"It Looks Good on Paper, But It Was Never Meant to Be Real": Mixed-Gender Events in the Paralympic Movement

Although the Paralympic Games have been around for over 60 years, women remain underrepresented in almost all aspects of the Paralympic Movement. It has been suggested that a way to increase women's involvement is through the implementation of mixed-gender events. On paper, this approach makes sense. However, when it comes to the implementation of mixed-gender opportunities for women, it is less clear how effective these events are in increasing participation by women in Para sport. Through document analysis and interviews with athletes and organizers of mixed-gender Paralympic sport, we explore the various strategies that four mixed-gender sports have used to address the issue of gender parity. Using critical feminist theories, we illustrate how larger social, political, and cultural ideas about gender influence women's experiences within these events and discuss the potential of using mixed-gender initiatives to address gender parity within the Paralympic Movement.

Feedback-based Self-improving CNN Algorithm for Breast Cancer Lymph Node Metastasis Detection in Real Clinical Environment

Digital pathology can be thought of as a model composed of 3 main elements; classification algorithm, Graphical User Interface (GUI) and the pathologists. Currently there is only a one way interaction from the classification algorithm to the pathologist. This paper, proposes an additional backward path which is a new feedback-based method, aimed to improve the performance of the classification algorithms by utilizing the feedback of the pathologists. The GUI developed for this purpose, is aimed to be simple and adaptive to different classification algorithms. The method showed significant improvement in the classification performance of the applied Convolutional Neural Network (CNN) algorithm. The 25% quantile of the probability score of the predictions increased from 0.48 to 0.89 and the median of the data increased from 0.95 to 0.99.