Genetic Indigenisation in ‘The People of the British Isles’

In 2007, Channel 4 screened Face of Britain, a documentary about the genetic mapping of Britain. Face of Britain promised to reveal ‘who we really are’ by tracing genetic links back to ancient Celts, Anglo-Saxons, Vikings and Normans. This article situates Face of Britain within the wider racial and national politics that it is invariably caught up in, and examines how ‘race’ and racial thinking are reconfigured in ways that are both ‘old’ and ‘new’. Face of Britain constitutes an interesting case study to examine how ideas of indigeneity are produced and naturalised in scientific discourses and practices. Here, indigeneity is mobilised through three sub-narratives: the ‘vanishing indigene’; the promise of facial recognition; and DNA and national relatedness. The analysis reveals how some people of the British Isles are naturalised as indigenous by virtue of their ancestral presence in this land through a combination of genetic and photographic technologies. In short, blood and soil are intertwined, with genes as mediators between ancestors and contemporary inhabitants of Britain. Furthermore, the invisible genetic connection is made visible through the creation of ‘average faces of Britain’, which is considered here as a contemporary version of physiognomy. In conclusion, Face of Britain testifies to the reconfiguration of ‘racial thinking’ in contemporary science, through what ultimately amounts to the genetic indigenisation of white Britons. Consequently, this study lends itself to racialised politics of land claims that resonate with, but are different from, indigenous politics in other contexts, namely with regards to the relationship to whiteness.     

Personhood: Elusive But Not Illusory

Bioethics as a field has been fortunate that its values and concerns have mirrored the values and concerns of society. In light of the September 11th attacks, it is possible that we are witnessing the beginning of a transition in American culture, one fraught with implications for bioethics. The emphasis on autonomy and individual rights may come to be tempered by greater concern over the collective good. Increased emphasis on solidarity over autonomy could greatly alter public response to research abuses aimed at defense from bioterrorism, to privacy of genetic information, and to control of private medical resources to protect the public health.     

Perception of risk in genetic counseling

Abstract

Genetic counseling is a psychological process of communicating and perceiving information about risks. As such, it is important to assess how information is understood by counselees and how psychological factors affect risk perception. Subjects were 76 patients at a genetic clinic whose understanding of genetic counseling was assessed, along with their motivation and way of thinking about risks. Results indicated that subjective interpretations of recurrence risks are better predictors of their reproductive intentions than the “objective” risks. Also, specific cognitive and motivational factors appear to explain much of the variance in risk perception in genetic counseling. The results have important implications for how counseling is conducted, as well as for theoretical issues about cognitive processes.     

A latent class distance association model for cross‐classified data with a categorical response variable

In this paper we propose a latent class distance association model for clustering in the predictor space of large contingency tables with a categorical response variable. The rows of such a table are characterized as profiles of a set of explanatory variables, while the columns represent a single outcome variable. In many cases such tables are sparse, with many zero entries, which makes traditional models problematic. By clustering the row profiles into a few specific classes and representing these together with the categories of the response variable in a low‐dimensional Euclidean space using a distance association model, a parsimonious prediction model can be obtained. A generalized EM algorithm is proposed to estimate the model parameters and the adjusted Bayesian information criterion statistic is employed to test the number of mixture components and the dimensionality of the representation. An empirical example highlighting the advantages of the new approach and comparing it with traditional approaches is presented.     

Effects of chronic cocaine administration on spatial learning and hippocampal spine density in two genetically different strains of rats

Lewis and Fischer-344 rats have been proposed as an addiction model because of their differences in addiction behaviour. It has been suggested that drug addiction is related to learning and memory processes and depends on individual genetic background. We have evaluated learning performance using the eight-arm radial maze (RAM) in Lewis and Fischer-344 adult rats undergoing a chronic treatment with cocaine. In order to study whether morphological alterations were involved in the possible changes in learning after chronic cocaine treatment, we counted the spine density in hippocampal CA1 neurons from animals after the RAM protocol. Our results showed that Fischer-344 rats significantly took more time to carry out test acquisition and made a greater number of errors than Lewis animals. Nevertheless, cocaine treatment did not induce changes in learning and memory processes in both strains of rats. These facts indicate that there are genetic differences in spatial learning and memory that are not modified by the chronic treatment with cocaine. Moreover, hippocampal spine density is cocaine-modulated in both strains of rats. In conclusion, cocaine induces similar changes in hippocampal neurons morphology that are not related to genetic differences in spatial learning in the RAM protocol used here.     

A Latent Block Distance-Association Model for Profile by Profile Cross-Classified Categorical Data

Abstract

Distance association models constitute a useful tool for the analysis and graphical representation of cross-classified data in which distances between points inversely describe the association between two categorical variables. When the number of cells is large and the data counts result in sparse tables, the combination of clustering and representation reduces the number of parameters to be estimated and facilitates interpretation. In this article, a latent block distance-association model is proposed to apply block clustering to the outcomes of two categorical variables while the cluster centers are represented in a low dimensional space in terms of a distance-association model. This model is particularly useful for contingency tables in which both the rows and the columns are characterized as profiles of sets of response variables. The parameters are estimated under a Poisson sampling scheme using a generalized EM algorithm. The performance of the model is tested in a Monte Carlo experiment, and an empirical data set is analyzed to illustrate the model.     

PROBabilities from EXemplars (PROBEX): a “lazy” algorithm for probabilistic inference from generic knowledge

PROBEX (PROBabilities from EXemplars), a model of probabilistic inference and probability judgment based on generic knowledge is presented. Its properties are that: (a) it provides an exemplar model satisfying bounded rationality; (b) it is a “lazy” algorithm that presumes no pre‐computed abstractions; (c) it implements a hybrid‐representation, similarity‐graded probability. We investigate the ecological rationality of PROBEX and find that it compares favorably with Take‐The‐Best and multiple regression (Gigerenzer, Todd, & the ABC Research Group, 1999). PROBEX is fitted to the point estimates, decisions, and probability assessments by human participants. The best fit is obtained for a version that weights frequency heavily and retrieves only two exemplars. It is proposed that PROBEX implements speed and frugality in a psychologically plausible way.     

异步异构分层并行演化算法及其在串并系统可靠性优化中的应用(英文)

本文提出了一种新的并行演化算法――异步异构分层并行演化算法(AHHPGA),用于求解串并系统可靠性分配的多目标优化问题(RAP)。AHHPGA采用分层结构,上层由粗粒度模型构成,下层由细粒度模型构成。在AHHPGA的每个子种群中,采用不同的全局/局部搜索度和拓扑结构,构成异构模型。AHHPGA的迁移方式包括异步接收和异步迁出。采用基于模型的复杂系统可靠性评价工具(HiP-HOPS),以克服可靠性框图方法(RBD)的缺点。仿真结果表明,基于异步异构分层并行演化算法和HiP-HOPS工具的串并系统可靠性分配的多目标优化方法,优于传统的基于遗传算法的优化方法。     

‘Grandpa,Do You Like Roller Coasters?’: Identifying Age‐Appropriate Personality Indicators

Personality development research heavily relies on the comparison of scale means across age. This approach implicitly assumes that the scales are strictly measurement invariant across age. We questioned this assumption by examining whether appropriate personality indicators change over the lifespan. Moreover, we identified which types of items (e.g. dispositions, behaviours, and interests) are particularly prone to age effects. We reanalyzed the German Revised NEO Personality Inventory normative sample (N = 11,724) and applied a genetic algorithm to select short scales that yield acceptable model fit and reliability across locally weighted samples ranging from 16 to 66 years of age. We then examined how the item selection changes across age points and item types. Emotion‐type items seemed to be interchangeable and generally applicable to people of all ages. Specific interests, attitudes, and social effect items—most prevalent within the domains of Extraversion, Agreeableness, and Openness—seemed to be more prone to measurement variations over age. A large proportion of items were systematically discarded by the item‐selection procedure, indicating that, independent of age, many items are problematic measures of the underlying traits. The implications for personality assessment and personality development research are discussed. © 2019 European Association of Personality Psychology