Finding Your Feet in the Field: Critical Reflections of Early Career Researchers on Field Research in Transitional Societies

Fieldwork that takes place in conflict or transitional regions is becoming increasingly popular amongst early-career and more seasoned researchers, but is an area that retains an air of mystery and remains an exotic form of knowledge gathering. There exists a paucity of personal reflection on the challenges associated with conducting fieldwork in conflicted or transitional regions and a limited amount of insight into the practical steps taken in advance of and when immersed in the field. Such reticence to share honest fieldwork experiences, particularly the more challenging research that takes place in conflict or transitional settings aids in creating a culture of silence. This paper attempts to counteract this silence by drawing on the challenges experienced by two early career researchers conducting fieldwork in Uganda and Palestine, focusing on the practical steps taken in advance of entering the field, and the challenges faced whilst engaged in fieldwork. Specific challenges are highlighted throughout, including: physical access to areas in conflict; engaging with reluctant research participants; the emotional impact of fieldwork on the researcher; maintaining confidentiality; researching with vulnerable victims; and ensuring appropriate knowledge exchange between researchers and participants. The paper concludes by emphasising the requirement for greater reflection on the inherently personal challenges associated with conducting fieldwork in conflicted or transitional settings and highlights the view that fieldwork is a privileged position that carries great responsibilities which must be upheld to ensure the sustainability of future research. This paper hopes to contribute to the wider debate on conducting fieldwork and the challenges associated with working in conflicted or transitional regions.

Finding the magic number

Paul Wilson and Colin Cooper investigate methods used to extract the number of factors in a factor analysis

Unite and conquer: univariate and multivariate approaches for finding differentially expressed gene sets

Motivation: Recently, many univariate and several multivariate approaches have been suggested for testing differential expression of gene sets between different phenotypes. However, despite a wealth of literature studying their performance on simulated and real biological data, still there is a need to quantify their relative performance when they are testing different null hypotheses.

Results: In this article, we compare the performance of univariate and multivariate tests on both simulated and biological data. In the simulation study we demonstrate that high correlations equally affect the power of both, univariate as well as multivariate tests. In addition, for most of them the power is similarly affected by the dimensionality of the gene set and by the percentage of genes in the set, for which expression is changing between two phenotypes. The application of different test statistics to biological data reveals that three statistics (sum of squared t-tests, Hotelling's T2, N-statistic), testing different null hypotheses, find some common but also some complementing differentially expressed gene sets under specific settings. This demonstrates that due to complementing null hypotheses each test projects on different aspects of the data and for the analysis of biological data it is beneficial to use all three tests simultaneously instead of focusing exclusively on just one.