Saldaña ▒ Codes and Analytic Memos

Saldaña, Jonny (2009). The coding manual for qualitative researchers. London: Sage. (chs. 1 and 2)
Ochs, E. (1979). Transcription as theory.  In E. Ochs & B. Schieffelin (Eds.), Developmental Pragmatics.  New York: Academic Press.
Barron, P. (2010). Four principles of using digital tools to assist humanities research. Retrieved from http://nicomachus.net/2010/10/four-principles-of-using-digital-tools-to-assist-humanities-research/.

I appreicate the fact that Saldaña spells out, deductively and up-front, what his book is and isn't. To me, it is a "repertoire of coding methods in broad brushstrokes" (1) that doesn't hurt to read just to see what the possibilities are. You know, sometimes theories resonate with you and it inspires you to study associated methods in detail, sometimes methods resonate with you and it inspires you to study associated theories in detail. I like that he intends to purposely juxtapose coding methods "to illustrate and highlight the diverse opinions among scholars in the field." (2)

Saldaña gets right to the point and defines the basic unit of his book: "A code in qualitative inquiry is most often a word or short phrase that symbolically assigns a summative, salient, essence-capturing, and/or evocative attribute for a portion of language-based or visual data." (3) When you realize that those attributes are assigned by you, the researcher, it becomes easier to see that data transcription/analysis really is theory generation (Ochs 1979). I appreciate the fact that he defines, then gives several concrete examples from different general approaches to the coding process, and then channels Charmaz to explain why we can't conflate codes and categories...codes are the bones, categories are the starting work in assembling "those bones into a working skeleton" (8), from which will eventually spring themes and theory.
It sounds like we get (have) to code everything, but that as one becomes seasoned, it becomes easier to decide for oneself what can be overlooked. I'm thinking of this as "I know the tell-tale signs of what I'm interested in observing, so that's what I look for", which I get, but does that not stultify your research at some point? How do you keep research fresh and exciting if you are not looking for new things to resonate with you, or is this an admission that you know what will resonate with you, so if you don't see that, you move on?

How would I know? I'm a n00b...

I appreciate the walk through manual and CAQDAS coding (wish I would have seen that elsewhere...). And the attributes! Although, I almost wish the first attribute would have been better explained:

• organization: It frustrates me that he defines organization ("a set of disciplined skills that can be learned and cultivated as habits", p. 28) but, unlike when he defined coding, he offers no concrete examples! What skills? Am I missing all/some/any? I mean, I get that one "will
  ...encounter and manipulate many pages of paper in qualitative work" and that even CAQDAS programs only go so far, but after laying the heavy on us, his advice is to "[d]ate and
  label all incoming data and keep multiple digital and hard copies as backup"? It's a sad day when I have to dig into advice from digital HUMANITIES research to find solace! A recent post from Phillip Barron discusses the more important skill of learning to SEARCH, and that in fact it is increasingly more important than organizational skills, because "[k]eeping your work organized is a valuable skill, but at some point in your research, you are working on a project that is too large to hold in your head." So, "if you have been tagging information all along the way, then you have a way to search through your own stuff." Developing a strong sense of your own folksonomy seems to me a much more valuable way to burn brain cells than the traditional sense of "organization" because, as Barron (correctly, IMHO) points out, "I don’t know about you, but I am never going to remember that a pdf from JSTOR with the filename [dateauthorsmalltag.pdf] is an article on gender discrimination in the death penalty". When looking the data tsunami (Barron channeling Blatecky, not mine...I wish, though!) of a dissertation head-on, tagging and searching skills look a lot more life-saving than organizational skills. Of course, maybe that's what Saldaña was thinking of when he mentioned it. Too bad I'll never know.
• perseverance: No kidding! When one is looking at the prospect of having to eat an elephant, it's perhaps not eating the elephant that seems daunting, but the prospect that you'll be eating elephant omelettes, elephant stew, elephant fricassee, elephant goulash (you get the idea) day in and day out for months. I have no suggestions, I'm hoping you do.
• ambiguity: One of Trena's mantra. I'm OK with this.
• flexibility: You know, I think this goes hand-in-hand with ambiguity. How can one cope with ambiguity if one is not flexible?

I LOVE Saldaña's description of analytic memos...It's where you get reflecive about your data and analyses, codes being "a prompt or trigger for written reflection on the deeper and complex meanings it evokes." (32). He then goes into detail on a few scenarios that he then gives examples for, mentioning that this process will also "generate codes and categories" (41).

Putting the Finish on Grbich

Grbich, C. (2007). Qualitative data analysis: An introduction. Thousand Oaks, CA: Sage Publications. Chs, 14-17.

Grbich, C. (1998) Computing packages for qualitative data measurement: what is their real impact? Australian Journal of Primary Health - Interchange 4 (3): 98-104.

I'm definitely a "theory generation" type of person...theory directing seems a bit too "old-school" for me. Grbich's explanation resonated with me:"where you draw a range of 'theories' from the literature and from available theoretical ideas of relevance. Some of these will fall by the wayside as their explanatory power cannot be sustained in view of your research findings, while you may combine others with what is emerging from the data to form the basis for new theoretical explanations and models of practice." (186)

I was less impressed with the folksonomy she uses to discuss theory and its levels, but the small blurbs on different approaches to theory generation was nice.

I really don't know what to say about "Incorporating Data from Multiple Sources". It just rings false to me. If you have more or less subscribed to the notion that quantitative research in educational psychology places an emphasis on absolutely decontextualized cognitive states and appraisals at the expense of the interactive context in which cognition occurs, and then has the unmitigated gall to pass itself off as somehow more objective, scientific (see: superior), any talk of mixed methods sounds like a request to adulterate your otherwise pristine foray into ambiguity. I'm willing to be convinced otherwise.

I enjoyed the list and description of available display options Grbich put into Chapter 16. I can see referring to that while dissertating to see what would be the best fit for something I wanted to display.

Chapter 17...what to say about Chapter 17? At first, I was thinking that it simply was a bit too "SouthPacific-centric" for my sensibilities...and I still think that way about the layout of the software, most of which I either don't recognize or recognize as being out of date...which a simple nod to a group like the CAQDAS project and mention of some of the programs with staying power would have corrected. But then I noticed in the "concerns" section that (as some of my neighbors might say) Grbich has a dog in this hunt! (see 231) Was this whole thing just a straw-man argument?

Under the general concept of "tools constructed for a particular program must inevitably impact upon the data" (230), Grbich then opens up a five-page salvo (which, to my remembering, she has done nowhere else in this book) on CAQDAS programs, with volleys on the "framing" of knowledge (as if all knowledge wasn't framed), the "texturing" of reality (as if all reality wasn't textured) and its impact on knowledge, the "unnatural" structuring of collaborative communication in CAQDAS programs (as if there was a "natural" communicative structure) and, OMGG, REIFICATION (which she likely says with the same tone of voice as SINGULARITY). She then gives voice (minimally disturbed, I'm sure) to several researchers for a pastiched gripe session she frames as "users' comments".

If you look up her article, she at least admits that all data sets are disturbed by collection and framing, but that computer framing takes it up a notch by adding an additional frame embedded in the metaphors and ideology of the program. The SCT folk would call this "cultures of use", which they argue have existed in all technology from time immemorial, but of course, since we're talking about computers, and since Grbich might have a blind spot to SCT herself, all of the sudden CAQDAS framing is diametrically opposed to the center of a qualitative community of inquiry which values context, thick description and conveyance of participant voice..."minimally disturbed".

At this point I was having only a Tums moment. But then Grbich had to go and get shrill: "The way knowledge is constructed in our society is important, as is the hege­mony of logic which determines which statements become knowledge. As human beings we have the capacity to create an inner representation of life which is multidimensional, complex and characterised by spontaneous reflexive actions. Processes involving segmenting and ordering data "ave the capacity to distance us as researchers, to limit perspectives, and to favour outcomes of homogenisation and standardisation. The tyranny of a system, however useful, which has the capacity to direct and simplify the construction of the views of researchers and ultimately those of readers, will thus always be problematic."

Excuse me, I need to go grab some Tagamet...fast.