Blog Archives

Stay on target! We’re too close! Stay on target!*

by Rachel Ridley

     After all the weeks of coding, re-coding, exporting, and now pulling it all together in a final analysis, we are finally at the end. We went through elephants, fences, and machambas [agricultural fields] all the way to standing water, hospitals, and weather (for Health in the SES Model, at least). It seems like we covered so much ground in so little time. I find myself still thinking back to coding interviews about elephant damage and realizing just how extensive this research was and is. I’m continually amazed by it as I sit down and try to bring it all to a close.
     One of the biggest struggles was having to organize all of the exported codes together and find themes in them. The problem is, not all of us (in my group) coded the same things in the same way. At first, this seemed immensely problematic. I kept thinking, “How is this going to add up to make any sense together at all?” But in the end, I think it was important that we had experience working on a project such as this in a group. I know I gained a lot from looking at the way the same thing could be interpreted in multiple ways.
     But now that we’re working on our final analyses, I realize that that wasn’t the hard part. Somehow we’ve got to pull all of what we’ve done through the whole semester into one analysis paper. I keep going back and forth, worrying that I won’t have enough to say and then realizing I probably have too MUCH to say to be concise! How to pull together these complex, interrelated themes without minimizing them or making them larger than life?
     Not to mention it’s the end of the semester (finally!) and there’s all kinds of absurdly long papers and cruel, unusual final presentations to do, and it’s hard to keep focus. I want to make sure that the material I create to finish up this project does the full experience and research justice. I keep stalling by making more and more maps or finding some new way to tie them together (I’m using online mapping software) and waiting around, as if I expect that if I do enough maps, a beautifully crafted full-length analysis will pop into my head, fully formed.
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     In all, I think it’s bittersweet. Of course, here in this moment, I want everything I have to do for the semester to just be over and done with. I want to move on to holiday celebration, sleeping until 2pm, and not having any deadlines to even consider. Yet there’s a whole other part of me that wants it to continue. I want more time and more space to write about it, because in many ways, the interviews – the issues themselves – that we studied became important to me personally. I find myself regularly thinking about the problems and subject matter that I spent so much time organizing and analyzing. In some ways, it has become larger than life for me.
     We’ve all got until Friday to pull our masterpieces together, and I’m hoping we can make them just that! It has been more than fulfilling to spend so much time with this research, so here’s hoping we can all produce some worthwhile thematic analysis from it.
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     The KRAC Lab research assistants this term have struggled mightily to work though a ton of crazy data.  They’ve ridden a rollercoaster from learning how to code all the way through to their final analysis.  Their learning process is very much the same that socio-cultural anthropologists of all levels go through – down to the part of having so much to say and so little space to say it.  Their analyses has contributed to one submitted NSF proposal and two more in the works.  Their work will also go into a report for the Mozambican government and local communities, as well as multiple anticipated articles (and depending on how much work they’ve put in may include their names as co-authors).  I’m really proud of all of them.  ~ JS
* Gold Leader to Gold Five, Star Wars: A New Hope (Ep. IV)

There’s a map for that!

by Adriane Michaelis

If you’ve been following the blog, you know that we’re wrapping up our data analysis for this semester’s projects. Everyone’s been busy–organizing data, looking for themes, and making some amazing Excel spreadsheets. Now we’re taking that analysis one step further, and trying to visualize the big picture (literally). We’ve moved on to map-making. I’m not talking about applying our cartography or ArcGIS skills (though that may come later), instead we’re using the data we’ve been spending so much time with to create mind maps.

What is a mind map you ask? A mind map is “a graphical organization of ideas and concepts that can be used to facilitate the generation of ideas and the learning process” (thanks to Michael Poh for the succinct definition as well as some examples of pretty creative maps). In the spirit of the semester, see the figure below for a mind map that provides a visual schematic of how to prepare for exams.

Instead of making maps to help us study for the end of semester exams, we’ve been mapping our data for each of the three projects, and maybe, just maybe, eventually creating a super-map that incorporates all three projects (or at least aspects of all three). Through the use of many colors, arrows, shapes, and even illustrations for those so inclined, we’re thinking of different ways to consider and visually depict our data. This can be especially helpful when pulling together large qualitative datasets, and will hopefully help guide the next step, putting all of our analyses to paper…as in writing a paper for each group’s project.

One of the more interesting things about the mapping process is that, though we’re attempting to map other people’s interview responses, perceptions, and ways of thinking about certain things, we’re actually getting a glimpse of how each member of the group thinks (mapping our own minds, one might say). As you can probably imagine, there are a number of ways to approach creating a map of a data set, and you can see different approaches and interpretations in the form that each map takes. This is not a bad thing—we can compare maps and reconsider our interpretations to try and create the most appropriate representation of each analysis.

As a final thought, it’s not so bad to have the task of playing with crayons and colored pencils for a bit. 🙂