Developing a Scientific Workforce Analysis and Modeling Framework

开发科学的劳动力分析和建模框架

• 批准号: 8286208
• 负责人: Joshua Hawley
• 金额: $ 25.94万
• 依托单位: OHIO STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2014-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8286208
• 关键词: Academia; Accounting; Achievement; Affect; Area; Behavior; Biological Models; Characteristics; Communities; Complex; Consultations; Data; Data Collection; Data Set; Decision Making; Economics; Ecosystem; Education; Feedback; Funding; Future; Goals; Health Sciences; Industry; Institution; International; Internet; Intervention; Knowledge; Literature; Longitudinal Surveys; Mathematics; Medical; Medicine; Methods; Modeling; Pattern; Performance; Policies; Policy Maker; Population; Principal Investigator; Process; Publishing; Research; Research Personnel; Resolution; Running; STEM career; STEM student; Science; Science, Technology, Engineering and Mathematics Education; Societal Factors; Staging; Structure; Students; System; Talents; Time; United States National Institutes of Health; Universities; career; collected works; design; driving force; flexibility; innovation; insight; interest; model development; models and simulation; network models; programs; public health relevance; science education; simulation; sound; technological innovation; tool; trend

DESCRIPTION (provided by applicant): This research proposes to develop a layered, extensible system modeling framework representing the diverse, complex, and interdependent institutions and policies that influence the quality and availability of the U.S. academic medicine/health sciences (M/HS) workforce. This approach avoids the tendency to "lock in" to a single model that may be appropriate only for certain types of analysis by developing multiple models at different levels of resolution, using a variety of modeling tools. Model development will be an iterative and recursive process, starting with top-down modeling to develop the key insights needed and guide data collection, which will in turn suggest the detailed model structure required to make sense of the empirical findings. The choice of system domains and behaviors to model will be guided by consultations with subject-matter experts and coordination with other efforts funded under this solicitation. Quantitative associations will be established through review of the published literature and examination of extant datasets, including a number of large-scale longitudinal surveys not heretofore available to modelers. Selected issues and policy scenarios will be investigated via simulation runs. Model interfaces will be developed that align with the needs and capacities of key stakeholders, such as NIH managers and policymakers. The long-term goal of this research is to encourage the use of integrated simulation modeling tools within the M/HS community to support the establishment of sound policies and practices for workforce improvement and beneficial interventions in education, recruitment and retention. Such models have the potential to enhance decision-making processes by allowing leaders to (a) account for historical patterns in the M/HS education systems, (b) examine what might have occurred under other historical conditions, (c) explore what may happen in a variety of future scenarios, (d) identify methods and/or points of intervention with higher leverage (stronger influence) over system behavior, (e) characterize the time constants applicable to various actions or changes, and (f) identity the most critical areas for future research and data collection. PUBLIC HEALTH RELEVANCE: Patterns and trends in U.S. student science and mathematics abilities and career selections raise concern about the future supply of well-prepared people entering the nation's medical and health sciences workforce. This project will rigorously model the complex web of factors influencing these patterns and trends and develop tools to assist national leaders in designing more effective policies and programs aimed at assuring this vital flow of talent.

描述（由申请人提供）：本研究建议开发一个分层，可扩展的系统建模框架，代表影响美国学术医学/健康科学（M/HS）劳动力的多样化，复杂和相互依存的机构和政策。这种方法避免了使用一种模型“锁定”到单个模型中的趋势 多种建模工具。模型开发将是一个迭代和递归过程，从自上而下的建模开始，以开发所需的关键见解并指导数据收集，这反过来又提出了理解经验发现所需的详细模型结构。系统领域和模型行为的选择将由与主题专家的磋商以及与此招标资助的其他努力进行协商。定量关联将通过审查已发表的文献和现有数据集的检查，包括许多迄今为止可供建模者可用的大规模纵向调查。选定的问题和政策方案将通过模拟运行进行研究。将开发模型接口，以与NIH经理和政策制定者等主要利益相关者的需求和能力保持一致。这项研究的长期目标是鼓励在M/HS社区中使用综合模拟建模工具，以支持建立合理的政策和实践，以改善劳动力，并在教育，招聘和保留方面进行有益的干预措施。这样的模型有可能通过允许领导者（a）说明M/HS教育系统中的历史模式来增强决策过程，（b）检查在其他历史条件下可能发生的事情，（c）探索可能发生的事情在各种未来的情况下，（d）确定对系统行为具有更高杠杆作用（更强影响）的方法和/或干预点，（e）表征适用于各种行动或更改的时间常数，以及（f）身份最多。未来研究和数据收集的关键领域。 公共卫生相关性：美国学生科学和数学能力和职业选择的模式和趋势引起了人们对进入该国医学和健康科学劳动力的未来供应的关注。该项目将严格地模拟影响这些模式和趋势的复杂因素网，并开发工具，以帮助国家领导者设计旨在确保这种至关重要的人才流动的更有效的政策和计划。