A linked and Enhanced SDR for Modeling Scientific Workforce Dynamics

描述(由申请者提供)：在美国，女性在许多地方的代表性严重不足 科学和工程的学术和非学术职业领域(S和E)。这是一个严重的问题。 由于妇女和少数群体构成了潜在科学劳动队伍的重要组成部分，保持一支强大和充满活力的科学劳动队伍对经济和科学进步至关重要。要了解影响女性和少数民族参与S职业生涯的因素，需要数据。人们还需要数据，以便制定和评估旨在增加妇女和少数民族在S和易卜拉欣各级职业生涯中的代表性的政策。这项建议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员工队伍的关键问题。这项拟议的研究有四个具体目标，是实现以新颖方式利用现有信息来源解决有关S&E员工队伍的关键问题这一主要目标的关键步骤。在这四个目标的基础上，将建立一个科学劳动力动态的计算模型。首先，NSF对博士学位获得者的调查将随着时间的推移而联系在一起，并通过几个额外信息来源的时变协变量来增强。其次，我们将计算纵向调查抽样权重，目的是使用数据库来推断影响科学职业生涯关键转变的因素。第三，该数据库将用于估计美国科学劳动力动态的计算模型中的参数。合并后的数据库在其组成和评估有关女性和少数族裔在科学劳动力中的经历的基本假设方面将是独特的。第四，研究合并方案。 其他数据来源和设计与关键假设相关的重点调查。这项研究的方法和产品将产生独特的见解，并成为今后研究旨在鼓励妇女和少数群体参与科学工作的政策和提高干预措施的关键基石。能够提高科学、工程和卫生事业的可持续性和生产力的成功政策，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：我们建议从公共来源创建一个实质性的数据库，并进行统计分析，以估计劳动力动态的计算模型。这项工作将有助于更好地了解科学、工程和卫生职业道路，并有助于改进政策，以提高留住和生产率，特别是妇女和少数群体的留住和生产率，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.