Bayesian shrinkage in mixture-of-experts models: identifying robust determinants of class membership

A method for implicit variable selection in mixture-of-experts frameworks is proposed. We introduce a prior structure where information is taken from a set of independent covariates. Robust class membership predictors are identified using a normal gamma prior. The resulting model setup is used in a finite mixture of Bernoulli distributions to find homogenous clusters of women in Mozambique based on their information sources on HIV. Fully Bayesian inference is carried out via the implementation of a Gibbs sampler

Are e-readers suitable tools for scholarly work?

This paper aims to offer insights into the usability, acceptance and limitations of e-readers with regard to the specific requirements of scholarly text work. To fit into the academic workflow non-linear reading, bookmarking, commenting, extracting text or the integration of non-textual elements must be supported. A group of social science students were questioned about their experiences with electronic publications for study purposes. This same group executed several text-related tasks with the digitized material presented to them in two different file formats on four different e-readers. Their performances were subsequently evaluated by means of frequency analyses in detail. Findings - e-Publications have made advances in the academic world; however e-readers do not yet fit seamlessly into the established chain of scholarly text-processing focusing on how readers use material during and after reading. Our tests revealed major deficiencies in these techniques. With a small number of participants (n=26) qualitative insights can be obtained, not representative results. Further testing with participants from various disciplines and of varying academic status is required to arrive at more broadly applicable results. Practical implications - Our test results help to optimize file conversion routines for scholarly texts. We evaluated our data on the basis of descriptive statistics and abstained from any statistical significance test. The usability test of e-readers in a scientific context aligns with both studies on the prevalence of e-books in the sciences and technical test reports of portable reading devices. Still, it takes a distinctive angle in focusing on the characteristics and procedures of textual work in the social sciences and measures the usability of e-readers and file-features against these standards.Comment: 22 pages, 6 figures, accepted for publication in Online Information Revie

Analysing Timelines of National Histories across Wikipedia Editions: A Comparative Computational Approach

Portrayals of history are never complete, and each description inherently exhibits a specific viewpoint and emphasis. In this paper, we aim to automatically identify such differences by computing timelines and detecting temporal focal points of written history across languages on Wikipedia. In particular, we study articles related to the history of all UN member states and compare them in 30 language editions. We develop a computational approach that allows to identify focal points quantitatively, and find that Wikipedia narratives about national histories (i) are skewed towards more recent events (recency bias) and (ii) are distributed unevenly across the continents with significant focus on the history of European countries (Eurocentric bias). We also establish that national historical timelines vary across language editions, although average interlingual consensus is rather high. We hope that this paper provides a starting point for a broader computational analysis of written history on Wikipedia and elsewhere

Face IT: Only Congress Can Preserve Privacy from the Pervasive Use of Facial Recognition Technology by Police

This Comment implores Congress to limit the development of law enforcement FRT databases. In Part II, the Comment describes facial recognition technology, examining its development and uses. This section describes how law enforcement compiles databases of faces. It concludes by exploring potential future applications of the technology. Part III discusses the privacy rights angle, answering why the American population should be concerned about—and why legislators should act to prevent—unchecked FRT-equipped law enforcement. Part IV addresses the current statutory framework that governs law enforcement’s use of FRT. In this section, the Comment points out the general lack of enacted legislation regarding the use of biometric information by law enforcement. The analysis shows that current statutory law is blind to the potential abuses of FRT-equipped law enforcement agencies, making the technology ripe for exploitation. In Part V, the Comment reviews Fourth Amendment jurisprudence and its applicability to FRT. Further, this section examines Supreme Court Fourth Amendment jurisprudence and concludes that recent decisions indicate that the Court would be unlikely to hold law enforcement’s uninhibited use of FRT unconstitutional. The section concludes that relying on the courts to protect citizens from technology’s encroachment on Fourth Amendment rights will result in millions of Americans losing privacy rights, even if the Court eventually changes its conception of what the Fourth Amendment protects. Part VI proffers a legislative solution to directly address FRT’s use by law enforcement. The solution requires congressional action that addresses privacy concerns while still allowing law enforcement to use the cutting-edge technology. The proposed solution has two primary prongs: first, amending the U.S. Code to limit the authorization of the FBI’s collection and compilation of facial images to those obtained by law enforcement and correctional entities; second, proposing a new law that vests responsibility for the collection of non-criminal identification information in the Department of Health and Human Services, or another non-law enforcement agency

The Impact of Differentiated Learning Activities on Student Engagement and Motivation in the English Language Arts Classroom

This 2021 study focused on student motivation and engagement when differentiated instruction was provided. By taking into consideration how each individual student learns, there is an opportunity to create an engaged and motivated student body as they each learn and understand in their own way. The purpose of this research study was to investigate how differentiated learning activities could affect student engagement and motivation. In other words, how does providing students the opportunity to learn in their preferred learning intelligence affect how they interact with the content and complete the work assigned? This study was conducted with two student groups in the 9th English course; one group was provided with differentiated learning activities catered to their learning intelligences and the second group was not provided the differentiated learning options. Students were sorted based on the class period they were assigned at the start of the school year. Through observations, interviews, and surveys, this study was able to examine how students’ engagement and motivation was affected by differentiated learning activities and used to guide future curriculum planning. Based on the data collected, there was little impact on student motivation and engagement in the 9th Grade English Language Arts classroom. Students in the differentiated group were motivated to complete their work more frequently than students in the non-differentiated. In terms of engagement, based on the student interviews, students from both groups felt they were motivated and engaged in the work assigned. These results provide us with a deeper understanding of what motivates and engages students in the classroom setting and how educators can better meet their needs