LISA SERGIO: HOW MUSSOLINI'S "GOLDEN VOICE" OF PROPAGANDA CREATED AN AMERICAN MASS COMMUNICATION CAREER

In 1937 Lisa Sergio, "The Golden Voice" of fascist broadcasting from Rome, fled Italy for the United States. Though her mother was American, Sergio was classified as an enemy alien once the United States entered World War II. Yet Sergio became a U.S. citizen in 1944 and built a successful career in radio, working first at NBC and then WQXR in New York City in the days when women's voices were not thought to be appropriate for news or "serious" programming. When she was blacklisted as a communist in the early 1950s, Sergio compensated for the loss of radio employment by becoming principally an author and lecturer in Washington, D.C., until her death in 1989. This dissertation, based on her personal papers, is the first study of Sergio's American mass communication career. It points out the personal, political and social obstacles she faced as a woman in her 52-year career as a commentator on varied aspects of world affairs, religion and feminism. This study includes an examination of the FBI investigations of Sergio and the anti-communist campaigns conducted against her. It concludes that Sergio's success as a public communicator was predicated on both her unusual talents and her ability to transform her public image to reflect ideal American values of womanhood in shifting political climates.

Modeling the Effects of Habitat Fragmentation on the Movements of the Mongolian Gazelle in the Eastern Mongolian Steppe

The Mongolian gazelle, Procapra gutturosa, resides in the immense and dynamic ecosystem of the Eastern Mongolian Steppe. The Mongolian Steppe ecosystem dynamics, including vegetation availability, change rapidly and dramatically due to unpredictable precipitation patterns. The Mongolian gazelle has adapted to this unpredictable vegetation availability by making long range nomadic movements. However, predicting these movements is challenging and requires a complex model. An accurate model of gazelle movements is needed, as rampant habitat fragmentation due to human development projects - which inhibit gazelles from obtaining essential resources - increasingly threaten this nomadic species. We created a novel model using an Individual-based Neural Network Genetic Algorithm (ING) to predict how habitat fragmentation affects animal movement, using the Mongolian Steppe as a model ecosystem. We used Global Positioning System (GPS) collar data from real gazelles to “train” our model to emulate characteristic patterns of Mongolian gazelle movement behavior. These patterns are: preferred vegetation resources (NDVI), displacement over certain time lags, and proximity to human areas. With this trained model, we then explored how potential scenarios of habitat fragmentation may affect gazelle movement. This model can be used to predict how fragmentation of the Mongolian Steppe may affect the Mongolian gazelle. In addition, this model is novel in that it can be applied to other ecological scenarios, since we designed it in modules that are easily interchanged.