Modeling STEM Workforce Dynamics Using Microsimulation & Multi-State Life Tables

描述（由申请人提供）：提高对科学，技术，工程和数学（STEM）领域代表性不足的少数民族的职业动态的了解对于维持和增加科学劳动力至关重要。少数群体是人口中迅速增长的一部分，在科学劳动力中的代表性不足。目前，它们是一种未充分利用的资源。增加少数民族在科学领域的存在的一个重要部分是增加他们在学术STEM劳动力中的代表性。为了确定哪些计划和政策是或将是最有效的维持和增加学术STEM劳动力，重要的是要了解进入和保留在学术和非学术STEM劳动力的动态。该项目将使用SPACE（复杂事件的随机人口分析）来估计多状态生命表函数。所产生的生命表模型将总结包括学术STEM劳动力的亚群的就业动态，并将根据美国劳动力人口构成的变化预测未来学术STEM工作者的培训需求。所使用的方法还将产生生命表估计值的置信区间。置信区间将允许假设检验来回答一些问题，例如种族/民族差异是否在职业生涯的早期就被观察到并持续存在，或者这些差异是否会随着时间的推移而积累。此外，SPACE还使用微观模拟程序，为代表性不足的少数群体（整体或单独）提供有关STEM劳动力动态的有用合成数据。 公共卫生相关性：STEM劳动力是维持研究所需的知识基础，技能水平和技术创新的重要组成部分，并将研究转化为健康问题的实际解决方案。拟议的研究提供了有用的工具，用于将政府资金投资于有助于改善美国人健康的STEM工作者的培训。

DESCRIPTION (provided by applicant): Improved knowledge of career dynamics for underrepresented minorities in science, technology, engineering, and mathematics (STEM) fields is critical to sustaining and increasing the scientific workforce. Minorities are a rapidly growing segment of the population and are underrepresented in the scientific workforce. Currently, they represent an underused resource. An important part of increasing the presence of minorities in the science fields is to increase their representation among the academic STEM workforce. In order to identify which programs and policies are or would be the most effective in sustaining and increasing the academic STEM workforce, it is important to understand the dynamics of entry into and retention in both the academic and non-academic STEM workforce. The project will use SPACE (Stochastic Population Analysis for Complex Events) to estimate multi-state life table functions. The life table models produced will summarize the employment dynamics for subpopulations comprising the academic STEM workforce and will project the need for training of future academic STEM workers in light of the changing demographic composition of the U.S. workforce. The methods used will also produce confidence intervals around life table estimates. Confidence intervals will allow hypothesis testing to answer questions such as whether race/ethnic differences are observed early in careers and persist or whether these differences accumulate over time. In addition, SPACE uses microsimulation procedures that will produce useful synthetic data on STEM workforce dynamics for underrepresented minority groups (as a whole or separately). PUBLIC HEALTH RELEVANCE: The STEM workforce is an important part of maintaining the knowledge base, skill level, and technological innovation necessary to research and translation of research into practical solutions to health problems. The proposed research provides useful tools for targeting investment of government funds in the training of STEM workers that contribute to improvement of American's health.