Active learning approaches for labeling text: review and assessment of the performance of active learning approaches

Supervised machine learning methods are increasingly employed in political science. Such models require costly manual labeling of documents. In this paper, we introduce active learning, a framework in which data to be labeled by human coders are not chosen at random but rather targeted in such a way that the required amount of data to train a machine learning model can be minimized. We study the benefits of active learning using text data examples. We perform simulation studies that illustrate conditions where active learning can reduce the cost of labeling text data. We perform these simulations on three corpora that vary in size, document length, and domain. We find that in cases where the document class of interest is not balanced, researchers can label a fraction of the documents one would need using random sampling (or “passive” learning) to achieve equally performing classifiers. We further investigate how varying levels of intercoder reliability affect the active learning procedures and find that even with low reliability, active learning performs more efficiently than does random sampling

Fragmented realities: The ‘sectarianisation’of space among Iraqi Shias in London

How do the spaces we inhabit shape our lived experiences? And how do those lived experiences in turn come to shape and influence our political subjectivity? Such questions are rendered all the more important in studies of migrant or diaspora populations who, by definition, conduct their daily lives in spaces and places that were initially alien to them. The way in which migrants interact with the spaces around them can tell us much about the social, political, and religious engagements they invest in, as well as the very real way in which they experience their local milieu. Through a detailed study of Iraqi Shiis living in London, specifically in the north-western borough of Brent, this article will seek to trace the ways in which religious institutions have carved up the physical and social landscape of north-west London in ways that have enduring effect on the communities with which they engage. The increasing diversification of different religious establishments, I argue, has led to a fragmentation of the city-as-lived, in which the vast majority of practising Iraqi Shiis engage with only small isolated pockets of the urban environment on a daily basis. Moreover, the growing number of specifically Shia schools, charities, mosques, community centres and other such institutions has resulted in what I call a ‘sectarianisation’ of space in Brent, in which individuals hailing from different branches of Islam inhabit different spaces within the city despite often living within metres of each other. Drawing on a mixture of interviews, participant observation, and mapping techniques, I bring together theory and practice in order to sketch out the ways migrant lives can come to be localised in certain spaces, and what that can ultimately mean in terms of their political subjectivity and engagement

Intra-individual methylomics detects the impact of early-life adversity.

Genetic and environmental factors interact during sensitive periods early in life to influence mental health and disease via epigenetic processes such as DNA methylation. However, it is not known if DNA methylation changes outside the brain provide an "epigenetic signature" of early-life experiences. Here, we used a novel intra-individual approach by testing DNA methylation from buccal cells of individual rats before and immediately after exposure to one week of typical or adverse life experience. We find that whereas inter-individual changes in DNA methylation reflect the effect of age, DNA methylation changes within paired DNA samples from the same individual reflect the impact of diverse neonatal experiences. Genes coding for critical cellular metabolic enzymes, ion channels, and receptors were more methylated in pups exposed to the adverse environment, predictive of their repression. In contrast, the adverse experience was associated with less methylation on genes involved in pathways of death and inflammation as well as cell-fate-related transcription factors, indicating their potential up-regulation. Thus, intra-individual methylome signatures indicate large-scale transcription-driven alterations of cellular fate, growth, and function

Use of the All Patient Refined-Diagnosis Related Group (APR-DRG) Risk of Mortality Score as a Severity Adjustor in the Medical ICU

Objective To evaluate the performance of APR-DRG (All Patient Refined—Diagnosis Related Group) Risk of Mortality (ROM) score as a mortality risk adjustor in the intensive care unit (ICU). Design Retrospective analysis of hospital mortality. Setting Medical ICU in a university hospital located in metropolitan New York. Patients 1213 patients admitted between February 2004 and March 2006. Main results Mortality rate correlated significantly with increasing APR-DRG ROM scores (p < 0.0001). Multiple logistic regression analysis demonstrated that, after adjusting for patient age and disease group, APR-DRG ROM was significantly associated with mortality risk in patients, with a one unit increase in APR-DRG ROM associated with a 3-fold increase in mortality. Conclusions APR-DRG ROM correlates closely with ICU mortality. Already available for many hospitalized patients around the world, it may provide a readily available means for severity-adjustment when physiologic scoring is not available