Humans, not machines, do the crucial work of coding and retrieving—i. The hope that the programme would do more and be able to replace the analytic mind is foolish. Only human researchers can make sense and analytic use of otherwise meaningless operations of the computer—such was the unforgettable lesson given by this little nasty quirk, incorporated into the design of the programme. This was an important and much needed lesson, of course, which was designed to prevent a typical misunderstanding about CAQDAS. Yet, I am convinced that the argument was and still is somewhat misleading.
Indeed, in this paper I would like to suggest that making CAQDAS a substantively irrelevant and purely instrumental technical extension and support of mental processes was a disservice , something of a poke in the eye of all qualitative research. I argue that the entire idea that software essentially represents what occurs in the analyst's head strengthened a classical "methodological" view of qualitative analysis, emphasising the role of a researcher who is superior to his or her research subjects by virtue of special qualities of his or her thinking.
Accordingly, this way of thinking suppressed a non-exclusive, say "ethnomethodological" position, which highlights taken-for-granted material practices and instructability of knowledge production. Such a mentalistic approach, either implicit or explicit, has had two unhappy consequences. First, CAQDAS has developed problematic relationships with those theoretical-methodological positions in qualitative research, increasingly influential among members of the community, that departed from objectivist methodology.
Computer assisted qualitative data analysis is seen as not easily compatible with radical constructivism or post-structuralist understandings of language. Second, a unique opportunity for better understanding qualitative analysis as a set of mediations and embodied practices has been missed. This is really unfortunate, since such an understanding is priceless for our ability to defend, explain and teach qualitative research.
In texts on qualitative research, there is usually an abundance of descriptions of various paradigms, approaches and theoretical frameworks; or of data collection procedures, fieldwork practices or research ethics. But when it comes to practices by means of which a new quality of reading which we call sociological understanding emerges, descriptions often become somewhat vague and poor. There seem to be no intermediaries here, just the lucid mind of the researcher contemplating the data. And it is the mind that is responsible for deduction, induction, generalisation, conceptualisation, comparison—as basically mental operations … [ 5 ].
Such accounts do reveal important things about qualitative analysis. But they are of a limited help. It is especially true when one has to explain to an outsider or to a student in what terms qualitative analysis consists of anything more than a careful reading of data, spiced by providential insights and observations if there ever are any. As a consequence, it is claimed that qualitative research is in fact an art , hardly graspable and transferable DENZIN, , p.
It is emphasised, in response to inquiring questions about "how it is done", that there is no single qualitative method and that analysis of data can hardly be separated from other research-related activities which can subsequently be described at length. Qualitative research is presented as a complex and context-dependent activity that resists a cook-book style of instructions. Similar responses are surely not wrong.
Not per se. But they avoid the main point. Even worse: by avoiding the point they make it even more urgent—how qualitative analysis actually generates a new knowledge , in a distinctive and recognisable way? Conventionally, as we have seen, people are told that it is not by pressing a button in the interface of a computer programme. This would not help, it is believed, because everything important happens in our minds, in a way that is difficult to explain.
My paper takes a different road though. I will try to talk about material practices and inter-actions, rather than of mental operations of an individual. The ambition here cannot be to explain the logic of grounded theory qualitative analysis better and deeper than, e. And because the conceptual usually seems to be overrepresented in qualitative methodology writings, including the STRAUSS's book, I will focus here on the physical.
Of course, we analysts do think. No question about that. But so do all the others, including our research subjects. Therefore it does not make much sense to ground the superiority of sociological knowledge almost exclusively in our mental qualities and in the very act of … thinking. Rather we should focus, as science and technology studies do, on practical manipulations with visible, hearable and palpable pieces of reality that have the power of making the final sentence stronger and more durable than any other competing statement LATOUR , one for all.
In the next section I am going to briefly explain this particular inspiration taken from science and technology studies. Also, I will clarify in what sense it is possible to keep the focus on material practices in the virtual environment of a computer programme. The main part then follows: an attempt to describe the analytical work with Atlas. The most ordinary analytic procedures such as data segmenting and coding, linking or memoing will be presented as practical manipulations with objects visible on the screen.
Precisely these manipulations endow the knowledge arising from qualitative analysis with qualities that make it distinct from ordinary members' knowledge. Furthermore, they enable us to speak of qualitative analysis in an instructable, practical way. The conclusion will discuss some broader theoretical consequences of such reframing of our thinking about qualitative analysis.
Bruno LATOUR in his article on a research expedition to the Amazon forests gives an illustrative example of how contemporary science studies understand the operation of scientific work. The question is how it is possible that scientific texts speak of reality; what constitutes their reference to the things under study. This question of the relation between the word and the world is an old one. But the perspective of science studies comes out with a novel answer to it. As a sociologist of science, LATOUR avoids theoretical concepts of epistemology and offers an ethnographic account accompanied by a set of photographs of various practices by which members of the research expedition "translate" the border between savannah and forest somewhere in Amazonia i.
He emphasises that the empirical evidence he presents contains no traces of a mysterious jump from the world to a word; rather, we can follow numerous small practical operations by means of which reality is more and more loaded with meaning and progressively de-materialised so that it becomes increasingly "textual". There is no direct bridge between the world and the word, only chains of translations—i. Like LATOUR, or many his colleagues, we could follow the series of translations made by qualitative researchers on the move from the field to the realm of textual data.
For instance, something which has happened is narrated by an interviewee; the narration is recorded; the recording is transcribed; the transcript is incorporated to a set of data … each such step meaning that something is lost and something is gained.
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In general, it is materiality what is lost—e. What is gained? Meaning is gained, simply put. This is possible because the gradual loss of materiality brings about new possibilities. Once reality is narrated, recorded, and transcribed we can better manipulate it—store, transport, compress, mark, juxtapose to another realities, cut into pieces, recompose, reorder, etc.
Only thanks to these manipulations we can see and show differences and similarities, emerging patterns, new contexts. Since we proceed in such a way that it is always possible to go back, along the chain of transformations i. Hence the LATOUR's argument, which he so nicely illustrated by the case of the research expedition to the Amazon forest: scientific texts speak of reality not because of a mysterious bond between things and words something philosophers are so busy with , but rather thanks to well-tied chains of small transformations, during which something is preserved while other qualities are lost.
However, I am not so much interested here in reference as a bond between the world and the word which we strive to maintain during the move from the field to analytic work on data. Rather, my task is to apply science studies' imagination to a "next step", i. I would like to show that what is often seen as an achievement of mind can be perhaps better described in terms of practical manipulations with bodies of texts.
But what kind of qualitative analysis am I going to discuss? There exist different traditions and approaches to qualitative analysis 6 and my account will in no case be "methodologically neutral". I should stress right from the beginning that it is not "grounded theory methodology" as a label for a self-contained epistemology that really matters.
Rather, by GTM I refer to a loosely defined set of analytic practices, the use of which is very common among sociologists, ethnographers, psychologists or even historians. There are several good reasons for choosing GTM as an example for my argument. First, the choice is not surprising given the credit the authors of Atlas. Further, whether one likes it or not, GTM enjoys persisting popularity, especially among students and teachers, and aspires to be taken as an overall strategy for non-deductive research projects.
Occasionally, if taken as a generic approach for generating theory out of qualitative data, it is even perceived as a synonym for qualitative research. Last and perhaps most important and in close relation to the above GTM is nowadays a challenged and often misunderstood qualitative paradigm.
Further, software packages organised around the procedures of coding and retrieving contributed to a more or less implicit conviction that grounded theory methodology is nothing but an application of the code-and-retrieve principle. On the other hand, however, the "ecumenical" focus on something-like-grounded-theory-methodology is relatively arbitrary.
In fact, we could try to follow other analytic practices—e. It should be also stressed that I am not going to come out with some new and specific analytical procedures. No new analytical techniques and no new features of Atlas. Instead, I suggest just an alternative "theory" and practice-oriented account of very ordinary and basic procedures we all usually do as analysts. A question might appear: if we are to understand material practices of qualitative analysis, why not to look at a pre-CAQDAS researcher working with real things such as sheets and pieces of paper, printers, colour pencils, scissors, glue and card files?
Such a focus would definitely be possible. And at some moments it could be pretty illuminating. In comparison to that when an analyst works with a specialised computer programme, the only thing he or she can manipulate seems to be pure information—bits and bytes that are thought to represent ideas in researcher's mind.
Indeed, if we consider a computer to be a direct extension of human thinking, we could hardly talk about material practices at all. They have keyboards, mouses, speakers and monitors. And on screens of monitors we can create, see and manipulate various objects. These objects can be of different sizes and shapes; they can be hidden, moved, split, colourised, grouped and regrouped, forgotten and rediscovered on unexpected occasions. In short, computers provide a virtualised environment in which we can not only do all the operations available to the pre-CAQDAS researcher equipped with paper, scissors and pencils, but much more.
Virtual ob jects on the screen are even more shapeable by and embedded in practices than real ones.
What do researchers practically do with Atlas. Let me pick up just a few key moments of the process. I will proceed from what is typical for the beginning of the project to what usually takes place at later stages. In Atlas.
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These are our data. And data, so is the common belief, are what we gather in the field. True, but this is only a half of the story. Because data are also everything that we strive to put on one place , on one table. Or, more exactly, into a single textual laboratory—which has the power to shrink time and space distances between observable phenomena so that everything important is present and under control. We can better understand the point when we imagine what happens when primary documents are assigned to a project to a "hermeneutic unit", as it is called in Atlas.
Adding new documents has important practical consequences: once we open the hermeneutical unit next time we immediately have all the materials at hand. These materials can have various formats—they can be texts, photographs, scanned documents, audio or video recordings. They can even be physically located on various media—on hard disks, optical discs, local network or the Internet. But most importantly, these documents can have their origin in a variety of times and places. They refer to different sites and moments.
Interviews, recorded and transcribed, could have been made, for instance, during last two years in dozens of households and offices in several middle-sized cities. But the interview transcripts, or other data "from the field", are not the only documents that may belong to the primary documents of our project. Other primary documents, depending on circumstances, could be: excerpts from literature on the topic, written down actually during our entire professional career either at home or during study trips abroad; scholarly articles downloaded from online databases and covering several decades of relevant research; selected newspaper articles on the problem, published in the last decades; related official documents obtained from the Internet or coaxed from a range of involved authorities; a project proposal of our research written almost three years ago; e-mail exchanges with colleagues home and abroad that took place when the project proposal was prepared.
And so on. So now we have all this in sight and within arm's reach. Or rather, we have all this available for scrutiny with the help of a few clicks of the computer mouse. While browsing primary documents of the project, we travel in time and space. It is unbelievably easy and fast: click, click.
An interview with Mr. Miller from the city of Plzen, May we talked about how new civil organisations in the Czech Republic had been established in the beginning of s. Click, click. A resolution of the governmental council for NGOs approved one month ago: it suggests a redefinition of the legal status of some non-profit organisations.
My own excerpts from a book on environmental movements, published in I made the excerpts roughly five years ago in Paris when I was writing a short note on new social movements. Now, in the context of these excerpts, what exactly did Mr. Miller say? Click, click, and here we are. When I was reading the book on environmental movements, I did not know about Mr.
Miller's civil association. I was not even interested in it. I had no idea that I would engage, several years later, in a research project on expertise and democracy, for which I would also need interviews with local activists. And at the moment when I was doing my interview with Mr. Miller I only vaguely recollected what the authors of the book had said.
The two events were too distant from each other. Both temporally and geographically.
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And also in terms of their nature, since the former concerns "theory" and broader sociological contexts while the latter is about the production of "empirical evidence" and my own data. But at the present moment they are juxtaposed, next to each other, right at hand: Paris and Plzen, and referring to the early s and early s —here and now. The distance between the two pieces of reality is very small at the present moment, measurable by a few clicks of the computer mouse. They can be carefully compared and confronted. As primary documents, they have standardised headers e.
But it is difficult to juxtapose entire PDs. They are too large.
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There usually is no practical way to squeeze two full transcripts into a single unifying view. We can see more than one PD at once only as a list of items or a set of icons in a window, arranged in various ways. Even more, it is hard to see—at one moment—a single entire PD. Both our visual field and the size of the screen are limited. We can always see but a couple of paragraphs. We need a different kind of object to be able to closely study our data.
Something smaller. That is why we mark some paragraphs or sentences of particular interest as "quotations". In the first view it looks like marking relevant passages on the margin of a book. But the virtual environment allows more: in fact, by marking a piece of data, we not only modify and extend the original PD, but also create a new analytical object —a piece of data separated and freed from its original context.
The separation is never complete though. We can always trace back the quotations to their original location. What is the advantage of having the marked quotations at hand as self-contained objects? We now have our data in a form that better fits the screen and, in its variety and multiplicity, our field of view. Miller said, that is what the governmental resolution stated, and here we have a sociological observation from literature. But now we can work with all these textual pieces together, since the data are transformed in a double way. First, they are reduced in number so that we can focus only on what we have found relevant so far.
Only now can we arrange, on the screen of a monitor, unprecedented rendezvous that occur under our direct visual control: a piece of a legal document a particular paragraph meets a piece of an interview or a passage from an older research report. Do they contradict? In what sense? Now we are in a good position to start arguing about all that.
Indeed, quotations are elementary units of analysis not only because their meanings are reasonably contained and therefore accessible to our minds and mental processing; they are also of reasonable physical size to be grasped and processed in a material way —by eyes, hands, lists and boxes, computer screens. Hence the general point of this paper, i. There is a big "but" in this though. The more quotations we have, the more distant from each other they again become. They are so numerous that one easily gets drowned in data. It takes a long and painful journey to find a way, or even the way, the connection, from one piece to another.
Two relevant passages are often separated from each other by hours of careful reading and browsing. Pieces of data, quotations, need to be somehow ordered to become manageable even in large quantities. This is where the procedure known as coding comes in as a useful strategy.
Codes are names for such groups, indicating what kind of quotations can be found in each particular bundle. Here the gathered documents, interviews, excerpts, scholarly papers, project proposals, and media articles speak, for instance, about "money", here about "legislation" and here about "negotiation". With the help of codes and the virtual Atlas. But codes are not just names, conceptual labels. They are also useful handles with which we can grasp and manipulate respective groups of data-pieces. They can be viewed in lists, hierarchies, network views or as particular occurrences instances when browsing through our data.
Anytime we are doing an operation with a code e. Now, instead of having to freely dig through and through an unsorted heap of quotations, we can proceed more effectively. By means of coding, quotations gain relevance and meaningfulness. Some groups of quotations become closer than others. Coded data selectively shrink analytic distances between some pieces of data, making these elementary units more manageable. In short, they allow for a kind of more efficient, thematically or semantically organised reading. Four principles, on which Atlas.
Exploration is a very general term and can be applied to almost anything we do in qualitative analysis.
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Indeed, coding-and-retrieving refers to not much more than the mere possibility of organised and efficient reading. No matter that so many people cannot imagine that qualitative analysis would consist of anything more than precisely this procedure, a rigorous analytic knowledge originates in something else other than only the coding-and-retrieving activity.
And this something else has something to do with the other two principles, visualisation and serendipity. Each of the analytic objects we create in Atlas. There also are "free" comments, called memos, that can be attached either to more or less than one kind of object. The ways in which comments are used may be different, depending on the kind of commented object and chosen strategy. For instance, comments to individual PDs may contain detailed information about the source of data. Code comments would typically, but not necessarily, be descriptions or explanations of names given to less obvious or less descriptive codes.
In the case of quotations or links, comments might provide explanations of why we have created these objects—i. Memos are a special case. Their importance and analytical use is typically growing together with the progress of our analysis. In memos we integrate partial observations. The integration is not just an abstract mental operation. It corresponds with the ability of memos to be attached to several codes, quotations and other memos at once. We can therefore imagine memos as embryo-paragraphs or -pages of a future research report, already well-founded in empirical data and embedded in a broader argument in the structure of other memos.
Ideally, the report should be at least half-written within Atlas. However, such a dense and empirically grounded network of Atlas. It is the result of a long-term work which goes through and beyond the above-described code-and-retrieve operations. What kind of work? It is generally thought that the main purpose of commenting on analytical objects is to help one's memory. The best way to prevent the ideas emerging from our reading the data becoming lost to our minds is to write these ideas down.
Again, this is a conventional view, in which the use of software promotes and extends our mental capabilities. But there are other benefits of commenting. First of all, it is important to note that commenting is one of the key moves that constitute interpretation of data. By means of writing comments the researcher inscribes him- or herself into the studied material so that it becomes more and more under control.
In the beginning, almost everything we have "on the table" is what others say; as time goes, the others' accounts are extended by our own textual interventions and additions. Brackets that mark quotations emerge on the margin of the main text; code names are attached to some of the quotations; and, above all, we add our comments here and there. After some time, we are studying not exactly the same original data, but a much richer mixture of voices , our own voice being increasingly pervasive among them.
This is how sociological text is produced out of the text of data. No sudden switch from the empirical to the sociological is possible, only slow growing of the latter into the former. Comments should therefore not be seen only as tools for preservation of ideas, but also and perhaps rather more importantly, since the aim of analysis is not to just preserve ideas! As such they should be made whenever possible.
Our ability to add a comment to a possible new free quotation or a link could even be well taken as a test of whether the creation of certain new objects is legitimate. It is typical that beginners produce new analytical objects of Atlas. Seduced by the effortlessness and speed with which new quotations or links can be made, they soon have thousands of coded or free quotations and hardly any item unlinked to anything else, without having an idea what to do with these huge quantities of connected objects.
Careful consideration is in place, especially when non-trivial, "strong links" are at stake. Some would suggest various kinds of rational criteria, but I recommend a pragmatic and almost mechanical one: is there anything worth of putting down about this particular text passage or connection? If yes, then let us create the link with confidence and make the respective comment. But if we are unable to write a comment on the considered link at the time, and only have an uncertain "feeling" or "sensation", then we should hesitate. If theory is to be grounded in empirical data then practical details, such as links grounded in arguments not mentally, but virtually, in the form of written link comments , are observable procedural elements of it.
Creation of quotations is somewhat different in this. The most common purpose for creation of a new quotation is the need to code a piece of data. Often creation of a new quotation and coding can be considered a single operation. We can imagine a procedure technically analogous to creation of free codes, which would consist of marking out only free quotations during an initial reading of data, without thinking of any codes for the time being.
And precisely for the production of free quotations we might use a similar rule as for links: commented free quotations are fully legitimate, uncommented only as exceptions. Let us assume that our data are segmented and coded carefully and with circumspection. Segments and codes are linked to each other by various kinds of relations where appropriate. Comments are attached to created objects and links that are, in fact, analytical objects too , which—as I have just argued—enhances the quality and argumentative groundedness of our work.
In short, a large number of partial and limited analytic considerations have been materialised or rather virtualised in the form of observable and manipulable objects—codes, quotations, comments and links … So far so good. But this surely cannot be the end of analysis, but rather the beginning. What next then? What to start with? There are so many potential points of interest, so many possible questions.
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