Gender in Political Sex Scandals in Contemporary Turkey: Women’s Agency and the Public Sphere

Sex scandals in politics lead to intense public debates about fundamental issues, such as morality, publicity, and privacy, rendering gender inequalities more visible than ever. This article aims to reveal the complex gendered dynamics of the political culture by looking at sex scandals in contemporary Turkey. The ways in which these scandals have been narrated, negotiated, and resolved among the public and political actors provide grounds for analysis about the nature of patriarchal dynamics regarding women’s agency and public credibility communicated through their sexuality in contemporary Turkey.     

Unearthing Loci that influence life span

It is known that certain hormones are involved in determining longevity (for example, insulin and insulin-like growth factor). Results presented in a paper published in this week's issue of Science allow us to add steroid hormones to this list. Anne Simon and colleagues show for the first time that a sterol hormone--ecdysone of the fly Drosophila melanogaster--regulates life span. In this Perspective, I discuss the implications of this result in the context of gene regulation and mechanisms of aging.     

Comparing the methods of measuring multi-rater agreement on an ordinal rating scale: a simulation study with an application to real data

Agreement among raters is an important issue in medicine, as well as in education and psychology. The agreement among two raters on a nominal or ordinal rating scale has been investigated in many articles. The multi-rater case with normally distributed ratings has also been explored at length. However, there is a lack of research on multiple raters using an ordinal rating scale. In this simulation study, several methods were compared with analyze rater agreement. The special case that was focused on was the multi-rater case using a bounded ordinal rating scale. The proposed methods for agreement were compared within different settings. Three main ordinal data simulation settings were used (normal, skewed and shifted data). In addition, the proposed methods were applied to a real data set from dermatology. The simulation results showed that the Kendall's W and mean gamma highly overestimated the agreement in data sets with shifts in data. ICC₄ for bounded data should be avoided in agreement studies with rating scales<5, where this method highly overestimated the simulated agreement. The difference in bias for all methods under study, except the mean gamma and Kendall's W, decreased as the rating scale increased. The bias of ICC₃ was consistent and small for nearly all simulation settings except the low agreement setting in the shifted data set. Researchers should be careful in selecting agreement methods, especially if shifts in ratings between raters exist and may apply more than one method before any conclusions are made.     

Disaster risk and artificial intelligence: A framework to characterize conceptual synergies and future opportunities

Artificial intelligence (AI) methods have revolutionized and redefined the landscape of data analysis in business, healthcare, and technology. These methods have innovated the applied mathematics, computer science, and engineering fields and are showing considerable potential for risk science, especially in the disaster risk domain. The disaster risk field has yet to define itself as a necessary application domain for AI implementation by defining how to responsibly balance AI and disaster risk. (1) How is AI being used for disaster risk applications; and how are these applications addressing the principles and assumptions of risk science, (2) What are the benefits of AI being used for risk applications; and what are the benefits of applying risk principles and assumptions for AI-based applications, (3) What are the synergies between AI and risk science applications, and (4) What are the characteristics of effective use of fundamental risk principles and assumptions for AI-based applications? This study develops and disseminates an online survey questionnaire that leverages expertise from risk and AI professionals to identify the most important characteristics related to AI and risk, then presents a framework for gauging how AI and disaster risk can be balanced. This study is the first to develop a classification system for applying risk principles for AI-based applications. This classification contributes to understanding of AI and risk by exploring how AI can be used to manage risk, how AI methods introduce new or additional risk, and whether fundamental risk principles and assumptions are sufficient for AI-based applications.     

Regulation of aging by germline stem cells

The author discusses a recent paper published in Science (see Arantes-Oliveira) that shows that germline stem cells in the worm Caenorhabditis elegans send a signal to a steroid hormone receptor and a forkhead-family member to stimulate reproduction and shorten longevity. The author compares the new results to previous findings in the fruit fly and discusses possible mechanisms behind the inverse relationship between reproduction and life-span extension.