The International Affairs Review is a non-profit, peer-reviewed, academic
journal published biannually in Washington, DC. It is an independent,
graduate student run publication sponsored by the Elliott School of
International Affairs at the George Washington University.
The International Affairs Review is a non-profit, peer-reviewed, academic
journal published biannually in Washington, DC. It is an independent,
graduate student run publication sponsored by the Elliott School of
International Affairs at the George Washington University.
Established in 2016, the GW Undergraduate Review (GWUR) is the premier publication of research from undergraduate students at the George Washington University. Our mission is to promote undergraduate research on GW’s campus through events, workshops, and the publication of a peer-reviewed...
This report is a collaborative effort from researchers at the Brookings Institution, Fannie Mae, Georgetown University and the George Washington University. We are particularly grateful to the Trachtenberg School of Public Policy and Public Administration and the George Washington Institute for...
This study explores the effect of ecological factors such as plant density, shade, location, and vulnerability to foot traffic on the health of plant-pollinator relationship. By monitoring numerous pollinator populations during Summer of 2018, we gained an understanding of GW's current...
In 2019, about fifty years after the Feminist art movement, women's art work in major museums is still minimal at best. For years groups like the Guerrilla Girls publicly protested and relied on quantitative data to call attention to the disparity that plagues most fine art spaces. Despite an...
Understanding Climate Change is important from a practical perspective, because it is related to the environment we live in and the health of the planet. Understanding Climate Change is also important from an academic perspective because it is related to public opinion on politics and economics....
Learning embedding functions, which map semantically related images to nearby locations in a feature space supports a variety of image retrieval tasks. In this work, we propose a novel, generalizable and fast method to define a family of embedding functions that can be used as an ensemble to give...