A linked and Enhanced SDR for Modeling Scientific Workforce Dynamics

描述（由申请人提供）：在美国，妇女在许多国家的代表性严重不足， 科学和工程（S&E）的学术和非学术职业领域。这是一个严重问题 因为妇女和少数群体构成了潜在科学工作者的重要组成部分，保持一支强大和充满活力的科学工作者队伍对经济和科学进步至关重要。要了解影响妇女和少数民族参与科技职业的因素，需要数据。人们还需要数据来制定和评估旨在增加妇女和少数民族在各级科技职业中的代表性的政策。该提案的主要目标是以新颖的方式利用现有的信息来源来解决有关S&E劳动力的关键问题。拟议的研究有四个具体目标，是实现以新的方式利用现有信息来源来解决S&E劳动力的关键问题的主要目标的重要步骤。这四个目标的基础将是一个科学劳动力动态的计算模型。首先，美国国家科学基金会的博士学位获得者的调查将随着时间的推移而联系起来，并与来自几个额外信息来源的随时间变化的协变量相结合。其次，我们将计算纵向调查的抽样权重，以便使用数据库来推断影响科学职业关键转变的因素。第三，该数据库将被用来估计参数的计算模型的动态科学劳动力在美国合并后的数据库将是独特的，其组成和有用性评估的主要假设的经验，妇女和少数民族在科学劳动力。四是研究纳入计划， 额外的数据来源，并设计与关键假设有关的重点调查。这项研究的方法和产品将产生独特的见解，并成为未来政策研究的关键组成部分，旨在鼓励妇女和少数群体参与科学劳动力。成功的政策，导致科学，工程和健康事业的可持续性和生产力的提高，预计将对科学研究，公共卫生和经济产生重大的积极影响。 公共卫生相关性：我们建议从公共资源中创建一个大量的数据库，并进行统计分析，以估计劳动力动态的计算模型。这项工作将导致更好地了解科学，工程和健康的职业道路，并有助于改善政策，以提高保留和生产力，特别是妇女和少数民族，从而改善科学，公共卫生和经济。

DESCRIPTION (provided by applicant): In the U.S., women are severely underrepresented in many academic and nonacademic career areas of science and engineering (S&E). This is a serious problem because women and minorities form a significant portion of the potential scientific workforce and maintaining a strong and vibrant scientific workforce is critical to economic and scientific progress. To understand the factors affecting participation of women and minorities in S&E careers one needs data. One also needs data in order to formulate and evaluate policies seeking to increase representation of women and minorities at all levels of S&E careers. The principal goal of this proposal is to use existing sources of information in novel ways to address key questions about the S&E workforce. The proposed study has four specific aims that are essential steps toward achieving the principal goal of using existing sources of information in novel ways to address key questions about the S&E workforce. Underlying the four aims will be a computational model of the dynamics of the scientific workforce. First, the NSF's Survey of Doctorate Recipients will be linked over time and enhanced with time varying covariate variables from several additional sources of information. Second, we will calculate longitudinal survey sampling weights for the purposes of using the database for inference concerning factors affecting key transitions in scientific careers. Third, the database will be used to estimate parameters in computational models of the dynamics of the scientific workforce in the U.S. The merged database will be unique in its composition and usefulness for assessing primary hypotheses about the experiences of women and minorities in the scientific workforce. Fourth, plans will be studied for incorporating additional data sources and for designing focused surveys related to key hypotheses.. The methods and products of this research will yield unique insights and be a key building block for future studies of polices and lifting interventions that aim to encourage the participation of women and minorities in the scientific workforce. Successful policies that lead to increased sustainability and productivity in science, engineering, and health careers are anticipated to have significant, positive impacts on science research, public health, and the economy. PUBLIC HEALTH RELEVANCE: We propose to create a substantial database from public sources and conduct statistical analyses to estimate a computational model of workforce dynamics. This work will lead to better understanding of scientific, engineering, and health career paths and help improve policies to increase retention and productivity, especially of women and minorities, thereby improving science, public health, and the economy.