"Traditionally, estimates of the number of people in small areas (the smallest geographical units for which data are available) have been disaggregated only by age and sex. More recently, much research effort has been directed towards developing some form of enhanced small-area population estimation, in which the population in a small area is disaggregated not only by age and sex, but also by a wide range of additional economic and social characteristics. Solutions to this problem currently include account-based demographic models, often used by local authorities."
The paper describes the creation of the Office for National Statistics 2001 output area classification, which was created in collaboration with the authors. The classification places each 2001 census output area into one of seven clusters based on the socio-economic attributes of the residents of each area. The classification uses cluster analysis to reduce 41 census variables to a single socio-economic indicator. The classification was made available with a host of supporting and descriptive information as a National Statistic via National Statistics on line. The classification forms part of a suite of area classifications that were produced by the Office for National Statistics from 2001 census data. Classifications of local authorities, statistical wards and health areas are also available. Copyright 2007 Royal Statistical Society.
Our objectives are to identify the issues that researchers encounter when measuring internal migration in different countries and to propose key indicators that analysts can use to compare internal migration at the 'national' level. We establish the benefits to be gained by a rigorous approach to cross-national comparisons of internal migration and discuss issues that affect such comparisons. We then distinguish four dimensions of internal migration on which countries can be compared and, for each dimension, identify a series of summary measures. We illustrate the issues and measures proposed by comparing migration in Australia and Great Britain. Copyright 2002 Royal Statistical Society.
Our objectives are to identify the issues that researchers encounter when measuring internal migration in different countries and to propose key indicators that analysts can use to compare internal migration at the 'national' level.We establish the benefits to be gained by a rigorous approach to cross-national comparisons of internal migration and discuss issues that affect such comparisons. We then distinguish four dimensions of internal migration on which countries can be compared and, for each dimension, identify a series of summary measures. We illustrate the issues and measures proposed by comparing migration in Australia and Great Britain.
We know that internal migration shapes human settlement patterns, but few attempts have been made to measure systematically the extent of population redistribution or make comparisons between countries. Robust comparisons are hampered by limited data access, different spacetime frameworks, and inadequate summary statistics. We use new analysis software (IMAGE Studio) to assess the effects of differences in the number and configuration of geographic zones and implement new measures to make comparisons across a large sample of countries, representing 80% of global population. We construct a new Index of Net Migration Impact to measure system-wide population redistribution and examine the relative contributions of migration intensity and effectiveness to crossnational variations. We compare spatial patterns using the slope of a regression between migration and population density across zones in each country to indicate the direction and pace of population concentration. We report correlations between measures of population redistribution and national development and propose a general theoretical model suggesting how internal migration redistributes population across settlement systems during the development process.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. Figure 1. Migration intensity, migration effectiveness and the aggregate net migration rate, as a function of the number of spatial units, selected countries that measure migration over a 5-year interval. 8 of 22 P. Rees et al.
This paper presents an analysis of the degree to which the population of Britain has become more or less geographically polarised as compared with 1991 and earlier censuses. We use the Key Statistics for local authorities from the 2001 Census, released on 13 February 2003 by the census authorities. All of the variables from the 26 Key Statistics tables which can be compared over time with the 1991 Census are examined. The analysis is then extended for a subset of variables that were similarly measured in 1971 and 1981. We conclude that for key aspects of life in Britain, as recorded by the censuses, the nation has continued in the 1990s to divide socially geographically, often at a faster rate than was occurring in the 1980s or 1970s. Where there appears to have been a reduction in polarisation it tends to have been for those aspects of life which are now poorly measured by the census. The paper concludes with speculation about the possible reasons for the continued division of the country into areas now more easily than ever typified as being old and young, settled and migrant, black and white, or rich and poor. Finally the potential for the continued sociospatial polarisation of Britain is discussed. The paper begins with a fictional vignette.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.