Development Core

项目概要/摘要-开发核心 发展核心（Dev Core）的主要目标是吸引和支持早期职业人口 科学家和不同的跨学科团队推出创新的研究项目。这些目标支持 我们对P2C基础设施支持提案的总体目标是设计、创建和使用新数据， 推进人口科学。Dev Core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内的工作生产力：（1）家庭和 对健康和福祉的代际影响;（2）生殖健康、生育率和浪漫 关系;和（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，社会研究所和大学的重要资源 密歇根为了实现Dev Core的目标，我们将用途：（1）试点项目种子赠款;（2）密集期 初级教师的研究指导;（3）资深的，有经验的同行评审的建议。该芯体的 活动的目的是明确提高所有PSC科学家的竞争力，同行评审的外部 经费与我们中心的统一功能相一致，我们的方法将侧重于使用来自 创新的大规模调查，新的行政/有机数据连接科学和实验设计， 干预措施。Axinn、Bailey和S.墨菲从我们的教师中被选中领导这个核心，因为他们每个人都 在一个或多个关键数据科学领域提供科学领导。

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.