Development Core

项目摘要/摘要-开发核心 发展核心(开发核心)的主要目标是吸引和支持早期就业人口 并由不同的跨学科团队发起创新研究项目。这些目标支持 我们的P2P基础架构支持建议书的总体目标是设计、创建和使用新数据以 推进人口科学。开发人员核心服务将增强科学影响力、创新和 人口研究中心(PSC)的三个主要研究领域：(1)家庭和 代际对健康和幸福的影响；(2)生殖健康、生育和浪漫 (3)人口健康、生命历程和生物社会过程。核心的活动将 利用PSC、社会研究所和华盛顿大学的重要资源 密歇根州。为了实现开发人员核心的目标，我们将使用：(1)试点项目种子赠款；(2)密集阶段 为初级教员提供研究指导；以及(3)资深、有经验的同行评议提案。核心的 活动明确旨在提高所有PSC科学家在同行评议的外部环境中的竞争力 资金问题。与我们中心的统一功能一致，我们的方法将专注于使用来自 创新的大规模调查、新的行政/有机数据--将科学和实验设计和 干预措施。艾克辛、贝利和S·墨菲是从我们的教职员工中挑选出来领导这个核心的，因为他们各自 在这些关键数据科学领域中的一个或多个领域提供科学领导。

Project Summary/Abstract – Development Core The main objectives of the Development Core (Dev Core) are to engage and support early career population scientists and launch innovative research projects by diverse interdisciplinary teams. These objectives support the overall aim of our proposal for P2C infrastructure support, which is to design, create, and use new data to advance population science. The Dev Core services will enhance the scientific impact, innovation, and productivity of work within the Population Studies Center's (PSC) three primary research areas: (1) Family and Intergenerational influences on Health and Wellbeing; (2) Reproductive Health, Fertility and Romantic Relationships; and (3) Population Health, the Life Course and Biosocial Processes. The Core's activities will harness the significant resources available at PSC, the Institute for Social Research, and the University of Michigan. To achieve the Dev Core's aims, we will use: (1) pilot project seed grants; (2) periods of intensive research mentoring for junior faculty; and (3) senior, experienced peer review of proposals. The Core's activities are explicitly designed to increase all PSC scientists' competitiveness for peer-reviewed external funding. Consistent with the unifying features of our center, our approach will focus on the use of data from innovative, large-scale surveys, new administrative/organic data-linking science and experimental designs and interventions. Axinn, Bailey, and S. Murphy were selected from our faculty to lead this Core because they each provide scientific leadership in one or more of these key data science areas.