Spatial dependence and heterogeneity in patterns of urban deprivation

Developments in the provision and quality of digital data are creating possibilities for finer resolution spatial and temporal measurement of the properties of socio-economic systems. We suggest that the ?lifestyles? datasets collected by private sector organisations provide one such prospect for better inferring the structure, composition and heterogeneity of urban areas. Clearly, deprivation and hardship are inextricably linked to incomes from earnings and transfer payments. In many countries (e.g. the UK) no small area income measures are collected at all, and this forces reliance upon commercial sources. Yet, the use of such data in academic research is not without considerable problems. In the same spirit as Gordon and Pantazis (1995) we thus think it necessary to retain some linkage to population census data ? but in a way which is much more sensitive to spatial context. A critical issue is thus to understand the scales at which both income, and the variables that are used to predict it, vary (see also Rees, 1998; Harris and Longley, 2002). We address some of these issues in the context of the debate about the intra-urban geography of hardship and social exclusion. Low income fundamentally restricts the abilities of people to participate actively in society (Harris and Longley, 2002), yet reliable, up-to-date income measures at fine spatial scales are rarely available from conventional sources. As a consequence, many indicators of deprivation are reliant upon data sources that are out of date and/or entail use of crude surrogate measures. Some measures bear little clear correspondence with hardship at all. Other widely-used indicators are spatially variable in their operation. The broader issue concerns the scale and extent of ?pockets? of hardship and the scale ranges at which difference is deemed manifests. The problems are further compounded if each of the range of surrogate measures used to specify a concept operates at different scales. Taken together, it remains unclear whether meaningful indicators of social conditions can ever be adequately specified, or whether generalised representations can be sufficiently sensitive to place. Using a case study of Bristol, UK, we compare the patterns of spatial dependence and spatial heterogeneity observed for a small area (?lifestyles?) income measure with those of the census indicators that are commonly used as surrogates for it. This leads to specification of spatial dependence using a spatially autoregressive model, and accommodation of local heterogeneity using geographically weighted regression (GWR). This analysis begins to extend our understanding of the determinants of hardship and poverty in urban areas: urban policy has hitherto used aggregate, outdated or proxy measures of income in a less critical manner; and techniques for measuring spatial dependence and heterogeneity have usually been applied at the regional, rather than intra urban, scales. The consequence is a limited understanding of the geography and dynamics of income variations within urban areas. The advantages and limitations of the data used here are explored in the light of the results of our statistical analysis, and we discuss our results as part of a research agenda for exploring dependence and heterogeneity in spatial distributions.

Participating in the Past: Recording Lives in Digital Environments

The article focuses on the impact of digital media on the recording and presentation of oral history. It discusses some issues such as the finance for oral history research, the problems associated with maintaining and updating digital histories and the demands of interdisciplinary collaboration in Australia. It also looks into some oral history projects to describe the essence and impact of digitalization on oral history. Moreover, it explores the constraints of the digital environment

An Individual Level Method for Improved Estimation of Ethnic Characteristics

This paper develops an improved method for estimating the ethnicity of individuals based on individual level pairings of given and family names. It builds upon previous research by using a global database of names from c. 1.7 billion living individuals, supplemented by individual level historical census data. In focusing upon Great Britain, these resources enable, respectively, greater precision in estimating probable global origins and better estimation of self-identification amongst long-established family groups such as the Irish Diaspora. We report on geographic issues in adjusting the weighting of groups that are systematically under- or over-predicted using other methods. Our individual level estimates are evaluated using both small area Great Britain census data for 2011 and individual level data for asylum seekers in Canada between 1995 and 2012. Our conclusions assess the value of such estimates in the conduct of social equity audits and in depicting the social mobility outcomes of residential mobility and migration across Great Britain

Consumer Data Research

Big Data collected by customer-facing organisations – such as smartphone logs, store loyalty card transactions, smart travel tickets, social media posts, or smart energy meter readings – account for most of the data collected about citizens today. As a result, they are transforming the practice of social science. Consumer Big Data are distinct from conventional social science data not only in their volume, variety and velocity, but also in terms of their provenance and fitness for ever more research purposes. The contributors to this book, all from the Consumer Data Research Centre, provide a first consolidated statement of the enormous potential of consumer data research in the academic, commercial and government sectors – and a timely appraisal of the ways in which consumer data challenge scientific orthodoxies

Georeferencing historical telephone directories to understand innovation diffusion and social change

This paper explores how historical archives of British telephone directories, recently made available, can be used to revisit historical and geographical questions using a modern, quantitative approach. By geolocating telephone subscribers throughout history, we seek to retrace spatial and temporal changes in demography and the spread of the fixed line telephone network in Britain. We develop a prototypical pipeline for capturing and processing these data using archives from 1881 and demonstrate that, if extended and applied to directories from the subsequent 100 years, this research can provide new insights into wide-ranging aspects of British social and economic history

Geography, ethnicity, genealogy and inter‐generational social inequality in Great Britain

This paper documents population-wide inequalities of outcome in Great Britain amongst and between long-established and more recently arrived family groups. ‘Establishment’ is defined using family group presence in the 1851 Census of Population as a benchmark, and the ethnicity or nationality of more recent migrants is determined through classification of given and family names. Inequalities of outcome are measured using a harmonised indicator of neighbourhood deprivation (hardship). White British individuals tend to live in the best neighbourhoods, but within-group inequalities reflect regional locations in which different family names were first coined 700 or more years ago. The living circumstances of White Irish and Chinese migrants are observed to be in line with long-established White British family lines, but other conventionally defined ethnic groups fare worse, some very markedly so. Disaggregation of conventional ethnic groups used by the Office for National Statistics such as White Other and Other Asian reveals stark within-group inequalities. These findings suggest: (a) regional origins of inter-generational inequalities amongst the White British; (b) comparable neighbourhood environments experienced by the White Irish, Chinese and some White Other groups and (c) significantly worse neighbourhood circumstances within and between other more recently arrived immigrant groups. This work has several implications for understanding economic assimilation of migrants and the existence of inequalities amongst and between populations

Exploring the spatial disparities in gambling risk and vulnerability

Gambling harm disrupts the health and wellbeing of the individuals, as well as families, communities and societies around them. Despite the growing recognition that gambling harms are socially and geographically uneven in its occurrence and impacts, there is limited empirical knowledge about the factors underlying the disparities. Here, w e quantitatively profile nationwide gambling survey using series of small area geodemographic data. Results from this granular analysis are synthesized to devise a composite indicator of gambling risk and vulnerability that can be mapped to provide new insights into public health strategies to tackling gambling harms in a more effective manner

Towards Real-Time Geodemographics: Clustering Algorithm Performance for Large Multidimensional Spatial Databases

and demographic characteristics of people living within small geographic areas. They have hitherto been regarded as products, which are the final “best” outcome that can be achieved using available data and algorithms. However, reduction in computational cost, increased network bandwidths and increasingly accessible spatial data infrastructures have together created the potential for the creation of classifications in near real time within distributed online environments. Yet paramount to the creation of truly real time geodemographic classifications is the ability for software to process and efficiency cluster large multidimensional spatial databases within a timescale that is consistent with online user interaction. To this end,this article evaluates the computational efficiency of a number of clustering algorithms with a view to creating geodemographic classifications “on the fly” at a range of different geographic scales.tgis_1197 283..29