Tag Archives: WrELFA corpus

On the other side: variations in organising chunks in ELF

Variations in organising chunks aren't that common, but they do tend to stand out.Source: Livio Bourbon via The Telegraph

Variations in organising chunks aren’t that common, but they do tend to stand out.
Source: Livio Bourbon via The Telegraph

When working with ELF data – English used as a lingua franca between second/foreign-language speakers – one of the things that stands out are slight variations in conventional chunks of language. A formulaic chunk like as a matter of fact might be realised as as the matter of fact, or you could hear now that you mention it spoken as now that you say it. There’s no sense in calling them errors, since the variants won’t cause miscommunication, they resemble their conventional counterparts in both function and form, and the less-preferred variant is likely found elsewhere. It’s just not the English native-speaker preference.

These variations are interesting linguistically and they tend to stand out impressionistically for researchers, but I’ve wondered how often these variations actually occur in ELF – both in frequency and also in their distribution relative to conventional forms. It’s not an easy question to answer. Many of these formulaic chunks of language occur infrequently, so finding a couple variants doesn’t really tell you much. The example above of now that you say it occurs twice in the million-word ELFA corpus, with just one instance of the conventional form. Alternatively, as the matter of fact is found in ELFA 21 times compared to just eight occurrences of the expected chunk, but only two speakers account for those 21 instances.

We can see from these examples that a formulaic chunk that rarely shows up won’t reveal much about how often variation occurs among ELF users, across speech events, in different times and places. To find out more, I wanted to start with the highest frequency chunks I could find. These are described by Linear Unit Grammar as organising chunks, the recurring and relatively fixed chunks we use to structure our speech and writing, like on the other hand. Using the corpus freeware AntConc, I looked at the most frequent 3-, 4- and 5-word clusters (aka n-grams) in the ELFA corpus of spoken academic ELF. Keep reading…

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