课题基金 / 基金详情

Value-Added Postdoctoral Research on the Scientific Workforce

Value-Added Postdoctoral Research on the Scientific Workforce
科学劳动力的增值博士后研究
批准号:
1247079
负责人:
Alan Karr
金额:
$22.49万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-07-01 至 2016-06-30

项目摘要

项目成果

Alan Karr的其他基金

相似基金

相关文献

中文摘要
翻译
国家统计科学研究所(NISS)的这个博士后研究项目包括进行创新研究和创造有用的产品,这些产品不仅支持国家科学与工程统计中心(NCSES)的使命,而且满足国家的需求。从技术角度来看,这项研究由两个统计主题和两个关键的社会问题构成。第一个统计主题是描述综合和分析数据的新方法产生的不确定性,以满足数据收集预算下降和参与政府调查减少的时代的迫切需要。第二个主题集中在用真实数据进行实验,模拟感兴趣的现象,以便评估,在某些情况下,使方法进步。与调查有关的关键问题,如联系多少次以及以什么方式联系非受访者,太复杂了,无法通过分析处理,也不可能通过真实世界的实验来解决;因此,模拟实际上是唯一可用的实验室。具体的研究主题包括数据集成、预测、设计反馈的模型、数据质量感知的统计披露限制和成本数据质量权衡。所有联邦统计机构都将从这项研究中受益,它将产生创新的理论、新颖的方法和算法实现,以及数据集、分析、软件和洞察力,为未来的数据收集提供信息。更广泛的影响:社会问题是劳动经济学,因为它与科学、工程和卫生劳动力(SEHW)有关。了解工资、附加福利、流动性和培训/工作关系等现象对于保持美国在全球经济中的竞争力以及应对经济困难时期的挑战至关重要。第二个问题是老龄化,因为除了在美国以外出生的学生的作用,老龄化是在SEHW(可以说是整个社会)发生的最重要的现象。对于这两个问题,理解SEHW中观察到的行为的急剧丰富是一个深刻的机会。新的家庭结构、共享的职位以及各种形式的退休后就业都是我们这个时代的中心社会趋势。这个项目将产生新的见解,为未来的研究和健全的政策提供信息。
英文摘要
This postdoctoral research program at the National Institute of Statistical Sciences (NISS) comprises performing innovative research and creating usable products that not only support the mission of the National Center for Science and Engineering Statistics (NCSES) but also address the needs of the nation.From a technical perspective, the research is framed by two statistical themes and two key societal issues. The first statistical theme is characterization of uncertainties arising from novel methods of integrating and analyzing data, addressing a critical need in an era of declining data collection budgets and decreasing participation in government surveys. The second theme centers on conducting experiments with real data, simulating phenomena of interest in order to evaluate, and in some cases enable, methodological advances. Key issues regarding surveys, such as how many times and by what means to contact nonrespondents, are too complex to be treated analytically, and infeasible to address with real world experiments; therefore simulation is effectively the only laboratory available. Specific research topics include data integration, prediction, model to design feedback, data-quality-aware statistical disclosure limitation and cost data quality tradeoffs. All Federal statistical agencies stand to benefit from the research, which will produce innovative theory, novel, methodology and algorithmic implementations, together with datasets, analyses, software and insights that inform future data collections.Broader Impacts: The societal issues are labor economics as it relates to the science, engineering and health workforce (SEHW). Understanding phenomena such as salaries, fringe benefits, mobility and training/job relationships is crucial to maintaining the United States' competitiveness in a global economy, as well as to facing the challenges of difficult economic times. The second issue is aging, because other than the role of students born outside of the US, aging is the most important phenomenon taking place in the SEHW (and, arguably, in society as a whole). For both issues, understanding the dramatically increasing richness of observed behaviors within the SEHW is a profound opportunity. New kinds of family structures, shared positions, and an array of forms of post-first-retirement employment are among the central social trends of our times. This project will generate new insights that inform both future research and sound policy.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Postdoctoral Research in Support of SRS
Collaborative Research for Developing ATD: Bayesian Methods in Syndromic Surveillance: CAR Models and Computational Implementation
Workshop on Mathematical Geosciences
Collaborative Research: Dynamics for Social Networks Processes: Comparing Statistical Models with Intelligent Agents
海外基金