Family Name Origins and Intergenerational Demographic Change in Great Britain
Bibliographic Data
| ID | 4853121 |
|---|---|
| Authors | Jens Kandt (0000-0003-0945-6322, CRC for Spatial information), J Van Dijk (0000-0001-5496-425X, University College London), Paul Longley (0000-0002-4727-6384, University College London) |
| Year | 2020 |
| Volume | 110 |
| Issue | 6 |
| Pages | 1726-1742 |
| Publication date | 2020-11-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Annals of the American Association of Geographers (JOURNAL) |
| Journal identifiers | ISSN: 2469-4452 • E-ISSN: 2469-4460 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/24694452.2020.1717328 |
| OpenAlex | W3010730780 |
| Language | EN |
| Citations received | 8 |
| References cited | 42 |
We develop bespoke geospatial routines to typify 88,457 surnames by their likely ancestral geographic origins within Great Britain. Linking this taxonomy to both historic and contemporary population data sets, we characterize regional populations using surnames that indicate whether their bearers are likely to be long-settled. We extend this approach in a case study application, in which we summarize intergenerational change in local populations across Great Britain over a period of 120 years. We also analyze much shorter term demographic dynamics and chart likely recent migratory flows within the country. Our research demonstrates the value of family names in characterizing long-term population change at regional and local scales. We find evidence of selective migratory flows in both time periods alongside increasing demographic diversity and distinctiveness between regions in Great Britain
Bespoke · Demographic change · Economic geography · Genealogy · Geography · Optimal distinctiveness theory · Political science · Population · Sociology · Demographic Trends and Gender Preferences · Demography · History · Names, Identity, and Discrimination Research · Race, Genetics, and Society
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| Unique citing works | 8 |
|---|---|
| Citations per year | 1,33 |
| Citation span | 2020 - 2026 (7) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 5 |