Individual exercises to help test your understanding and knowledge of key areas of text. Complete them to see your strengths and weaknesses.
A group of students have been struggling to perform an onerous but nevertheless important task: a so-called ‘literature review.’ Basically, rather than write an essay on something or other out there in the world, like the human slaughter industry or the joy of anaerobic digestion, they need to write about how geographers have written about something or other. Fifteen journal articles, several books, and four weeks later the reviews are in. Although they have read a vast amount they still find it hard to get a grip on what academics think about things. Imagine their dismay when I suggested this short cut after the event. Take any textbook – perhaps this one – and go and get a very old textbook on the same subject from the library (say something from the 1990s). Open their indexes and make three lists of words and phrases: (1) those that appear in both; (2) those that only appear in the old textbook; and (3) those that only appear in the new textbook. What are the dominant themes within each of the lists? Now, compare what has been preserved within the subject (list 1), what has been purged from the subject (list 2), and what has been added to the subject (list 3). What does this tell you about the changing interests of geography and geographers? Do these changes amount to progress? If you are really pressed for time, try the same procedure with the contents pages instead. This will give you a sense of how the subject is structured and the relative importance of various issues and debates.
When faced with the inconvenience of long indexes, feel free to restrict your textual analysis to a workable range of letters: say M–R. For those with a quantitative bent, try drawing inferences about the population of the entire index from this sample, jot down how confident you are about your inferences, and then compare your expected results with what is actually the case. This should alert you to the fact that quantitative analysis is a particular way of thinking rather than a fixation on numbers per se. If you extrapolate this way of thinking to vast amounts of textual data – such as Hansard’s verbatim report of the proceedings of the UK’s House of Commons and House of Lords, or William Shakespeare’s entire œuvre (including the recipes), or every use of the phrase ‘I feel’ on social media over the last three months ‒ then one can subject these ‘populations’ as a whole (these ‘universes of discourse’), or ‘samples’ thereof (so-called ‘corpora’), to the usual array of descriptive and inferential statistics in order to tease-out significant patterns in the data. (For example, given the feelings expressed on social media, where in the world do young women ‘feel’ especially happy or lonely or enraged?) This study of language through ‘real-world’ samples of text is called Corpus Linguistics, and it is flourishing in an environment characterized by an explosion of electronic data and the ability of computer programs such as WordSmith to digest them.