Gender and Representation: Economic Performance and the Emergence of Women in State Politics

A plethora of literature in gender and representation has been devoted to understanding disparities that occur during campaigns. More recently, the shift has been toward candidate emergence and the decision of individual women to run in the United States. In this vein, we are curious whether women are likely to run for office following times of economic prosperity or disparity, respectively. We hypothesize that when the state of the economy is generally decreasing in terms of declining GDP per capita and growing unemployment rates, fewer women will emerge to run for office. In times of worse economic performance, we argued that voters will show less interest in a broader range of topics besides those that will directly affect their personal economic well-being. This will happen because they feel less safe in their economic position. We suggest that this will lead to fewer women feeling encouraged to run for office because they anticipate a lower probability of winning. This may be attributable to asymmetrical partisan gender gaps and decreased confidence to run on platforms typically supported by female politicians like issues affecting women, children, and families, and the promotion of the arts, rather than an economic focus typical to male campaigns. We analyzed state level data from 2009 to 2018 looking at state GDP per capita, unemployment rate by state, incumbency, and the number of women running for state executive in each state. We find initial support for part of the hypothesis. Unemployment rates seem to have a statistically significant and negative affect on female candidate emergence. GDP per capita was a statistically significant measure, however this measure did not directly play a role in the relationship between candidate emergence. The results of this study offer insight and speculation into female candidate emergence and more generally for understanding gender and representation

Nature\u27s Humans: Presence, Absence, Transformation -- Photography Selected by Chris Jackson

Photography selected by Chris Jackson, featuring the following artists: Bill Bodish Cynthia Chang Phuong Phan Janet Powel

Myth Understanding

Myth Understanding is a prototype of an interactive educational program geared towards elementary school children. It provides self-paced instruction, mixing animation, graphics, and sound with information pertaining to earth science. Mythological characters from ancient Greece are sources which provide the child with scientific as well as historic information. In effect, children learn about ancient Greek mythology as they discover the mysteries and makeup of the earth. Children are given the flexibility to decide on what information to view ac cording to their own personal preference. Meticulous attention was given to the artwork interface design and layout. Myth Understanding incorporates multimedia design to make Greek mythology and earth science come alive, exhibiting facts that are not only illustrative, but at the same time entertaining and informative. The evolution of Myth Understanding will be explored in the following chapters. Initial concepts, research, character development and tqaechnical considerations will be addressed. My main goal is to stimulate, educate, and entertain children about Greek mythology and earth science. Myth Under standing provides them with a passport to the time of myths and magic

El valor del trabajo doméstico en Canadá, 1986

Sin resume

Battlegrounds of environmental change

The Thames catchment encompasses one of Europe’s largest cities, the UK’s principal aquifer, an extensive zone of coastal interaction and much else. It presents a unique conjunction of geological, hydrogeological, environmental and socio-economic factors that are intrinsically linked by the effects of environmental change and the pressures of developmen

Extracting 3D parametric curves from 2D images of Helical objects

Helical objects occur in medicine, biology, cosmetics, nanotechnology, and engineering. Extracting a 3D parametric curve from a 2D image of a helical object has many practical applications, in particular being able to extract metrics such as tortuosity, frequency, and pitch. We present a method that is able to straighten the image object and derive a robust 3D helical curve from peaks in the object boundary. The algorithm has a small number of stable parameters that require little tuning, and the curve is validated against both synthetic and real-world data. The results show that the extracted 3D curve comes within close Hausdorff distance to the ground truth, and has near identical tortuosity for helical objects with a circular profile. Parameter insensitivity and robustness against high levels of image noise are demonstrated thoroughly and quantitatively