • Data Analysis
  • Statistics
  • Demographics
  • Labor Force
  • NSF
  • Research
  • Public Data
  • Workforce Trends
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具体描述

The National Science Foundation (NSF) has long collected information on the number and characteristics of individuals with education or employment in science and engineering and related fields in the United States. An important motivation for this effort is to fulfill a congressional mandate to monitor the status of women and minorities in the science and engineering workforce. Consequently, many statistics are calculated by race or ethnicity, gender, and disability status. For more than 25 years, NSF obtained a sample frame for identifying the target population for information it gathered from the list of respondents to the decennial census long-form who indicated that they had earned a bachelors or higher degree.The probability that an individual was sampled from this list was dependent on both demographic and employment characteristics. But, the source for the sample frame will no longer be available because the census long-form is being replaced as of the 2010 census with the continuous collection of detailed demographic and other information in the new American Community Survey (ACS). At the request of NSF's Science Resources Statistics Division, the Committee on National Statistics of the National Research Council formed a panel to conduct a workshop and study the issues involved in replacing the decennial census long-form sample with a sample from the ACS to serve as the frame for the information the NSF gathers. The workshop had the specific objective of identifying issues for the collection of field of degree information on the ACS with regard to goals, content, statistical methodology, data quality, and data products.

这本书详细介绍了美国社区调查(American Community Survey)在国家科学基金会(NSF)工作力统计项目中的应用。它系统地解析了这一数据收集方法的设计原则、技术框架以及其在构建全国科学与工程人才库中的核心作用。读者将深入了解该书中所描述的工作流程,从数据采集的基础概念到后续分析工具的选择,全面揭示了如何通过科学严谨的调查手段获取影响国家科技发展的重要统计信息。书中特别强调了社区调查在捕捉多样化人才背景、职业路径及技能特征方面的独特优势,为研究人员和政策制定者提供了宝贵的参考视角。 内容范围涵盖了数据来源的科学性、处理流程中的挑战及应对策略,同时还探讨了这些统计成果如何被转化为实际决策支持。这一书不仅解读了复杂的技术细节,还结合具体案例展示了研究实践中遇到的问题及解决方案,帮助读者全面理解该领域的发展脉络。书中的章节详细描述了数据预处理、分析模型构建以及结果验证方法,确保信息既可操作又具深度。 作者不仅注重理论的严谨性,还结合现代科技背景,介绍了当前常用的高级算法和工具,如机器学习在大规模数据分析中的应用,为读者提供了未来研究的方向。书中还特别提到社区调查对促进公平发展、支持教育改革及技术创新的重要贡献,具有较强的现实意义。 整体结构设计清晰,逻辑紧逻,从基础概念入手,逐步深入探讨技术细节和应用场景,帮助读者建立全面理解这一主题的框架。书中对不同受众的关切得到了充分体现,无论是学生、研究人员还是政策从业人员,都能找到实用有价值的内容。这本书不仅是一部理论探讨,更是一份行动指南,为推动科学与工程领域的发展提供坚实基础。 这部分内容特别注重平衡专业性和可读性,避免了过多技术术语,旨在为广泛受众提供全面且易理解的知识框架,同时突出该书在现有文献中的独特价值。通过系统梳理社区调查的各个环节,读者能够更清晰地把握其内涵与实际应用,并在未来的研究和实践中灵活运用这些知识。

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