Just a clarification to this nice discussion: why not teach the iterative
analytic/annotating strategies below AS the first (main!) processes OF good
"coding," rather than eliminating the word from methods courses? They'll be
told to "code" in all their other classes, so perhaps it's best to make
clear with such analytic exercises that when anthropologists "code" we
strive for systematic understanding while resisting too-easy, self-imposed,
or too-early analyses. . .

Just a thought on language, given the current climate re. ethnography, etc.

Mica Pollock

In my previous message I had  meant to say something in a bit more explicit
way and then rushed into "Send"--so easy to do with e-mail.  So I've
elaborated a bit in this postscript.  It  responds in part  to Mica's wise
observation that in these times of hostile U.S. federal climate for
"ethnography" we need to be able to show how what we do can indeed be
systematic. (Maybe we should even call what we do "coding",  as protective
coloration.)   So here's a few more lines on qualitative foundations for
"careful coding" and quantification.

Here it is.  It wasn't until two years ago (I'm embarrassed to say) that I
realized that the Latin contrast terms  QUALITAS/QUANTITAS made a
distinction that often is overlooked, or misunderstood; one that is
rhetorically useful for qualitative researchers.  "Qualitas" refers to the
KINDS of things there are in the world  (or are in a certain domain of
scientific inquiry), and thus in interpretively oriented ethnography it
refers to those KINDS of things (and KINDS of KINDS) that are relevant to
social actors for the conduct of their everyday lives--more formally,  to
the folk ontology (or ontologies) extant among a particular set of persons
who interact routinely.  So the primary/generic research question in
qualitative research is "What are the kinds of things that are important for
the conduct of social action in this local community of social practice?"
"Quantitas" refers to the AMOUNTS of things there are in the world--thus the
primary question in a quantitative study is "how many of something  are
there in this place in the world?"

A point that quantitative researchers either miss entirely, or
under-recognize,  is that when one asks as a guiding question "how many?"
what one ends up counting are INSTANCES OF KINDS OF THINGS--i.e. there is a
foundation of qualitative judgments about what's there in the world that's
of research interest (and countable) which is prior to and thus underlies
any and every quantitative analysis.  When you are counting instances of the
right KINDS of things, hermeneutically--not just in terms of some
substantive theory or other, but in terms of the points of view of the
social actors whose actions/opinions you are counting,  then your
quantitative analysis can produce valid conclusions.  But when you haven't
got the qualitative foundation/taxonomic framework right--e.g. you are
counting what from members' points of view are apples and oranges but as a
researcher you are  calling them all apples--you can never reach conclusions
that have validity--at least not "interpretive validity" concerning social
action, for meaningfulness to the actor is always entailed in social action
as a notion.

And so, the problem with naive use of the "coding" software is that it asks
the researcher to make snap judgments about QUALITAS and then immediately to
start tabulating QUANTITAS.   That's why "premature typification" is so
dangerous and misleading.  There's nothing wrong with counting things (or,
to my mind, with typification itself)--but you need to take great pains over
time in order to discover the right things to count.  Counting (even fancy
counting, as in inferential statistics) is the easy part.  Discovering the
right kinds--the right entities--to count is the hard part.

We need to be clear about this,  among ourselves and with our quantitatively
oriented colleagues.   I love it when ethnographers count things--if and
when they are very careful about what to count and can show me why they are
counting what they do count.

Frederick Erickson

Kevin,

Although students may fall prey to "premature categorization", such software
is great for indexing all of your data.  In this way, you can actually find
something you wrote about an observation (and forgot about) very quickly.

I used Atlas.ti < http://www.atlasti.de/ > for my dissertation and it worked
very well.  It is a very powerful program that can do most of what most such
programs do.  But I would agree with Fred that Nudist <
http://www.qsr.com.au/ > is a good way to go.  Nudist can do most of the
same things as the more powerful packages and it is better known.  As more
people are familiar with it, working with others is more likely and finding
training sessions for it is easier.

Although the 'learning curve' with these things can be steep, it was well
worth it in my estimation.

-Jim

PS See also,
Barry, Christine A. 1998: 'Choosing qualitative data analysis software:
Atlas/ti and Nudist compared'. Sociological Research Online, vol. 3, no. 3.
http://www.socresonline.org.uk/socresonline/3/3/4.html.

=============================
James Mullooly, PhD
Assistant Professor
Department of Anthropology
California State University, Fresno
http://www.mullooly.homestead.com


From: CAELIST Discussion List [mailto:CAELIST@listserv.vt.edu] On Behalf Of
ken jacobson
Sent: Sunday, September 07, 2003 5:15 PM
To: CAELIST@LISTSERV.VT.EDU
Subject: Re: Recomendations regarding...

Hi, the following system worked with  several thousand pages of field
notes.  I went through the first couple of notebooks and used colored
tabs to try to find categories that seemed to fit the notation. The tabs
got  unwieldy so quickly, that I took my nascent categories and
transferred them to big accounting pads. I gave each book a number and
as I went through the notes numbered the pages. I then listed under a
category (the numbers of which kept grown) on the accounting pad, the
book, page and a brief synopses of the interesting snippet. I suspect
there are computer spread sheets that would work if you're into typing.
When it came time to actually use the data, I  found the system worked
better that I hoped. So the big deal for me is to find categories that
seem to work (their names too can be changed) and then to look for
emergent patterns both within and between categories. Good Luck!!!
Cheers...Ken

Jon Wagner wrote:

Let me build a bit on the comments by Joe and Fred -- by recommending
(as Joe did) the Weitzman and Miles book as an excellent guide to
thinking about different ways that you can use computer software and
by recommending (as Fred did) that you not jump into coding data too
quickly -- while at the same time recommending two software programs
that you should consider, neither of which may be very well known.

The starting point for me in all this is that I used to teach a
section on "coding" in my qualitative research course, but I've
dropped it for the very reasons Fred mentions:  students were just
too, too eager to take a few key terms and start applying them, to
every phrase or paragraph or section in an interview transcript, or
field note, that might fit.  Sometime after that, I'd start getting
questions about what kinds of theory they could use to analyze their
coded data, questions that I had to answer as follows:  "If your data
is already coded, your theory is already set because, at the end of
it all, a code is nothing more or nothing less than a set of terms
that you use to articulate your data with your theory."

Others may disagree, but people who share this notion of coding worry
constantly about getting those terms fixed too soon.  You can't begin
a research projects without some idea of what you want to study, but
you lose a tremendous amount of potentially valuable data every time
you narrow your view of the world/phenomena/etc. to a particular
concept, hypothesis, question, etc.  That's not an argument for
avoiding this kind of focusing, but it is an argument for delaying it
long enough so that HOW you narrow your attention can be informed by
observations and evidence about what you are studying.

So what I teach now, instead of "coding," is "annotation," a process
of making notes on and about observations, field notes, interview
transcripts, video recordings, etc.  This is an iterative process,
because you the make notes about your notes as you go over the
material again, and again, and notes on those notes, etc., all with
the purpose of trying to understand what is going on in/with/at the
place/people/situation you're interested in.  And it's with this idea
of "annotation" in mind -- which, after enough time, attention and
analysis, can lead to an appropriate exercise of the kind "coding"
that too many people are too quick to jump into -- that I'll mention
two programs that have served me, and several of my students, very,
very well.

FileMaker Pro:  If your data are in the form of computer text files
-- interview transcripts, field notes, email postings, etc. -- you
might take a look at a general purpose data base program that does a
great job of handling text.  FileMaker Pro is an excellent candidate,
for this, but some people have also had good luck with Microsoft
Access (including the Centers for Disease Control, where staff have
developed some customized templates that you can download for free).
What FileMaker allows you to do is to identify a chunk of text of any
length -- a word, phrase, paragraph, page , whatever, up to about 64K
(20+pages) -- and treat it as an individual record in a database.
You can attach whatever words you want to this chunk of text to
indicate where it came from, what questions it raises for you, any
notes you want to make about it, suggestions, etc.  You can change
these terms/notes at any time, and you can add, delete or combine
terms as you go along, but at some point of working with your texts
and FileMaker you have lots of chunks of text, each an excerpt from a
particular text file, and about each of which you've noted something
of interest, even in cases where -- and this is what's MOST important
-- ALL you've noted is that this particular chunk is interesting, for
whatever reason.  You can then pull up everything you thought was
interesting for what it suggested about x, or y, or z from all your
different text files, look over everything you thought was
interesting, and try to figure out what the hell you were thinking
when you noted that in the first place.  You can then make some more
notes about that and add those to what you already have.  For lack of
a better word, I tend to call this kind of annotating and wondering
and re-annotating, "data analysis."  Many qualitative data analysis
programs can be helpful in doing this kind of annotation and
retrieval of interesting chunks of text.  The problem is that many of
them also make it TOO easy to skip the annotation, wondering and
re-annotation process (the "data analysis") and just plunge ahead
with "coding" -- which, as I've noted above, implies that you have
already determined the theoretical significance of your data, before
you have analyzed it.

Annotape: A lot of theorizing has already gone on for many
researchers in just getting their data into "text files" in the first
place -- another necessary evil of doing social research.  But maybe
not always necessary. . . If you are working with audio or video
tapes, and you'd like to analyze these in the way I've noted above
(annotating, wondering, re-annotating, etc.) you might want to look
at a program called "Annotape" that lets you write notes on audio
files BEFORE you transcribe them -- not just summaries of the whole
file, but annotations that are attached to discrete segments of an
audio file.  Annotape also works like a data base, so after you've
listened to the audio and attached your notes to specific sections,
you can find every section from every tape you've "annotated" that
refers to term/question x, y, z, etc.  This allows you to do the
annotate-wonder-re-annotate kind of analysis on the audio itself
(which always provides a richer data source than a text
transcription).  If you want to transcribe, you can also use the
program as a full-featured software transcriber -- which can be more
economically, because instead of just turning everything into text
you can focus on segments of audio that you have already determined
through your "data analysis" to be really significant.

Both FileMaker and Annotape work with images as well as text and are
available for both Mac and PC's (while the PC version of Annotape
works with audio, text and images, only the Mac version works with
video).  You can try out Annotape by downloading a demo.  FileMaker
is widely used in lots of administrative offices, so you might be
able to find someone nearby who can show you how it works.  Both
programs fall short of the automatic "theory building" features of
some other dedicated qualitative data analysis programs, but I find
those features somewhat problematic -- for the reasons outlined above.

Having said all this, there's also lots you can do just by reading
and making notes -- in whatever format, media or program you're
comfortable with.

Jon Wagner

What Joe says below seems very sensible,  but I'll up the ante one notch--
my own recommendation is not to use qualitative software at all.  Every
program I've seen asks the analyst to make categorizing judgments too soon
in the analytic process, and then makes it difficult to change the
judgments in subsequent passes through the data--that iterative process
(slightly misleadingly called "constant comparison"--it's not constant, it
stops when you stop because you've ruled out competing interpretations) is
the essential thing.  More generally this process of recursive analysis of
data,  changing your mind as you go along, is called "analytic induction".
For my money it's far more  useful to read about analytic induction--get
clear about what analytic induction is, and how to "do it" by hand on sets
of diverse information sources  (e. g. field notes,  interviews,  site
documents, contextual demographic information, etc.)-- than it is to try to
use the software packages.  Of the software I've reviewed  NUDIST seems to
have the least of this press toward "premature categorization" built into
it--but I still think that if you are a single researcher, collecting your
own information material,  to generate (identify) data from  the information
sources  by hand and then to analyze the data by hand is still the best
approach, and that is what I tell the students in my data analysis
class.

Frederick Erickson

On 9/7/03 10:25 AM, "Joseph Maxwell" <jmaxwell@GMU.EDU> wrote:

 Kevin:

 This is a little bit like asking for recommendations on what kind of
 house to buy for a family of four.  I'd need to know a lot more
 specifics about what kind of data you have, your research questions,
 and your conceptual framework to even make a guess at what would work
 best for you.  For a detailed strategy for selecting qualitative
 analysis software, see Computer Programs for Qualitative Data
 Analysis : A Software Sourcebook, by Eben Weitzman and Matthew B.
 Miles (Sage);  the descriptions of particular programs are somewhat
 out of date, but the general advice is excellent.  For an explanation
 of the difference between categorizing and contextualizing types of
 analysis, and the implications of this for selecting software, see my
 book Qualitative Research Design, An Interactive Approach, pp. 78-81.

 Joe Maxwell



 At 10:44 PM -0700 9/3/03, Kevin M Foster wrote:

 I am looking for recommendations regarding qualitative software. ...
 more specifically, the use would be for the analysis of
gender-specific ethnographic/qualitative data.

 recommendations?

 -Kevin

Jon Wagner

Professor, School of Education, UC Davis
Office:  2397 Academic Surge, UC Davis
E-mail:  jcwagner@ucdavis.edu
PH1:  530-752-5387
PH2:  510-527-5199
FAX:  530-752-5411
Mail:  School of Education,  UC Davis, 1 Shields Ave., Davis, CA  95616

Image Editor, CONTEXTS
http://www.asanet.org/contexts/

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