The UCLan history programme is based around a spine of core, skills-orientated modules. At level 1, Understanding History introduces students to the nature of history as an academic discipline, including the techniques and problems of historical enquiry. At level 2, Sources and Methods in History is offered, which deals in depth with the nature of historical evidence, covering a wide range of primary sources, and the skills needed for the practice of historical investigation. Both modules have a key function in preparing students for third-level dissertation work.
Exercises: working with historical statistics
The exercises described here form part of the Sources and Methods in History module.
Students are given a lecture entitled Statistics without maths, which is supplemented by detailed commentary in the module handbook. A key theme is to demonstrate the essential role that statistics have in historical enquiry and interpretation, whilst giving due recognition to their limitations. Students are presented with tables of statistics taken from UK and USA censuses, along with an accompanying sheet which describes the statistics and poses questions for students to address in seminar discussion.
The tables of figures in examples 1 and 2 below can be found in this PDF document.
Example 1. UK census
These figures are a small part of a summary table, which is derived ultimately from the census enumerators’ schedules that we looked at in the lecture. In its original form it is one big table, with male figures on the left of a central spine, and female figures to the right. I have had to divide it to reproduce it in on A4 paper in a legible format, and I have therefore duplicated the central spine section so you can refer to it easily from male and female figures. To understand the table, read the title very carefully and think out exactly what it means - the words were very carefully selected and are very specific Note that the occupations are organised into groups. They are based upon the official Standard Industrial Classification (which changes over time). Numbers given in italics are breakdowns of these categories, whereas category totals are given in normal print,
The table, like everything in the census, is a fairly direct product of the data collection process. That it is vol X shows how big such census reports are, and this is just one section of table 13. There is therefore an amazing amount of data here for us to reflect on. However, we can only derive what the categories allow us to derive, either directly or by credible inference, so it is important to reflect on what those categories are, and how they shape the questions we ask. In this table, this is particularly clear from women.
1) What exact geographical area does this table refer to?
It is only the rural districts of Lancashire, and we must also note that Lancashire as currently defined is only a remnant of the traditional county. However, given the stereotypes of Lancashire as entirely urban and industrial, the size of the numbers here is worth a comment. Reality is complicated, and students need to be explicit about that.
2) Do these tables tell us anything about the experience of particular, identifiable individuals?
That’s their great weakness – but the schedules do, and when the big tables and schedules are used together you have a resource of great possibilities – though weaker for women as their part-time occupations are often ignored, and they are given as housewife.
3) Do gender-based differences in life experiences appear in the agricultural section?
Yes – look at farmers and farmers’ relatives, foremen and bailiffs, and animal minders. Note gender heritage of dairymaids in cattle section. Also note widows.
4) Contrast the gender differences within farming with those visible for textiles.
Obviously, textiles are very gender-dominated.
5) Do the tables tell us why so many families persisted with small farms instead of seeking jobs in the towns?
No – it’s as simple as that. However, it can show us how prevalent they were (ratio of farmers to workers is very high), thus defeating another stereotype that they had been wiped out by enclosure. That in turn can lead us to reflect on why Lancs (and Yorks) show this pattern. My answer is that labour was so expensive that it made sense for landlords to offer farms that a family could manage without paying wages, and that the reward they got was intangible – independence. But the proof of that would have to come from elsewhere – statistics alone aren’t enough.
Example 2 USA census data
These figures are from a book based around the US Census, and which the Census Bureau collaborated with. However, it is at least one stage further from the original data compared to the UK figures since they are drawn from all the census ever conducted, and have been selected because they are likely to be useful for modern researchers. Historic figures have been extensively reworked for comparability, and we must be even more careful to be sure what each table represents. Moreover, not all figures come from the Census Bureau. Again the categories are not necessarily as simple as they seem to be, especially those relating to ethnicity.
Note that these figures have been collated from more than one census, and then further processed. They are therefore very remote from the original counting, which on the one hand saves you a lot of work in seeking patterns, but in another perhaps pre-empts some of the patterns you might see if doing it for yourself. Some table include non-census material. Note also, this is done for researchers – highly unusual despite the paranoid fears of many students.
I think the answers to the following are clear:
Questions on the extract:
6) How could we use the top table to see if Black slaves had worse living conditions than the White population?
7) What does the middle table tell us about the equality of educational opportunity in the USA in the 1940s?
8) What does the bottom table (and the notes that go with it) tell us about the place of Black people in American society?
9) Where did the evidence on lynching come from?
Contributor: Dr Steve Caunce