Disaggregating conservative Protestant groups in Northern Ireland: Overlapping categories and the importance of a born-again self-identification

Rather than treating conservative Protestantism as a homogenous phenomenon, recent literature has underlined the importance of disaggregating this group to illuminate important attitudinal and behavioral differences between conservative Protestants. However, the methods used to empirically operationalize conservative Protestantism have not always been able to capture variations within the groupings. Based on analysis of the 2004 Northern Ireland Life and Times Survey, we argue that religious self-identification is a more useful way of analyzing conservative Protestant subgroups than denomination or religious belief. We show that many of these identifications are overlapping, rather than stand-alone, religious group identifications. Moreover, the identification category of born-again has seldom been included in surveys. We find having a born-again identification to be a better predictor than the more frequently asked fundamentalist and evangelical categories of the religious and social beliefs that are seen as indicative of conservative Protestantism.

A Diagnostic System Using Broad Categories With Clinicaly Relevant Specifiers: Lessons for ICD-10

A diagnostic system for ICD-11 is proposed which commences with broad reorganization and simplification of the current categories and the use of clinically relevant specifiers. Such changes have implications for the positioning of diagnostic groups and lead to a range of possibilities for improving terminology and the juxtaposition of individual conditions. The development of ICD-11 provides the first opportunity in almost two decades to improve the validity and reliability of the international classification system. Widespread change in broad categories and criteria cannot be justified by research that has emerged since the last revision. It would also be disruptive to clinical practice and might devalue past research work. However, the case for reorganization of the categories is stronger and has recently been made by an eminent international group of researchers (Andrews et al., 2009). A simpler, interlinked diagnostic system is proposed here which is likely to have fewer categories than its predecessor. There are major advantages of such a system for clinical practice and research and it could also produce much needed simplification for primary care (Gask et al., 2008) and the developing world (Wig, 1990; Kohn et al., 2004).

From hyperactive children to ADHD adults:Observations on the expansion of medical categories

Medicalization is by definition, about the extension of medical boundaries. Analogous to "domain expansion," extant medicalized categories can expand to become broader and more inclusive. This paper examines the emergence of Attention Deficit Hyperactivity Disorder (ADHD) in adults. ADHD, commonly known as Hyperactivity, became established in the 1970s as a diagnosis for children; it expanded first to include "adult hyperactives" and, in the 1990s, "ADHD Adults." This allowed for the inclusion of an entire population of people and their problems that were excluded by the original conception of hyperactive children. We show how lay, professional, and media claims help establish the expanded diagnostic category. We identify particular aspects of the social context that contributed to the rise of adult ADHD and outline some of the social implications of ADHD in adults, especially the medicalization of underperformance and the availability of new disability rights. Adult ADHD serves as an exemplar of several cases of diagnostic expansion, an important avenue of increasing medicalization.

Model categories for orthogonal calculus

We restate the notion of orthogonal calculus in terms of model categories. This provides a cleaner set of results and makes the role of O(n)-equivariance clearer. Thus we develop model structures for the category of n-polynomial and n-homogeneous functors, along with Quillen pairs relating them. We then classify n-homogeneous functors, via a zig-zag of Quillen equivalences, in terms of spectra with an O(n)-action. This improves upon the classification theorem of Weiss. As an application, we develop a variant of orthogonal calculus by replacing topological spaces with orthogonal spectra.

Discriminating Taxonomic Categories and Domains in Mental Simulations of Concepts of Varying Concreteness

Most studies of conceptual knowledge in the brain focus on a narrow range of concrete conceptual categories, rely on the researchers' intuitions about which object belongs to these categories, and assume a broadly taxonomic organization of knowledge. In this fMRI study, we focus on concepts with a variety of concreteness levels; we use a state of the art lexical resource (WordNet 3.1) as the source for a relatively large number of category distinctions and compare a taxonomic style of organization with a domain-based model (associating concepts with scenarios). Participants mentally simulated situations associated with concepts when cued by text stimuli. Using multivariate pattern analysis, we find evidence that all Taxonomic categories and Domains can be distinguished from fMRI data and also observe a clear concreteness effect: Tools and Locations can be reliably predicted for unseen participants, but less concrete categories (e.g., Attributes, Communications, Events, Social Roles) can only be reliably discriminated within participants. A second concreteness effect relates to the interaction of Domain and Taxonomic category membership: Domain (e.g., relation to Law vs. Music) can be better predicted for less concrete categories. We repeated the analysis within anatomical regions, observing discrimination between all/most categories in the left middle occipital and temporal gyri, and more specialized discrimination for concrete categories Tool and Location in the left precentral and fusiform gyri, respectively. Highly concrete/abstract Taxonomic categories and Domain were segregated in frontal regions. We conclude that both Taxonomic and Domain class distinctions are relevant for interpreting neural structuring of concrete and abstract concepts.

Homological Localisation of Model Categories

One of the most useful methods for studying the stable homotopy category is localising at some spectrum E. For an arbitrary stable model category we introduce a candidate for the E–localisation of this model category. We study the properties of this new construction and relate it to some well–known categories.

Inferring and Exploiting Categories for Next Location Prediction

Predicting the next location of a user based on their previous visiting pattern is one of the primary tasks over data from location based social networks (LBSNs) such as Foursquare. Many different aspects of these so-called “check-in” profiles of a user have been made use of in this task, including spatial and temporal information of check-ins as well as the social network information of the user. Building more sophisticated prediction models by enriching these check-in data by combining them with information from other sources is challenging due to the limited data that these LBSNs expose due to privacy concerns. In this paper, we propose a framework to use the location data from LBSNs, combine it with the data from maps for associating a set of venue categories with these locations. For example, if the user is found to be checking in at a mall that has cafes, cinemas and restaurants according to the map, all these information is associated. This category information is then leveraged to predict the next checkin location by the user. Our experiments with publicly available check-in dataset show that this approach improves on the state-of-the-art methods for location prediction.