The modifiable areal unit phenomenon: an investigation into the scale effect using UK census data

The Modifiable Areal Unit Phenomenon (MAUP) has traditionally been regarded as a problem in the analysis of spatial data organised in areal units. However, the approach adopted here is that the MAUP provides an opportunity to gain information about the data under investigation. Crucially, attempts to remove the MAUP from spatial data are regarded as an attempt to remove the geography. Therefore, the work seeks to provide an insight to the causes of, and information behind, the MAUP. The data used is from the 1991 Census of Great Britain. This was chosen over 2001 data due to the availability of individual level data. These data are of key importance to the methods employed. The methods seek to provide evidence of the magnitude of the MAUP, and more specifically the scale effect in the GB Census. This evidence is built on using correlation analysis to demonstrate the statistical significance of the MAUP. Having established the relevance of the MAUP in the context of current geographical research, the factors that contribute to the incidence of the MAUP are considered, and it is noted that a wide range of influences are important. These include the population size and density of an area, along with proportion of a variable. This discussion also recognises the importance of homogeneity as an influential factor, something that is referenced throughout the work. Finally, a search is made for spatial processes. This uses spatial autocorrelation and multilevel modelling to investigate the impact spatial processes have in a range of SAR Districts, like Glasgow, Reigate and Huntingdonshire, on the scale effect. The research is brought together, not to solve the MAUP but to provide an insight into the factors that cause the MAUP, and demonstrate the usefulness of the MAUP as a concept rather than a problem

Ageing and cohort trajectories in mental ill-health: An exploration using multilevel models

Analyses of health over time must consider the potential impacts of ageing as well as any effects relating to cohort differences. The British Household Panel Survey (BHPS) and Understanding Society longitudinal studies are employed to assess trends in mental ill-health over a 26-year period. This analysis uses cross-classified multilevel models in an exploratory, non-parametric approach to evaluate age and cohort effects net of each other. Mental ill-health evidences an initial worsening trend as people age which then reverses and exhibits improvement in late-middle-age, before declining again in the latter stages of life. There were less defined cohort trends. The modelling technique also reveals the relative importance of the temporal contexts in relation to inter- and intra-individual effects on mental ill-health, demonstrating that the ageing and cohort dimensions explain little variation compared to these more dominant within and between influences. Ultimately, we suggest that researchers would benefit from wider use of this exploratory modelling strategy when evaluating underlying health trends and more research is now needed to explore potential explanations of these baseline trajectories.</p

In search of Britain’s Muslim ghettoes

The local media have recently carried a number of stories suggesting that Muslim ghettoes are developing in British cities – a claim also made about European cities more generally. Analysis of data from the 2001 and 2011 Censuses of England and Wales suggests that these representations are journalistic hyperbole: most British Muslims live in small city blocks where they form only a minority of the local population. </jats:p

Uncovering interactions in multivariate contingency tables:a multi-level modelling exploratory approach

Much quantitative behavioural social science – a great deal of it exploratory in nature – involves the analysis of multivariate contingency tables, usually deploying logistic binomial and multinomial regression models with no exploration of interaction effects, despite arguments that this should be a crucial element of the analysis. This article builds on suggestions that the search for interaction effects should employ multi-level modelling strategies and outlines a procedure for modelling patterns in data sets with small numbers of observations in many, if not all, of their multivariate contingency table cells; all expected cells must be non-zero. The procedure produces precision-weighted estimates of the observed:expected rates for each and every cell, together with associated Bayesian credible intervals, and is illustrated using a large survey data set relating voting (and abstaining) at the 2015 UK general election to age, sex and educational qualifications. Crucially, while fine detail can be explored in the analysis, unreliable rates for particular subgroups are automatically down-weighted to what is happening generally. The identification of reliable differential rates then allows a simpler hybrid model that captures the main trends to be fitted and interpreted. </jats:p

Multidisciplinary analysis of a mummified cranium claimed to be that of a medieval execution victim

This article presents a multidisciplinary analysis of a human skull with preserved soft tissue curated by a small museum in Boscastle, Cornwall, UK. The skull lacks a mandible and is coated in a black tar-like substance. Records left by a previous museum curator (now deceased) claimed the skull to be the head of a medieval execution victim. The skull was purportedly recovered from a London church that was destroyed during the Second World War where it had been kept in a carved oak box. If these details are correct, the skull would appear to have been venerated as a relic. The skull and box have been analysed using a range of techniques including computerised tomography, laser scanning, microscopy, infrared spectroscopy and radiocarbon dating. These analyses demonstrated the skull in fact to be that of an Egyptian mummy dating from the Ptolemaic period. Other instances have been noted of parts of Egyptian mummies being presented as European saintly relics, and the ‘Boscastle skull’ would appear to be an example of such. A wider point illustrated by the work presented here is that sufficient application of modern analytical techniques may reveal considerable information regarding human remains which otherwise have little or no provenance. This point strengthens arguments for the retention of such remains by curating institutions