Pacifying Muslims in Germany’s ‘City of Peace’: interreligious dialogue as a tool of governance in Osnabrück

ABSTRACT

Addressing Muslims as a target group in municipal politics is a relatively new development in German cities. Interreligious dialogue, often initiated by established Christian actors, provides a format for doing so. In our local West German case study, the politics of dialogue link up with a historical narrative of Osnabrück as ‘City of Peace’, creating a semantic framework which is hard to resist, yet not undisputed. As a governance tool, interreligious dialogue has the potential to pacify and to structure social relations. It tends to prefer and support certain subject positions, while neglecting others. In this contribution we focus both on actors who are involved in local interreligious dialogue as well as those who – for diverse reasons – do not participate, and who question or oppose it. Thus, we analyse the effects of interreligious dialogue on local subjectivation processes, including alternative reactions that might challenge the dominant paradigm.     

Random word generation reveals spatial encoding of syllabic word length

Existing random number generation studies demonstrate the presence of an embodied attentional bias in spontaneous number production corresponding to the horizontal Mental Number Line: Larger numbers are produced on right-hand turns and smaller numbers on left-hand turns (Loetscher et al.,2008, Curr. Biol., 18, R60). Furthermore, other concepts were also shown to rely on horizontal attentional displacement (Di Bono and Zorzi, 2013, Quart. J. Exp. Psychol., 66, 2348). In two experiments, we used a novel random word generation paradigm combined with two different ways to orient attention in horizontal space: Participants randomly generated words on left and right head turns (Experiment 1) or following left and right key presses (Experiment 2). In both studies, syllabically longer words were generated on right-hand head turns and following right key strokes. Importantly, variables related to semantic magnitude or cardinality (whether the generated words were plural-marked, referred to uncountable concepts, or were associated with largeness) were not affected by lateral manipulations. We discuss our data in terms of the ATOM (Walsh, 2015, The Oxford handbook of numerical cognition, 552) which suggests a general magnitude mechanism shared by different conceptual domains.     

Neuropsychological assessment could distinguish among different clinical phenotypes of progressive supranuclear palsy: A Machine Learning approach

Progressive supranuclear palsy (PSP) is a rare, rapidly progressive neurodegenerative disease. Richardson’s syndrome (PSP-RS) and predominant parkinsonism (PSP-P) are characterized by wide range of cognitive and behavioural disturbances, but these variants show similar cognitive pattern of alterations, leading difficult differential diagnosis. For this reason, we explored with an Artificial Intelligence approach, whether cognitive impairment could differentiate the phenotypes. Forty Parkinson's disease (PD) patients, 25 PSP-P, 40 PSP-RS, and 34 controls were enrolled following the consensus criteria diagnosis. Participants were evaluated with neuropsychological battery for cognitive domains. Random Forest models were used for exploring the discriminant power of the cognitive tests in distinguishing among the four groups. The classifiers for distinguishing diseases from controls reached high accuracies (86% for PD, 95% for PSP-P, 99% for PSP-RS). Regarding the differential diagnosis, PD was discriminated from PSP-P with 91% (important variables: HAMA, MMSE, JLO, RAVLT_I, BDI-II) and from PSP-RS with 92% (important variables: COWAT, JLO, FAB). PSP-P was distinguished from PSP-RS with 84% (important variables: JLO, WCFST, RAVLT_I, Digit span_F). This study revealed that PSP-P, PSP-RS and PD had peculiar cognitive deficits compared with healthy subjects, from which they were discriminated with optimal accuracies. Moreover, high accuracies were reached also in differential diagnosis. Most importantly, Machine Learning resulted to be useful to the clinical neuropsychologist in choosing the most appropriate neuropsychological tests for the cognitive evaluation of PSP patients.     

Some comments on selecting the best of several binomial populations or the bivariate normal population having the largest correlation coefficient

Using variance stabilizing transformations, this note describes approximate solutions to the ranking and selection problem of selecting the best binomial population or the bivariate normal population with the largest correlation coefficient.     

Memories of the dictatorship in Spain. An analysis of the narratives from three generations / Memorias de la dictadura en España. Un análisis de las narrativas de tres generaciones

Abstract

This study will investigate the narratives related by the members of three different generations within two different families on their memories of the Franco dictatorship. The first generation lived through Francoism, the second the democratic transition, and the third were born in a democratic country. Based on a social and discursive conception of memory and identity, this study is carried out using semi-structured interviews as a data collection tool, which we then thematically analyse, together with aspects of the participants’ positions and voices. The interviews are connected according to the factors of generation and family, and we analyse the similarities and differences. This is how the influence of both is seen in each individual’s memories and identities, in addition to how their political ideology is configured.