J D Porteous These are the methods used in J Douglas Porteus’ Surname Geography. Professor Porteous attempts to marry data derived from the International Genealogical Index (IGI), General Record Office (GRO) and a current questionnaire. Whether this data nests together without weighting might be a subject for discussion. Nonetheless the principle of using a variety of sources to produce a long timelime is judicious. The article has some excellent graphs, but the author does not always explain how he derived his data, so it is difficult to fully evaluate the effectiveness of his methods. For example, he talks of pre-censal crude county birth rates with no indication of where this data exists. See the illustrative figures. Vital statistics graphs Plot the birth/death figures on the same graph. Add the median line for both. Is there the normal rapid increase in the number of events before circa 1910, followed by an equally rapid decline? Ranking Sort the births by county, and then by period. Rank the counties for each period, and draw a line graph for each of the leading counties. Barcharts Convert the above data to barchart format. A county may remain predominant throughout, or be displaced by others. Relative birth rates (births per million population) by county by period. Numbers placed on a series of county maps, and shaded accordingly. Time frames: 1538-1637, 1638-1737, 1738-1837, 1838-1865, 1866-1894, 1895-1923, 1924-1952, 1953-1979. Source of County population estimates pre-1801? Rickman? Mitchell? Illustrative example needed. Location quotient Comparison of the birth rate of your family name with the county birth rate, and plotted on a graph over time. (Unity refers to a county birth rate equalling the national rate) Porteous cites as his sources the IGI, and the civil registration indexes. It is not evident how he is deriving a county birth rate pre-1837 from the IGI (and rather should it be the crude baptism rate) Timelines For each significant county, create a box with space for 8 numbers. Enter the relevant numbers in the box, which refer to at least one birth event recorded in the period 0 1538-1637 1 1638-1737 2 1738-1837 3 1838-1865 4 1866-1894 5 1895-1923 6 1924-1952 7 1953-1979 8 1980-2000 Thus: North Riding – – 2 – – – 6 7 8 West Riding 0 1 2 3 4 5 6 7 8 Lincolnshire – 1 2 3 – – – – 8 London – – – – – 5 6 7 8 Each row could be positioned on a map, or presented as an overall table. In a particular area, substitute the number of events in the boxes: 1538-1637 1638-1737 1738-1837 1838-1865 1866-1894 1895-1923 1924-1952 1953-1979 1980-2000 North Riding – – 5 – – – 10 8 6 West Riding 5 5 7 7 9 15 8 7 4 Time-lines can be in-depth for a county. As an example, here are the Worcestershire IGI Dances, expressed as an all event timeline. A red box signifies an event. A grey box signifies that there is no IGI coverage of the parish-time, and that the actual registers may hold further Dances. Each time-interval is 20 years. Correlation Rank correlation of x major counties in terms of births, 1838-1979 1838-1865 1866-1894 1895-1923 1924-1952 1953-1979 1838-1865 – 0.429 0.943* 0.943* 0.873 1866-1894 – 0.929* 0.929* 0.771 1895-1923 – 1.000* 0.995* 1924-1952 – 0.995* 1953-1979 – df=4; significant at 0.05% Explanation of how this correlation table is derived is needed. Its significance is that it reveals in the case of this name, a persistent place-loyalty at county-level, rather than long-distance migration. Time-scale paths A series of bifurcating lines (x axis = time; y axis = distance from origin in miles (logarithmic scale), which shows how far migration has affected the holders of a surname who originate from a common ancestor. See the illustrative graph. (Source: J Douglas Porteus Surname Geography in Transactions of the Institute of British Geographers).