Our Innovation Networks project is an EHR Core Research (ECR) project funded by the National Science Foundation (NSF) to study the creation and diffusion of gender equity ideas in universities. We seek to better understand the evolution, operation, and outcomes of grantees from the NSF-funded ADVANCE program.
Since 2001, the NSF ADVANCE program has awarded projects that promote systemic change in support of gender equity in the academic science, technology, engineering, and math (STEM) workforce. Through this program, the NSF ADVANCE network consists of more than 1,500 individuals from over 195 universities and STEM organizations. From Principal Investigators (PIs) and co-PIs to project directors and managers, advisory board members, evaluators, STEM faculty at all ranks, and gender and diversity scholars, many of the participants are, or become, mid- and top-level administrators who share ideas about how to create equitable workplaces and practices.
Using a multi-method social network approach, the Innovation Networks project examines how the ADVANCE network multiplied the NSF’s initial investment through the exchange of ideas among STEM organizations. By combining network statistics, textual analysis, and qualitative methods the research has created an original dataset from multiple sources that documents and offers insight into how the creation, adoption, and diffusion of innovative ideas by this unique network of university leaders and scholars spurs comprehensive change in higher education institutions, including those without NSF ADVANCE awards.
Our research will benefit funding agencies and the broader community of higher education professionals who are interested in pursuing equity enhancement in higher education, especially within STEM fields.
ADVANCE co-authorship network and video that shows how it works!
Blog post on implicit bias and article on implicit bias & organizational change (Gender & Society)
The NSF ADVANCE Network of Organizations in the ADVANCE Journal Special Issue of 20 Years of ADVANCE--
This material is based upon work supported by the National Science Foundation under Grants No. 1836671 and 2000713. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.