Me: Saya mou beli buah (I would like to buy some fruit)
Shopkeeper: buah tida ada (fruit doesn’t exist)
Me: Ok, ada apel? (Ok, do you have any apples?)
Shopkeeper: tidak ada apels (apples don’t exist)
Me: ada jeruk? (do oranges exist?)
Shopkeeper: ya, ada juruk (yes oranges exist)
Me: apa lagi (anything else?)
Shopkeeper: pisang (bananas)
Me: ok, saya minta pisang? (ok, may I have bananas?)
Shopkeeper: ya (yes)
That is an attempt at an amusing example of the difficulty of asking questions here. It’s not that people lie (although it can feel like it sometimes) but that you have to be able to ask the right questions.
It happens in every walk of life – the problem is not too serious when buying bananas, but is more difficult in working life (“have you done X” “ya” – but three days later you find out they haven’t). And in research it is impossible.
My research used four methodologies: participatory problem analysis; case studies; focus groups; and interviews. Until now, I have been working with the preliminary analysis based on feed-back and discussions with the colleagues who conducted the fieldwork. But over this past week I have been analysing the interview data in more detail, and this presents a totally different picture to the one my colleagues painted. Whereas my colleagues said gender was a real issue (women need men’s permission to seek healthcare), the data doesn’t actually support this.
People here don’t respond well to open ended questions. They seem only to tell you what you want to hear, so the interviewees may have told the interviewers what they thought was the ‘right’ answer. Or maybe the anomaly in the results is that the fieldworkers have brought their own biases and opinions to their analysis (i.e. they were telling me what they thought were the ‘right’ answers). My head tells me to work with the data that I’ve got, but my heart tells me to listen to my colleagues. I wish I could find an answer to this problem, but I just can’t ask the right question.
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1 comment:
Hello Whitters! Well, just want to get things clear - you say interviewees told interviewers what they wanted to hear.....so, leaves me a bit confused...
1. Your researchers were expecting the gender thing - but interviewees didint play ball - and therefore guessed wrong?
2. Your interviewers have written up the data they wanted to hear - but didnt collect?
3. Your interviewers have ignored the data and written up what they wanted to hear?
4. Your interviewers wrote up the data accurately and you're all wrong and your respondents told the 'truth'?
Sorry, very confused. Anyway - even if the calculus of 'felicity' works here - the greatest good for the greatest number - one cant ignore the data one has - it could concievanly lead to an international incident, never mind leading to your eternal research damnation and several years in a prison somewhere - for fraud, waisting someone elses money and generally being a very naughty English person.
But, and bear with me hear, one can set data in context - so long as you are very sure about what the data is saying and can explain why such data was collected - methods, questions, researchers - thro them all into the pot to get your '42'. For instance, the biggest finding here could be that 'methods' for gathering data have to take into account local cultrual and societal norms, namely, according to you respondents' reluctance or need to provide false evidance, if thats what it is....Other contextual routes as well - but to get to this point, you need something around context a hellava lot more relaible than your colleagues prejudice/bias. Look up some similar stuff, look at the questions - the line you tred between 'trashing' your work and creating a shining rose from a pigs ear of a weed bed, will be a fine one to walk - but potentially its dooable.
Hope I've made sense - good luck old chap!
dt
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