'We are actually raising South Africans''. Raising immigrant families: The parenting experiences of Zimbabweans in South Africa

South Africa is the most popular international destination for Zimbabwean migrants escaping the economic crisis of their country. It has been estimated that by 2016, one and a half million Zimbabwean nationals were living in South Africa. However, little research explores the lived experience of Zimbabweans in South Africa in the context of family. This is despite scholars highlighting an increase in family migration from Zimbabwe to South Africa in recent years. This study explores the parenting experiences of immigrant Zimbabwean parents raising their children in South Africa. Specifically, it investigates the ways in which raising children in a different country and cultural context influences parents’ understanding of and approaches to parenting. Nine Zimbabwean mothers and fathers living with their spouses and children in Cape Town participated in a qualitative study, with semi-structured interviews. Data was collected and analysed using thematic analysis. The study found that the participants’ overarching experience of parenting was that they were ultimately raising ‘South Africans’. Participants framed their children’s ‘South African-ness’ positively, identifying the children as cosmopolitan and empowered, which they celebrated. However, they also lamented the children’s loss of identity as the most problematic aspect of ‘South African-ness’. To navigate the resultant tensions, participants relaxed some of their existing beliefs while simultaneously implementing measures to reinforce some non-negotiable values and beliefs in their children. This dissertation argues that while parents’ understanding of parenting is strongly rooted in their cultural background and values, they adapt their parenting styles and practices according to what they calculate will enable their families to thrive. The study adds to the body of knowledge on immigrant Zimbabwean families who have become part of South African society. This is especially relevant in light of the South African government’s laudable initiatives towards regularising the stay of Zimbabweans in South Africa, such as the Dispensation of Zimbabweans Project (DZP) of 2009 and its successive permits. This study can therefore contribute to the body of knowledge that informs the ways in which South Africa can continue to respond to the reality of migration from Zimbabwe

A Maximum Entropy Procedure to Solve Likelihood Equations

In this article, we provide initial findings regarding the problem of solving likelihood equations by means of a maximum entropy (ME) approach. Unlike standard procedures that require equating the score function of the maximum likelihood problem at zero, we propose an alternative strategy where the score is instead used as an external informative constraint to the maximization of the convex Shannon\u2019s entropy function. The problem involves the reparameterization of the score parameters as expected values of discrete probability distributions where probabilities need to be estimated. This leads to a simpler situation where parameters are searched in smaller (hyper) simplex space. We assessed our proposal by means of empirical case studies and a simulation study, the latter involving the most critical case of logistic regression under data separation. The results suggested that the maximum entropy reformulation of the score problem solves the likelihood equation problem. Similarly, when maximum likelihood estimation is difficult, as is the case of logistic regression under separation, the maximum entropy proposal achieved results (numerically) comparable to those obtained by the Firth\u2019s bias-corrected approach. Overall, these first findings reveal that a maximum entropy solution can be considered as an alternative technique to solve the likelihood equation

Exact Multivariate Permutation Tests for Fixed Effects in Mixed-Models

A test for the fixed effect in mixed-models is proposed. It is based on permutation strategy and is exact. The testing approach presented is very general and the class of model covered is very broad. Multivariate responses with different type of variables (e.g. continuous, categorical and ranks) are usually tested with separated models and the overall test are usually reached trough Bonferroni-like combinations, i.e. without taking in account the joint distribution of the tests statistics. On the contrary in this approach the joint distribution is immediately obtained and the dependence among tests is taken in account in the overall test

k-FWER control without multiplicity correction, with application to detection of genetic determinants of multiple sclerosis in Italian twins

We show a novel approach for k-FWER control which does not involve any correction, but only testing the hypotheses along a (possibly datadriven) order until a suitable number of p-values are found above the uncorrected α level. p-values can arise from any linear model in a parametric or non parametric setting. The approach is not only very simple and computationally light, but also the data-driven order enhances power when the sample size is small (and also when k and/or m is large). We illustrate the method on an original study about gene discovery in multiple sclerosis, in which were involved a small number of couples of twins, discordant by disease

Procrustes analysis for high-dimensional data

The Procrustes-based perturbation model \citep{Goodall} allows to minimize the Frobenius distance between matrices by similarity transformation. However, it suffers from non-identifiability, critical interpretation of the transformed matrices, and non-applicability in high-dimensional data. We provide an extension of the perturbation model focused on the high-dimensional data framework, called the ProMises (Procrustes von Mises-Fisher) model. The ill-posed and interpretability problems are solved by imposing a proper prior distribution for the orthogonal matrix parameter, i.e., the von Mises-Fisher distribution, which is a conjugate prior, resulting in a fast estimation process. Furthermore, we present the Efficient ProMises model for the high-dimensional framework, useful in neuroimaging, where the problem has much more than three dimensions. We found a great improvement in functional Magnetic Resonance Imaging connectivity analysis since the ProMises model permits to incorporate topological brain information in the alignment's estimation process.Comment: 20 pages, 7 figure

TextWiller: Collection of functions for text mining, specially devoted to the Italian language

TextWilleris the development version of a R package that collects some text mining utilities intended for the Italian language. It’s available at https://github.com/livioivil/TextWiller. The aim of TextWiller is to help to deal with the pre-processing of a corpus and it also provides some functions about word classification and polarity

Robust testing in generalized linear models by sign flipping score contributions

Generalized linear models are often misspecified because of overdispersion, heteroscedasticity and ignored nuisance variables. Existing quasi-likelihood methods for testing in misspecified models often do not provide satisfactory type I error rate control. We provide a novel semiparametric test, based on sign flipping individual score contributions. The parameter tested is allowed to be multi-dimensional and even high dimensional. Our test is often robust against the mentioned forms of misspecification and provides better type I error control than its competitors. When nuisance parameters are estimated, our basic test becomes conservative. We show how to take nuisance estimation into account to obtain an asymptotically exact test. Our proposed test is asymptotically equivalent to its parametric counterpart

Hemisphere Mixing: a Fully Data-Driven Model of QCD Multijet Backgrounds for LHC Searches

A novel method is proposed here to precisely model the multi-dimensional features of QCD multi-jet events in hadron collisions. The method relies on the schematization of high-pT QCD processes as 2->2 reactions made complex by sub-leading effects. The construction of libraries of hemispheres from experimental data and the definition of a suitable nearest-neighbor-based association map allow for the generation of artificial events that reproduce with surprising accuracy the kinematics of the QCD component of original data, while remaining insensitive to small signal contaminations. The method is succinctly described and its performance is tested in the case of the search for the hh->bbbb process at the LHC.Comment: 4 pages plus header, 1 figure, proceedings of EPS 2017 Venic