AEA365 ran a blog on vulnerability vulnerability linkrecently (August 5, 2016). It cited the TED talk by Brené Brown brene brown on vulnerability on the same topic. Although I really enjoyed the talk (I haven’t met a TED talk I didn’t like), it was more than her discussion of vulnerability that I enjoyed (although I certainly enjoyed learning that vulnerability is the birth place of joy and connection is why we are here .

She talked about story and its relationship to qualitative data. She says that she is a qualitative researcher and she collects stories. She says that “stories are just data with a soul”. That made a lot of sense to me.

See, I’ve been struggling to figure out how to turn the story into a meaningful outcome without reducing it to a number. (I do not have an answer, yet. If any of you have any ideas, let me know.) She says (quoting a former research professor) that if you cannot measure it, it does not exist. If it doesn’t exist then is what ever you are studying a figment of your imagination? So is there a way to capture a story and aggregate that story with other similar stories to get an outcome WITHOUT REDUCING IT TO A NUMBER? So given that stories are often messy, and given that stories are often complicated, and given that stories are rich in what they tell the researcher, it occurred to me that stories are more than themes and and content analysis. Stories are “data with a soul”.

Qualitative Data

Yet any book on qualitative data analysis (for example qualitative data coding or Qualitative data analysis ed. 3 or Bernard qualitative data analysis ed 1) you will see that there is confusion in the analysis process. Is it the analysis of qualitative data OR is it the qualitative analysis of data. Where do you put the modifier “qualitative”? To understand the distinction, a 2×2 visual might be helpful. (Adapted from Bernard, H. R. & Ryan, G. W. (1996). Qualitative data, quantitative analysis. Cultural Anthropology Methods Journal, 8(1), 9 – 11. Copyright © 1996 Sage Publications.)

2x2 data analysis

We are doing data analysis in all four quadrants. We are analyzing and capturing the deeper meaning of the data in cell A. Yes, we are analyzing data in other cells (B, C, and D) just not the capturing the deeper meaning of those data. Cell D is the quantitative analysis of quantitative data; Cell B is the qualitative analysis of quantitative data; and Cell C is the quantitative analysis of qualitative data. So the question becomes “Do you want deeper meaning from your data?” or “Do you want a number from your data?” (I’m still working on relating this to story!)

It all depends on what you want when you analyze your data. If you want to reduce it to a number, focus on cells B, C, and D. If you want deeper meaning, focus on cell A. Depending on what you want (and how you interpret the data) will be the place where the personal and situational bias occur. No, you cannot be the “objective and dispassionate” scientist. Doesn’t happen in today’s world (probably ever–only I can only speak of today’s world). Everyone has biases and they rear their heads (perhaps ugly heads) when least expected.

You have to try. Regardless.

my two cents.

molly.

 

 

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