Gherardi and Turner’s “Real Men Don’t Collect Soft Data” is one of my favorite essays. Perhaps the faint shadow of my postmodern training as a PhD student in English literature made me sympathetic to the deconstruction of the hard and soft dichotomy. The power of that governing idiom in academe is nonetheless quite significant. I continue to have to ‘live with’ the choice I made to go to the ’soft side’ of the research world. It feels a bit like going to the Dark Side of the Force in Star Wars.

So, how have I survived academically despite this ill-fated choice? The answer is that I never bought the argument that qualitative research must be inferior or more subjective than quantitative research. When we set up the Qualitative Data Analysis Program at UCSUR, the goal was to provide a range of services that allowed PIs to develop rigorous research projects that result in reliable and valid observations and inferences using methods that any researcher could understand. In a recent grant proposal, I described it this way:

As a result of the ongoing collaboration with computer scientists working on human language technologies, the QDAP lab avails itself of several custom built software add-ons (kappa and F-measure reports of reliability, code-by-code match and mismatch tables for validity checking) that allow coding supervisors and the PI to analyze, address, and report reliability and validity issues in the coding. This attention to identifying, managing, and reporting the error inherent in the manual coding of text datasets puts the QDAP lab on a solid scientific footing for conducting qualitative research.

So, truth be told, part of what anchors my own long-term search for credible methods is counting. This is not, however, the straightforward word counting form of content analysis that is derided by some qualitative practitioners. Instead, we focus on counting the number of times independent coders record the same of overlapping observations. I will have more to say about the experimental tools we have built for this purpose. Suffice it to say for now, when Gherardi and Turner ask “do we wish to make the case that the process of measurement, of quantification in itself is damaging to the stature, to the quality and to the dignity of humankind?” my answer is absolutely not. Indeed, it is precisely the willingness to try and integrate the most applicable statistics to this work that makes it interesting and relevant to a wide scholarly audience.

This is a new blog continuing the “fluency blogging” tradition started in earlier classes. Last year, I created my first Qualitative Fluency Blog and last semester it was an IT Fluency Blog. So, you may ask, why all the blogging? Is this really an academic exercise?

The fact is I like the idea of building a searchable, linked, archive of the best moments in a particular class. The blogosphere is a medium that allows and even encourages us to freely use images, text and hypertext in a manner that mind-bogglingly self-organizing. The results may be trivial or profound; likely they are both. For now, I remain intriguigued by the possibilities and reasonably certain this practice fits well in academe.