Family names as indicators of Britain’s changing regional geography

In recent years the geography of surnames has become increasingly researched in genetics, epidemiology, linguistics and geography. Surnames provide a useful data source for the analysis of population structure, migrations, genetic relationships and levels of cultural diffusion and interaction between communities. The Worldnames database (www.publicprofiler.org/worldnames) of 300 million people from 26 countries georeferenced in many cases to the equivalent of UK Postcode level provides a rich source of surname data. This work has focused on the UK component of this dataset, that is the 2001 Enhanced Electoral Role, georeferenced to Output Area level. Exploratory analysis of the distribution of surnames across the UK shows that clear regions exist, such as Cornwall, Central Wales and Scotland, in agreement with anecdotal evidence. This study is concerned with applying a wide range of methods to the UK dataset to test their sensitivity and consistency to surname regions. Methods used thus far are hierarchical and non-hierarchical clustering, barrier algorithms, such as the Monmonier Algorithm, and Multidimensional Scaling. These, to varying degrees, have highlighted the regionality of UK surnames and provide strong foundations to future work and refinement in the UK context. Establishing a firm methodology has enabled comparisons to be made with data from the Great British 1881 census, developing insights into population movements from within and outside Great Britain

Impact Evaluations and Development: Nonie Guidance on Impact Evaluation

In international development, impact evaluation is principally concerned with final results of interventions (programs, projects, policy measures, reforms) on the welfare of communities, households, and individuals, including taxpayers and voters. Impact evaluation is one tool within the larger toolkit of monitoring and evaluation (including broad program evaluations, process evaluations, ex ante studies, etc.).The Network of Networks for Impact Evaluation (NONIE) was established in 2006 to foster more and better impact evaluations by its membership -- the evaluation networks of bilateral and multilateral organizations focusing on development issues, as well as networks of developing country evaluators. NONIE's member networks conduct a broad set of evaluations, examining issues such as project and strategy performance, institutional development, and aid effectiveness. By sharing methodological approaches and promoting learning by doing on impact evaluations, NONIE aims to promote the use of this more specific approach by its members within their larger portfolio of evaluations. This document, by Frans Leeuw and Jos Vaessen, has been developed to support this focus.For development practitioners, impact evaluations play a keyrole in the drive for better evidence on results and development effectiveness. They are particularly well suited to answer important questions about whether development interventions do or do not work, whether they make a difference, and how cost-effective they are. Consequently, they can help ensure that scarce resources are allocated where they can have the most developmental impact

Multi-scale morphology of the galaxy distribution

Many statistical methods have been proposed in the last years for analyzing the spatial distribution of galaxies. Very few of them, however, can handle properly the border effects of complex observational sample volumes. In this paper, we first show how to calculate the Minkowski Functionals (MF) taking into account these border effects. Then we present a multiscale extension of the MF which gives us more information about how the galaxies are spatially distributed. A range of examples using Gaussian random fields illustrate the results. Finally we have applied the Multiscale Minkowski Functionals (MMF) to the 2dF Galaxy Redshift Survey data. The MMF clearly indicates an evolution of morphology with scale. We also compare the 2dF real catalog with mock catalogs and found that Lambda-CDM simulations roughly fit the data, except at the finest scale.Comment: 17 pages, 19 figures, accepted for publication in MNRA

Red Supergiant Candidates for Multimessenger Monitoring of the Next Galactic Supernova

We compile a catalog of 598 highly probable and 79 likely red supergiants (RSGs) of the Milky Way, which represents the largest list of Galactic RSG candidates to date. We matched distances measured by Gaia DR3, 2MASS photometry, and a 3D Galactic dust map to obtain luminous bright late-type stars. Determining the stars' bolometric luminosities and effective temperatures, we compared to Geneva stellar evolution tracks to determine likely RSG candidates, and quantified contamination using a catalog of Galactic AGB in the same luminosity-temperature space. We add details for common or interesting characteristics of RSG, such as multi-star system membership, variability, and classification as a runaway. As potential future core-collapse supernova (SN) progenitors, we studied the ability of the catalog to inform the Supernova Early Warning System (SNEWS) coincidence network made to automate pointing, and show that for 3D position estimates made possible by neutrinos, the number of progenitor candidates can be significantly reduced, improving our ability to observe the progenitor pre-explosion and the early phases of the core-collapse supernova.Comment: 21 pages, 10 figures, 5 table. Comments welcom

Using the Global Positioning System (GPS) in household surveys for better economics and better policy

Distance and location are important determinants of many choices that economists study. While these variables can sometimes be obtained from secondary data, economists often rely on information that is self-reported by respondents in surveys. These self-reports are used especially for the distance from households or community centers to various features such as roads, markets, schools, clinics and other public services. There is growing evidence that self-reported distance is measured with error and that these errors are correlated with outcomes of interest. In contrast to self-reports, the Global Positioning System (GPS) can determine almost exact location (typically within 15 meters). The falling cost of GPS receivers (typically below US$100) makes it increasingly feasible for field surveys to use GPS as a better method of measuring location and distance. In this paper we review four ways that GPS can lead to better economics and better policy: (i) through constructing instrumental variables that can be used to understand the causal impact of policies, (ii) by helping to understand policy externalities and spillovers, (iii) through better understanding of the access to services, and (iv) by improving the collection of household survey data. We also discuss several pitfalls and unresolved problems with using GPS in household surveys