# Administrative Core

> **NIH NIH P2C** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2021 · $163,730

## Abstract

Project Summary/Abstract – Administrative Core 
The primary objective of the Administrative Core of this P2C application from Population Studies Center (PSC) 
at the University of Michigan is to support research to design, create, and analyze new data that advance the 
population sciences by minimizing the administrative burden of managing research projects, disseminating 
faculty research, and promoting a collaborative environment in which faculty are exposed to new ideas and 
perspectives related to population dynamics research. The Administrative Core will coordinate the activities of 
all the P2C Cores in a way that builds cohesion within the Center and creates opportunities for new 
interdisciplinary collaborations. The Administrative Core serves as the hub through which the Development 
Core's initiatives to promote innovation and scientific impact within PSC's three Primary Research Areas are 
harmonized with the Scientific/Technical Core's initiatives to enhance research capabilities within the Center's 
primary approaches to data collection and analysis. In addition to coordinating the work of the other Cores, the 
Administrative Core organizes its own set of activities that are designed to facilitate the exchange of ideas 
across the faculty and spur innovation and collaboration.

## Key facts

- **NIH application ID:** 10226829
- **Project number:** 5P2CHD041028-20
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Sarah A. Burgard
- **Activity code:** P2C (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $163,730
- **Award type:** 5
- **Project period:** 2001-08-21 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10226829

## Citation

> US National Institutes of Health, RePORTER application 10226829, Administrative Core (5P2CHD041028-20). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10226829. Licensed CC0.

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