All my coding is finally done! The bf was working super-hard in the run-up to his deadline so every evening when he was watching How I Met Your Mother or Scrubs and designing his building, I was data tagging. I essentially felt guilty if he was working and I wasn’t, which was a great motivator!

So now it’s scary writing-a-new-chapter-time. I think I’m going to start by looking at the rare occasions where things go wrong in my data. People think intercultural communication is full of unintentional impoliteness and misunderstandings, but in my data that’s just not the case, these things do occur, but they’re really rare. I think this chapter will encompass apologies, misunderstandings, aggressive behaviour and mistakes.

I’ve started pulling tagged segments out of QDA Miner today and putting them into Antconc to get an overview of themes. For example, I pulled out all the segments tagged as ‘apologies’, put them into 2 .txt files (one for Liz, one for her clients) and then compared the keywords with a standard British English corpus to show what occurred at a statistically significant frequency:

Antconc apologiesThe number to far-left shows the term’s number in the list, the next shows the frequency in the text (I eliminated anything with only one occurrence) the next number is the ‘keyness’ rating (anything over 3 is in the 95th percentile, so everything in the image is highly relevant). Draw what conclusions you will – I haven’t had time to fully analyse these yet, but it looks to me like the clients (left side) are late and forgetful, whereas Liz misunderstands and does things wrong!

In other news, I’ve also been writing my 4000-word report for my June yr1 viva. So that’s been fun! I hope my progress is PhD-worthy-enough.


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