A new "pressure point"

I remember well Piantanida and Garman’s (2009) advice about constructing a logic-of-justification for a research genre. It is not simply a matter of locating a recipe for the study. Instead, one must recognize and sort through the “epistemological and methodological pressure points” in the literature and choose which ideas will best guide the study at hand (Ch. 7, Conventions of a Genre and Logic-of-Justification, para 2).

I had forgotten that Piantanida and Garman had specifically referenced grounded theory as one such genre framed by “contentious literature”!

So, as I began my background reading of constant comparative analysis (with its roots in grounded theory), I was not expecting to encounter a new pressure point.

The tension for me, however, is not within the grounded theory tradition itself but between grounded theory’s constant comparative method and Stake’s (1995) case study method.

I thought I had this part pretty well sewn up: case study research methods, followed by constant comparative analysis, and concluding with activity systems analysis. The path, while not necessarily easy, was at least clear.

Now, a bump in the path. 

Points of departure
On the subjects of generalization and sampling, I see a need to reconcile the different analytic stances of Strauss and Corbin versus Stake. With constant comparative method originating in the grounded theory tradition, and with the purpose of grounded theory being a systematic progression from descriptive to theoretical, is constant comparative analysis compatible with Stake's case study approach?

Time and again, Stake emphasizes that “case studies are undertaken to make the case understandable” (p. 85). He writes, “The function of research is not necessarily to map and conquer the world but to sophisticate the beholding of it” (p. 43). A skilled case researcher should organize his or her report in such a way as to stimulate a resonance with readers, who draw on their own past experiences with past cases to form “naturalistic generalizations” (p. 85).


Case research, then, is never about sampling: “Our first obligation is to understand this one case” (p. 4, emphasis added).

On the other hand, Strauss and Corbin (1998) present a step-by-step process of microanalysis that moves beyond description to conceptualizing and classifying and (eventually) theory building. The basic operations of theory building are 1) asking questions and 2) making theoretical comparisons -- analytic tools that guide and direct theoretical sampling.

In grounded theory, the researcher makes theoretical comparisons when in doubt or confused by the data. "The object, then, is to become sensitive to the number and types of properties that might pertain to phenomena that otherwise might not be noticed or noticed only much later" (Strauss &Corbin, p. 82). Properties and dimensions of one thing are used as tools for examining another.

Strauss and Corbin say the point of theoretical comparison is to move beyond describing and pinning down "facts." The issue, they say, is to move from the particular to the general.

The sticking point
How does the process of theoretical comparison fit with case study analysis?

Stake is clear: case studies don't produce generalizations, they refine them. Through counter example, a case study may help modify an existing generalization, but "the real business of case study is particularization, not generalization. We take a particular case and come to know it well, not primarily as to how it is different from others but what it is, what it does" (p. 8).

Particularization is the avenue to understanding, not generalization.

Or, has constant comparative method (and coding and memo writing, for that matter) become so commonplace within the broad spectrum of qualitative inquiry that it can be logically applied in descriptive case study? Has the constant comparative method become independent of grounded theory as a thematic analysis tool? At what point did the tools of grounded theory work cross over into the mainstream?

For instance, Saldaña (2013) presents six coding methods from the grounded theory “coding canon” in the newest edition of his book: in vivo, process, initial (formerly “open”), focused, axial, and theoretical (formerly “selective”). He says they all can be used in other non-grounded theory studies (p. 51).

At my breaking point

Part of my confusion, I realize now, stems from the fact that I have never clearly resolved in my head if my case is, according to Stake's terms, an "intrinsic" one or an "instrumental" one. In an intrinsic study the unique case itself is the center of attention; in instrumental study the case(s) are selected purposefully based on the researcher’s need to more fully understand an issue. Whatever the case, it’s not a process of sampling.

I think my study is somewhere in the middle: the case was practically handed to me on a silver platter, but my interest is instrumental and pre-existing. I embraced the opportunity to study the case in question because of my own a priori interests.

Stake warns that it is often not easy to categorize one’s work based on these distinctions. The researcher’s interest in the case (intrinsic versus instrumental) dictates the methods of analysis.

Where once I appreciated Stake’s broadminded stance (“..I encourage you readers to be alert for tactics that do not fit your style of operation or circumstances. Before you is a palette of methods” [Introduction, p. xii].), I now barely comprehend his musings on the “mystical side of analysis” (p. 72).

Stake writes,

Where thoughts come from, whence meaning, remains a mystery. The page does not write itself, but by finding, for analysis, the right ambience, the right moment, by reading and rereading the accounts, by deep thinking, then understanding creeps forward and your page is printed. (p. 73)

Whaaat?

Points on a continuum
Must I choose between Stake’s riddles and Strauss and Corbin’s rigidity?

In short, no. But I definitely need to write a clear articulation of the purpose, nature, and selection of my case as part of the logic-of-justification for my analytic methods.

For Stake, the case researcher must be equally inclined toward inductive analysis, which he calls "categorical aggregation," and interpretive analysis, or "direct interpretation." An intrinsic case study requires more direct interpretation, as there is little time or need to aggregate categorical data. Intrinsic case studies are more descriptive, with emphasis on particularization. In contrast, instrumental case studies are more theoretical, with emphasis on induction and generalization.

These analytical methods reside along a paradigmatic continuum with no hard-and-fast boundaries. Stake writes, "The quantitative side of me looked for the emergence of meaning from the repetition of phenomena. The qualitative side of me looked for the emergence of meaning in the single instance" (p. 76).

As with every other stage of the process, reflexivity is key:

Each researcher needs, through experience and reflection, to find the forms of analysis that work for him or her....The nature of the study, the focus of the research questions, the curiosities of the researcher pretty well determine what analytic strategies should be followed: categorical aggregation or direct interpretation. (p. 77)

The point, I think, is it is up to me to argue compatibility between the constant comparative method and Stake. The type and purpose of the case, the conceptual structure of the study, and reflexive management of evolving research questions will determine where I land along the analysis continuum.

References
Piantanida, M., & Garman, N. B. (2009). The qualitative dissertation: A guide for students and faculty (2nd ed., Kindle version.). Thousand Oaks, CA: Corwin.

Saldaña, J. (2013). The coding manual for qualitative researchers (2nd ed.). Los Angeles: SAGE Publications Ltd.

Stake, R. E. (1995). The art of case study research. Thousand Oaks, CA: SAGE Publications.

Strauss, A., & Corbin, J. M. (1998). Basics of qualitative research: Techniques and procedures for developing grounded theory. Thousand Oaks, CA: SAGE Publications.

A new "pressure point"

Dropping the ball

Research is a juggling act. I think to be a successful researcher you must juggle at any given time at least four of the following: data collection, reading, writing, analysis, reflexivity -- always reflexivity and reflection.

Am I leaving anything out? Probably.

This whole semester I thought I was doing well, when, in fact, at most I was tossing around maybe two things at a time. Big deal.

After reading the coding and analysis literature this week, I realize I have dropped a major ball, the analysis one.

I also realize I have some new questions. (See end of post for questions).

Coding, analysis, and interpretation
Coding is a commonly accepted approach to analysis, and, as such, it has its share of critics, who claim it is an over-glorified form of reductionist frequency counting.

In the opening chapters of the new edition of his coding manual, Saldaña (2013) addresses the critics. He says coding is not the end-all, be-all of analysis. Nor is it a discrete stage of analysis done in isolation from other aspects of research.

Saldaña argues that coding does not distance the researcher from his or her data:

If you are doing your job right as a qualitative researcher, nothing could be further from the truth. Coding well requires that you reflect deeply on the meanings of each and every datum. Coding well requires that you read and reread and reread yet again as you code, recode, and recode yet again. Coding well leads to total immersion In your data corpus with the outcome being exponential and intimate familiarity with its detail, subtleties, and nuances. (p. 39)

I so need to do this. I haven't been handling the data well at all. I have been amassing it, stockpiling it, peering at it occasionally with heavy heart as I do with hampers of dirty laundry. In fact, I now have piles of neatly folded, laundered clothes, and no grasp of my study. I will choose laundry any day over the challenge of data analysis.

The readings on coding and analysis cause me to feel a pit in my stomach as I realize how far removed I have become from the actual texts of my study. I haven't transcribed in weeks. I haven't touched, much less reflected on, field notes, emails, and other artifacts from last semester. I acquired a thick folder of documentation from one of the key informants for my study, and the documents still sit where I left them two weeks ago.

Worse, I have been continually conducting interviews with participants for the last three months, without the benefit of immersion in the data to guide or shape my interactions with those participants.

In their discussion on the process of line-by-line microanalysis, Strauss and Corbin (1998) write, "We are moved through microanalysis by asking questions, lots of them, some general but others more specific. Some of these questions may be descriptive, helping us ask better interview questions during the subsequent interviews" (p. 66).

I should be forming theoretical questions that probe relationships between concepts and then asking these question during follow-up interviews.

I just concluded the first round of interviews. Time is running out for follow-ups, as my participants are classroom teachers who will not relish being interviewed over summer vacation. This is a potential problem.

Analytic memos
And because I have not been immersed in the data, I also have not generated a single analytic memo about the data, not since last semester. This is another problem.

Analytic memos are the raw materials for what will ultimately become the “theoretic text,” in which the researcher “finally sees the theoretic interpretation – core thesis – he or she wants to put forward” (Piantanida & Garman, 2009, Ch. 13, para 1). They are initiated by “aha moments” and “conceptual leaps” that put “the myriad individual, idiosyncratic, and situational details into a meaningful, coherent, theoretic perspective” (para 2).

According to Saldaña, "Virtually every qualitative research methodologist agrees: whenever anything related to and significant about the coding or analysis of the data comes to mind, stop whatever you are doing and write a memo about it immediately" (p. 42).

Richardson (1994) refers to analytic memos as "theoretical notes." These are the researcher's hunches, hypotheses, connections, and/or critiques about what is being seen and heard in the field. The researcher opens up his or her texts to interpretation and a "critical epistemological stance" (p. 526).

Memo writing goes hand-in-hand with analysis. All sorts of memos may be generated during research, but the analytic ones mark the researcher's first attempts at creating findings.

In writing workshop, instructors guide their students: "Don't get it right, get it writ." This advice applies to the research memo as well. Saldaña says just write the memo; worry about the title and category later. He explains,

I simply write what is going through my mind, then determine what type of memo I have written to title it and thus later determine its place in the data corpus. Yes, memos are data; and as such they, too, can be coded, categorized, and searched with CAQDAS programs. Dating each memo helps keep track of the evolution of your study. Giving each memo a descriptive title and evocative subtitle enables you to classify it and later retrieve it through a CAQDAS search. (p. 42)

Grounded Theory and ATLAS.ti
One thing that has become more transparent to me in the coding and analysis readings is the connection between grounded theory and ATLAS.ti.

Some researchers distrust CAQDAS tools because “enduring foundationalist epistemologies are clearly being drawn on in their design and programming” (Brown, 2002). After reading portions of Strauss and Corbin’s (1998) handbook on grounded theory, I finally see what the critics are talking about. Key features of ATLAS seem to be borrowed directly from the grounded theory genre: open codes, in vivo codes, network views (Strauss and Corbin call them “diagrams”), and the integration of memos.

Strauss and Corbin did not claim to know much about computers in their 1998 volume, but they specifically mention ATLAS.ti as “more geared toward theory building” (p. 276) and reproduce a memo from ATLAS developer Heiner Legeiwe that says as much.

Questions:

• Both the grounded theory guidelines as well as Saldaña’s book refer to the use of categories. How does one denote categories in ATLAS.ti? I have been using prefixes to organize codes upfront, so my prefixes are definitely not categorical. They are simply organizational/topical in nature. Is this what code families are for? Does it matter?
• Saldaña refers to “subcodes” and “subcategories.” How can these be represented in ATLAS.ti?

References
Brown, D. (2002). Going digital and staying qualitative: Some alternative strategies for digitizing the qualitative research process. Forum Qualitative Sozialforschung/Forum: Qualitative Social Research, 3(2). Retrieved from http://www.qualitative-research.net/index.php/fqs/article/viewArticle/851

Piantanida, M., & Garman, N. B. (2009). The qualitative dissertation: A guide for students and faculty (2nd ed., Kindle version.). Thousand Oaks, CA: Corwin.

Richardson, L. (1994). Writing: A method of inquiry. In N. K. Denzin & Y. S. Lincoln (Eds.), Handbook of qualitative research (pp. 516–529). Thousand Oaks, CA: SAGE Publications, Inc.

Strauss, A., & Corbin, J. M. (1998). Basics of qualitative research: Techniques and procedures for developing grounded theory. Thousand Oaks, CA: SAGE Publications.

Saldaña, J. (2013). The coding manual for qualitative researchers (2nd ed.). Los Angeles: SAGE Publications Ltd.

Dropping the ball