Ravenstein Revisited: The Analysis of Migration, Then and Now

In 1876, 1885 and 1889, Ernst Ravenstein, an Anglo-German geographer, published papers on internal and international migration in Britain, Europe and North America. He generalized his findings as “laws of migration”, which have informed subsequent migration research. This paper aims to compare Ravenstein’s approach to investigating migration with how researchers have studied the phenomenon more recently. Ravenstein used lifetime migrant tables for counties from the 1871 and 1881 censuses of the British Isles. Data on lifetime migrants are still routinely collected but, because of the indeterminate time interval, they are rarely used to study internal migration. Today, internal migration measures from alternative sources are used to measure internal migration: fixed interval migrant data from censuses and surveys, continuous records of migrations from registers, and “big data” from telecommunications and internet companies. Ravenstein described and mapped county-level lifetime migration patterns, using the concepts of “absorption” and “dispersion”, using migration rates and net balances. Recently, researchers have used lifetime migrant stocks from consecutive censuses to estimate country to country flows for the world. In the last decade, an Australian-led team has built an international database of internal migration flow data and summary measures. Methods were developed to investigate the modifiable areal unit problem (MAUP), in order to design summary internal migration measures comparable across countries. Indicators of internal migration were produced for countries covering 80 percent of the world’s population. Ravenstein observed that most migrants moved only short distances, anticipating the development of “gravity” models of migration. Recent studies calibrated the relationship between migration and distance, using gravity models. For mid-19th century Britain, Ravenstein found the dominant direction of internal migration to be towards the “centres of commerce and industry”. Urbanization is still the dominant flow direction in most countries, though, late in the process, suburbanization, counter-urbanization and re-urbanization can occur. Ravenstein focussed on place-specific migration, whereas today researchers describe migration flows using area typologies, seeking spatial generality. Ravenstein said little about migrant attributes except that women migrated more than men. In recent decades, the behaviour of migrants by age, sex, education, ethnicity, social class and partnership status have been studied intensively, using microdata from censuses and surveys. Knowledge about processes influencing internal and international migration has rarely been built into demographic projections. Scenarios that link migration with sub-national or national inequalities and with climate or environmental change are influencing the design of policies to reduce inequalities or slow global warming

Frequency multiplication in high-energy electron beams Semiannual progress report, Oct. 1, 1966 - Apr. 1, 1967

Frequency multiplication in high energy electron beam

A classification for English primary schools using open data

England has statutory regulations in place that ensure state funded schools deliver broadly the same curriculum. However there still exists a wide range of contexts in which this education takes place, including: the management of schools; how the schools chose to spend their budgets; individual policies in regards to staffing, behaviour and attendance, and perhaps most importantly, the composition of the pupil population in the school. Given these contexts, one outcome of interest is the attainment profile of schools, and it is important that this performance is judged in context, for the benefits of pupils, parents and schools. To this end, this study develops a classification using contemporary data for English primary schools. The open data used captures aspects of the gender, ethnic, language, staffing and affluence makeup of each school. The nature of these derived groupings is described and made available as a mapping resource. These groupings allow the identification of “families of schools”, to act as a resource to foster better collaboration between schools and more nuanced benchmarking

Sub-national projection methods for Scotland and Scottish areas: a review and recommendations

This report responds to a request for advice by National Records of Scotland (NRS) on how to adapt and improve the methodology used for the Scotland Sub-National Population Projections (SNPP). The 2014- based Scotland SNPP are currently being prepared

A mass-market appraisal of the English housing rental market using a diverse range of modelling techniques

Introduction: Mass appraisals in the rental housing market are far less common than those in the sales market. However, there is evidence for substantial growth in the rental market and this lack of insight hampers commercial organisations and local and national governments in understanding this market. Case description: This case study uses data that are supplied from a property listings web site and are unique in their scale, with over 1.2 million rental property listings available over a two year period. The data is analysed in a large data institute using generalised linear regression, machine learning and a pseudo practitioner based approach. Discussion and Evaluation: The study should be seen as a practical guide for property professionals and academics wishing to undertake such appraisals and looking for guidance on the best methods to use. It also provides insight into the property characteristics which most influence rental listing price. Conclusions: From the regression analysis, attributes that increase the rental listing price are: the number of rooms in the property, proximity to central London and to railway stations, being located in more affluent neighbourhoods and being close to local amenities and better performing schools. Of the machine learning algorithms used, the two tree based approaches were seen to outperform the regression based approaches. In terms of a simple measure of the median appraisal error, a practitioner based approach is seen to outperform the modelling approaches. A practical finding is that the application of sophisticated machine learning algorithms to big data is still a challenge for modern desktop PCs

Rent/price ratio for English housing sub‐markets using matched sales and rental data

The ratio between the rental and sales values of residential properties are a much studied statistic in the field of real estate economics. When these values do not keep pace with each other, and in particular when the ratio is low, some commentators take this as an indication that there may be a housing bubble building. The ratios are also of interest to potential property investors. These ratios are commonly computed on aggregate statistics derived from the housing market and as such rarely provide any indication of sub‐market bubbles, that can occur with particular property types or regions of the country. In this study use is made of a data set from a property listings company that provides sales and, potentially, rental prices for the same properties within England. From the matching that takes place it is possible to calculate the rent/price ratio for individual properties. A regression model is then estimated to explain how the characteristics of the properties; the nature of their neighbourhood; and their location influence this ratio. The model consistently validates the hypothesis that the more desirable a property or affluent an area, the lower the rent/price ratio. It also begins to illustrate the range of “normal” rent/price ratios that may exist in housing sub‐markets. The regression model is then used to provide a map of the geographical distribution of the ratio for England for one property sub‐market

A worlds-eye view of the United Kingdom through parliamentary e-petitions

Gaining an understanding of the concerns and aspirations of a country’s diaspora can help domestic politicians to better connect with this community and gain their support in elections. The United Kingdom’s diaspora is large and spread among many countries, and currently has the right to vote in UK general elections only for a limited time. However, there are proposals to abolish these time limits and this will make this community of increasing interest to politicians. This study uses signatories to the UK Parliaments e-petitions platform to gain an understanding of the foreign and domestic political concerns of this community. The analysis uses Latent Dirichlet allocation to identify common topics among the e-petitions and hierarchical clustering to identify commonalities among countries, territories and regions. It is found that there are five meaningful groups of such, and they are diverse in the topics that are of most concern

Linguistic and semantic factors in government e-petitions: A comparison between the United Kingdom and the United States of America

Many legislators around the word are offering the use of web based e-petitioning platforms to allow their electorate to influence government policy and action. A popular e-petition can gain much coverage, both in traditional media and social media. The task then becomes how to understand what features may make an e-petition popular and hence, potentially influential. One area of investigation is the linguistic and topical content of the supporting e-petition text. This study takes an existing methodology previously applied to the American government's e-petition platform and replicates the study for the United Kingdom's equivalent platform. This allows an insight into not only the United Kingdom's e-petition process but also a comparison with a similar platform. We find that when assessing an e-petition's popularity, the control variables are significant in both countries, e-petitions in the United Kingdom are more popular if some named entities are used in the text, and that topics are commonly more influential in America

Using e-petition data to quantify public concerns during the COVID-19 pandemic: a case study of England

The COVID-19 pandemic has had a profound impact on society and many governments and politicians were required to make quick decisions to protect public health. In reaching these decisions they needed to weigh advice from experts in many fields and then “sell” these decisions. However little was known at the time about the desires and aspirations of their electorates. Here we identify one such source of public opinion, signatures to various COVID-19 related Parliamentary e-petitions Whilst there were over 1,500 such e-petitions, we identify 27 common and meaningful topics and show how the strength of these topics varies between individual parliamentary constituencies. Using a measure of support for each topic in the constituencies we identify five constituency groupings. There are two Conservative voting groups, “Middle England” and “Equity of Support”, the former are located largely in southern England whilst the latter are in the midlands and northern England. The groups that show strong support in Labour voting constituencies are ones around education and funding issues. This article shows how a targeted range of e-petitions can be grouped into topics and the popularity of topics established, and thereby function as a useful way of augmenting democracy and democratic institutions