Mapping inequalities in school attendance:The relationship between dimensions of socioeconomic status and forms of school absence

In this article, we investigated whether and to what extent various dimensions of socioeconomic background (parental education, parental class, free school meal registration, housing status, and neighborhood deprivation) predict overall school absences and different reasons for absenteeism (truancy, sickness, family holidays and temporary exclusion) among 4,620 secondary school pupils in Scotland. Students were drawn from a sample of the Scottish Longitudinal Study comprising linked Census data and administrative school records. Using fractional logit models and logistic regressions, we found that all dimensions of socioeconomic background were uniquely linked to overall absences. Multiple measures of socioeconomic background were also associated with truancy, sickness-related absence, and temporary exclusion. Social housing and parental education had the most pervasive associations with school absences across all forms of absenteeism. Our findings highlight the need to consider the multidimensionality of socioeconomic background in policy and research decisions on school absenteeism. A more explicit focus on narrowing the socioeconomic gap in absenteeism is required to close the inequality gap in educational and post-school outcomes

Permutationally invariant state reconstruction

Feasible tomography schemes for large particle numbers must possess, besides an appropriate data acquisition protocol, also an efficient way to reconstruct the density operator from the observed finite data set. Since state reconstruction typically requires the solution of a non-linear large-scale optimization problem, this is a major challenge in the design of scalable tomography schemes. Here we present an efficient state reconstruction scheme for permutationally invariant quantum state tomography. It works for all common state-of-the-art reconstruction principles, including, in particular, maximum likelihood and least squares methods, which are the preferred choices in today's experiments. This high efficiency is achieved by greatly reducing the dimensionality of the problem employing a particular representation of permutationally invariant states known from spin coupling combined with convex optimization, which has clear advantages regarding speed, control and accuracy in comparison to commonly employed numerical routines. First prototype implementations easily allow reconstruction of a state of 20 qubits in a few minutes on a standard computer.Comment: 25 pages, 4 figues, 2 table

Introduction to the rheory of statistics

xv, 443 p.; 23 cm

Introduction to the theory of statistics, 3rd.ed./ Mood

xvi, 564 hal. : bibl. ; ill. ; ind. ; 21 cm