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Social class differences in political participation are a pressing issue for democracies and they are particularly severe among young people in the UK. Disadvantaged young people are the least likely to be politically engaged in the UK and it is assumed that with declining levels of participation inequalities in political participation increase. What happens to political inequality though when levels of youth participation increase? Do more advantaged young people account for most of the extra participation or do disadvantaged young people ‘catch up’? Based on representative survey data, this paper investigates levels of political inequality among 16- and 17-year-olds in a context of increasing participation in Scotland. We find that in Scotland young people of all social classes were equally likely to be politically engaged, while among young people in the rest of the UK and adults from Scotland those of higher social status were more likely to be engaged in politics. Overall, social class differences in political engagement were less pronounced amongst 16- and 17-year-olds in Scotland than in the rest of the UK. The paper offers some possible explanations of this finding and suggestions for further research.

SummaryEssential features of cancer tissue cellular heterogeneity such as negatively selected genome topologies, sub-clonal mutation patterns and genome replication states can only effectively be studied by sequencing single-cell genomes at scale and high fidelity. Using an amplification-free single-cell genome sequencing approach implemented on commodity hardware (DLP+) coupled with a cloud-based computational platform, we define a resource of 40,000 single-cell genomes characterized by their genome states, across a wide range of tissue types and conditions. We show that shallow sequencing across thousands of genomes permits reconstruction of clonal genomes to single nucleotide resolution through aggregation analysis of cells sharing higher order genome structure. From large-scale population analysis over thousands of cells, we identify rare cells exhibiting mitotic mis-segregation of whole chromosomes. We observe that tissue derived scWGS libraries exhibit lower rates of whole chromosome anueploidy than cell lines, and loss of p53 results in a shift in event type, but not overall prevalence in breast epithelium. Finally, we demonstrate that the replication states of genomes can be identified, allowing the number and proportion of replicating cells, as well as the chromosomal pattern of replication to be unambiguously identified in single-cell genome sequencing experiments. The combined annotated resource and approach provide a re-implementable large scale platform for studying lineages and tissue heterogeneity.