University of Exeter

About: University of Exeter is a education organization based out in Exeter, United Kingdom. It is known for research contribution in the topics: Population & Climate change. The organization has 15820 authors who have published 50650 publications receiving 1793046 citations. The organization is also known as: Exeter University & University of the South West of England.

Citizenship-as-Practice: The Educational Implications of an Inclusive and Relational Understanding of Citizenship

Abstract: Over the last few years there has been a renewed interest in questions of citizenship and in particular its relation to young people. This has been allied to an educational discourse where the emphasis has been upon questions concerned with ‘outcome’ rather than with ‘process’– with the curriculum and methods of teaching rather than questions of understanding and learning. This paper seeks to describe and illuminate the linkages within and between these related discourses. It advocates an inclusive and relational view of citizenship-as-practice within a distinctive socio-economic and political, and cultural milieu. Drawing upon some empirical insights from our research we conclude that an appropriate educational programme would respect the claim to citizenship status of everyone in society, including children and young people. It would work together with young people rather than on young people, and recognise that the actual practices of citizenship, and the ways in which these practices transf...

Methylation QTLs in the developing brain and their enrichment in schizophrenia risk loci

Abstract: We characterized DNA methylation quantitative trait loci (mQTLs) in a large collection (n = 166) of human fetal brain samples spanning 56-166 d post-conception, identifying >16,000 fetal brain mQTLs. Fetal brain mQTLs were primarily cis-acting, enriched in regulatory chromatin domains and transcription factor binding sites, and showed substantial overlap with genetic variants that were also associated with gene expression in the brain. Using tissue from three distinct regions of the adult brain (prefrontal cortex, striatum and cerebellum), we found that most fetal brain mQTLs were developmentally stable, although a subset was characterized by fetal-specific effects. Fetal brain mQTLs were enriched amongst risk loci identified in a recent large-scale genome-wide association study (GWAS) of schizophrenia, a severe psychiatric disorder with a hypothesized neurodevelopmental component. Finally, we found that mQTLs can be used to refine GWAS loci through the identification of discrete sites of variable fetal brain methylation associated with schizophrenia risk variants.

Weakly Supervised Joint Sentiment-Topic Detection from Text

Abstract: Sentiment analysis or opinion mining aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text. This paper proposes a novel probabilistic modeling framework called joint sentiment-topic (JST) model based on latent Dirichlet allocation (LDA), which detects sentiment and topic simultaneously from text. A reparameterized version of the JST model called Reverse-JST, obtained by reversing the sequence of sentiment and topic generation in the modeling process, is also studied. Although JST is equivalent to Reverse-JST without a hierarchical prior, extensive experiments show that when sentiment priors are added, JST performs consistently better than Reverse-JST. Besides, unlike supervised approaches to sentiment classification which often fail to produce satisfactory performance when shifting to other domains, the weakly supervised nature of JST makes it highly portable to other domains. This is verified by the experimental results on data sets from five different domains where the JST model even outperforms existing semi-supervised approaches in some of the data sets despite using no labeled documents. Moreover, the topics and topic sentiment detected by JST are indeed coherent and informative. We hypothesize that the JST model can readily meet the demand of large-scale sentiment analysis from the web in an open-ended fashion.