Category Archives: podcasts

Mule Bites is the Stubborn Mule podcast. The Stubborn Mule
is a blog exploring economics, science, politics, the environment
and just about anything that can be subject to some objective
analysis.

How common are common words?

One of my favourite podcasts is Slate’s Lexicon Valley. All about language, it is rigorous and detailed in its approach to the subject, which appeals to the closet academic in me, but also extremely entertaining. It is a sign of a good podcast to find yourself bursting out laughing while walking down a busy city street. Lexicon Valley is to blame for numerous moments of alarm for my fellow commuters.

In September last year, hosts Mike Vuolo (the knowledgeable one) and Bob Garfield (the funny one) interviewed linguist Geoffrey Nunberg, talking to him about his recent book, Ascent of the A-Word: Assholism the First Sixty Years. A half hour discussion of the evolution of the word “asshole”helps earn this podcast an “Explicit” tag in the iTunes store and, as a result, this will be the first Stubborn Mule post that may fall victim to email filters. Apologies in advance to anyone of a sensitive disposition and to any email subscribers this post fails to reach.

Nunberg traces the evolution of “asshole” from its origins among US soliders in the Second World War through to its current role as a near-universal term of abuse for arrogant boors lacking self-awareness. Along the way, he explores the differences between profanity (swearing drawing on religion), obscenity (swearing drawing on body parts and sexual activity) and plain old vulgarity (any of the above).

The historical perspective of the book is supported by charts using Google “n-grams”. An n-gram is any word or phrase found in a book and one type of quantitative analysis used by linguists is to track the frequency of n-grams in a “corpus” of books. After working for years with libraries around the world, Google has amassed a particularly large corpus: Google Books. Conveniently for researchers like Nunberg,with the help of the Google n-gram Viewer, anyone can analyse n-gram frequencies across the Google Books corpus. For example, the chart below shows that “asshole” is far more prevalent in books published in the US than in the UK. No surprises there.

"Asshole" frequency US vs UKUse of “asshole” in US and UK Books

If “asshole” is the American term, the Australian and British equivalent should be “arsehole”, but surprisingly arsehole is less common than asshole in the British Google Books corpus. This suggests that, while being a literal equivalent to asshole, arsehole really does not perform the same function. If anything, it would appear that the US usage of asshole bleeds over to Australia and the UK.

Asshole/Arsehole frequencies“asshole” versus “arsehole”

Intriguing though these n-gram charts are, they should be interpreted with caution, as I learned when I first tried to replicate some of Nunberg’s charts.

The chart below is taken from Ascent of the A-word and compares growth in the use of the words “asshole” and “empathetic”. The frequencies are scaled relative to the frequency of “asshole” in 1972* . At first, try as I might, I could not reproduce Nunberg’s results. Convinced that I must have misunderstood the book’s explanation of the scaling, I wrote to Nunberg. His more detailed explanation confirmed my original interpretation, but meant that I still could not reproduce the chart.

Nunberg's chart: asshole versus empathy

Relative growth of “empathetic” and “asshole”

Then I had an epiphany. It turns out that Google has published two sets of n-gram data. The first release of the data was based on an analysis of the Google Books collection in July 2009, described in the paper Michel, Jean-Baptiste, et al. “Quantitative analysis of culture using millions of digitized books” Science 331, No. 6014 (2011): 176-182. As time passed, Google continued to build the Google Books collection and in July 2012 a second n-gram data set was assembled. As the charts below show, the growth of “asshole” and “empathetic” is somewhat different depending on which edition of the n-gram data set used. I had been using the more recent 2012 data set and, evidently, Nunberg used the 2009 data set. While either chart would support the same broad conclusions, the differences show that smaller movements in these charts are likely to be meaningless and not too much should be read into anything other then large-scale trends.

Empathy frequency: 2009 versus 2012Comparison of the 2009 and 2012 Google Books corpuses

So far I have not done very much to challenge anyone’s email filters. I can now fix that by moving on to a more recent Lexicon Valley episode, A Brief History of Swearing. This episode featured an interview with Melissa Mohr, the author of Holy Shit: A Brief History of Swearing. In this book Mohr goes all the way back to Roman times in her study of bad language. Well-preserved graffiti in Pompeii is one of the best sources of evidence we have of how to swear in Latin. Some Latin swear words were very much like our own, others were very different.

Of the “big six” swear words in English, namely ass, cock, cunt, fuck, prick and piss (clearly not all as bad as each other!), five had equivalents in Latin. The only one missing was “piss”. It was common practice to urinate in jars left in the street by fullers who used diluted urine to wash clothing. As a result, urination was not particularly taboo and so not worthy of being the basis for vulgarity. Mohr goes on to enumerate another five Latin swear words to arrive at a list of the Roman “big ten” obscenities. One of these was the Latin word for “clitoris”, which was a far more offensive word than “clit” is today. I also learned that our relatively polite, clinical terms “penis”, “vulva” and “vagina” all derive from obscene Latin words. It was the use of these words by the upper class during the Renaissance, speaking in Latin to avoid corrupting the young, that caused these words to become gentrified.

Unlike Nunberg, Mohr does not make use of n-grams in her book, which provides a perfect opportunity for me to track the frequency of the big six English swear words.

Big 6 SwearwordsFrequency of the “Big Six” swear words

The problem with this chart is that the high frequency of “ass” and “cock”, particularly in centuries gone by, is likely augmented by their use to refer to animals. Taking a closer look at the remaining four shows just how popular the use of “fuck” became in the second half of the twentieth century, although “cunt” and “piss” have seen modest (or should I say immodest) growth. Does this mean we are all getting a little more accepting of bad language? Maybe I need to finish reading Holy Shit to find out.

Big 4 Swear WordsFrequency of four of the “Big Six” swear words

* The label on the chart indicates that the reference year is 1972, but by my calculations the reference year is in fact 1971.

Job guarantee on “Mule Bites”

It’s official! The Mule Bites podcast has been launched.

Regular readers will know that I travelled to Newcastle at the beginning of the month for the 12th annual CofFEE conference. Conference organiser and director of CofFEE, Professor Bill Mitchell, was kind enough to allow me to interview him after the conference. Fortunately, a couple of failed attempts to get the recorder to work did not exhaust Bill’s patience and I ended up with about half an hour of audio covering both Bill’s idea of a “job guarantee” to achieve full employment and a discussion of the nature of money. The workings of fiat money is a subject I have discussed a number of times here on the blog, so I thought that the job guarantee would make a good first podcast topic.

For those not satisfied with the 16 minutes in this podcast, I am planning another episode with the money discussion and will also make the full, unedited interview available.

Audio credits: Mule Bites theme by ToastCorp, train sounds CC by Robinhood76.

UPDATE: there were some balance problems in the audio mix, which have now been improved. Thanks for the feedback, keep it coming! I am well on my way to learning basic audio engineering.