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9: Computers and Qualitative Analysis

9: Computers and Qualitative Analysis

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Figure 11.2 Coded Text in MaxQDA

models, and theories. Researchers can relate the various
materials by coding relevant sections of text, by linking them,
or by writing about them.” Software allows you to enter
codes, sort by codes, add comments to texts, run multiple
analyses by adding or dropping different categories, and
generate a variety of custom reports. In other words, they
work similarly to quantitative analysis programs.
Software packages also facilitate team projects. By setting up a software “project,” users create a shared space in
which all data files, code systems, supporting materials,
queries, and output are kept and managed. With a common interface, multiple users can update or view the data
without overwriting each other’s work.
Figure 11.2 shows a screenshot from MAXQDA in
which the text of an interview has been coded by the
researcher, with paragraph numbers inserted by the program. In this excerpt, the entire section of the interview
is marked with the code “work issues,” while the one
paragraph shown is marked with the codes for “interests”

Figure 11.3 Network Output in ATLAS.ti

and “education.” Users can perform searches for all data
within any project folder with specific codes or combinations of codes. You can also run summary information
for each case (interview). In the screenshot shown in the
figure, you can also see that the researcher has attached a
note (■) to the paragraph.
Qualitative software programs also offer a variety of
visual displays of data in multiple forms, often interactive.
Figure 11.3 shows a network view of links among different
data sources, produced by ATLAS.ti. The visual representation is informative on its own, revealing connections among
different data segments. Additionally, the user may select
which codes are included or excluded from the output, in
which combination. In the language of the software, this
view shows different data objects and their relationships.
Qualitative analysis software packages offer a variety
of visual displays to help researchers discover, analyze,
and present relationships within their data. Figure 11.4
shows a word tree relating a single-code category to the

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An Introduction to Content Analysis 199

Figure 11.4 Word Tree in NVivo
and whether that’s from overfishing
high rises . multi - family buildings

,

as diseases . like dermo . and

,

becoming poorer with
being reduced
which is being squandered

definition Paragraph 6 : Effects
deteriorating because

and development

Pollution

of

out what the rivers bring quality . or has been ? Dorothy
almost destroyed due
priceless and vulnerable

like stormwater . Oysters grow by

. I really don’t know . Agriculture

by

just mentioned ? Robert I’m sure

I can’t tell you . But

to

due to chemical runoff from
from over development
has something to do with
industries .
problems on sea turtle nesting
Section and introduction Paragraph 7 :

Understanding . assessing . and resolving light

places and ways in which that code occurs throughout the
data. Importantly, however, we must remember that the
software can only give us back interpretable versions of
what we put in. The researcher defines the codes, identifies
the data to associate with them, and defines the queries
concerning the relations among them. The pictures in the
examples given here do not reveal the “truth” of the data.
They show the relations coded by people and entered into
a program.
The following is a list of just a few Internet sites that
might allow interested readers to begin their journey into
the vast world of qualitative research tools.
1. QualPage, a resource listing for qualitative researchers:
http://www.qualitativeresearch.uga.edu/QualPage/
2. Qualitative Report, an online journal that also provides
an alphabetized listing of helpful qualitative research
Web sites on a variety of interesting topics: www.nova.
edu/ssss/QR/
3. ATLAS.ti, a software site designed for qualitative text,
audio and video data: http://www.atlasti.com/
4. CAQDAS Network, a general listing of computerassisted qualitative analysis Web sites: http://caqdas.
soc.surrey.ac.uk/
5. MAXQDA, qualitative data analysis software: http://
www.maxqda.com/

11.10: Why It Works
11.10 outline the advantages of content analysis
Perhaps the most important advantage of content analysis
is that it can be virtually unobtrusive (Webb, Campbell,
Schwartz, & Sechrest, 2004). Content analysis, although

useful when analyzing depth interview data, may also be
used nonreactively: No one needs to be interviewed; no
one needs to fill out lengthy questionnaires; no one must
enter a laboratory. Rather, newspaper accounts, public
addresses, libraries, archives, television shows, movies,
and similar sources allow researchers to conduct analytic
studies.
Nonreactivity means that the information that we are
coding existed before we came along and was not influenced at all by our research process or objectives. When
we analyze a speech, it is a form of communication chosen
and presented entirely by the speaker and not shaped
by our questions. When we examine the lyrics to songs,
these songs were deliberately written and presented to
the public for their own communication value. Our work
is “clean.”
An additional advantage is that content analysis is
cost-effective. Generally, the materials necessary for conducting content analysis are easily and inexpensively
accessible. One college student working alone can effectively undertake a content analysis study of written public opinions, whereas undertaking a national survey, for
instance, might require enormous staff, time, and expense.

11.11: Why It Fails
11.11 recall causes why content analysis may fail
The most serious weakness of content analysis may be
in locating appropriate unobtrusive content relevant to
the particular research questions. In other words, content
analysis is limited to examining already-recorded messages. The unobtrusive nature of the work means that we

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rely on existing content rather than generating our own.
Although these messages may be oral, written, graphic,
or videotaped, they must be recorded in some manner
in order to be analyzed. We are therefore often limited
to the examination of records that others have decided
were worth preserving. Of course, when you undertake
content analysis as an analysis tool rather than as a complete research strategy, such a weakness is minimal. For
example, if researchers use content analysis to analyze
interview data or responses to open-ended questions
(on written questionnaires), this weakness is virtually
nonexistent.
A variation on this problem is that long before we
begin our data sampling, the available pool of data has
been limited to just that which has been compiled or
created through the work of filters that we can’t see. As
an obvious example, I might want to look at the comments section of a news Web site to see how readers
have responded to news stories on a particular topic. But
would anyone seriously suggest that the pool of people
who leave comments online in any way represent the
population of readers? My guess is that no matter what
topic you chose, from news about abortions to news
about kittens, the overwhelming trend of online comments would indicate that readers are angry about that
thing. The analysis might be excellent, but the data itself
has already been invisibly filtered through the social
world of the Internet.
Another limitation (although some might call it a
weakness) of content analysis is that it is often ineffective for testing causal relationships between variables.
Researchers and their audiences must resist the temptation

to infer such relationships unless the data collection has
been particularly designed around this relationship, as
might be the case with interview data. This issue reiterates the point made previously about motivations: We can
use content analysis to say what is present, but not why.
Causality may be suspected or suggested by the patterns
of association among measured phenomena, but other
means must be used to test that idea.

Trying iT OuT
Suggestion 2
Without writing their names on the paper, have everyone in your
class write a response to the following question: If you could
change one thing in the world today, what would it be?
Ask each classmate to write his or her gender or age at the
bottom of the response, but remind them not to write their names.
Have each person make enough photocopies to distribute one
copy to every person in the class. Now everyone has a set of data
to work with.
Next, go through the responses and see if you can locate any
patterns of similarity or difference. Sort the responses into groups
according to the patterns or themes that emerge as you read
through the responses. Try to make the following assessments:
1. How many times have students identified the same (or very
similar) things they would change if they could?
2. What proportion of the class used identical words to describe
what they would change?
3. Are patterns any different if you first sort them according to
gender?
4. Are patterns any different if you first sort them into the following age groupings: young, older, oldest?

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Chapter 12

Writing Research: Finding
Meaning in Data
Learning Objectives
After studying this chapter, you should be able to:
12.1 Evaluate the evils of plagiarism.
12.2 Relate the identification of the research

purpose to the identification of the
research question.
12.3 Illustrate the contents of the typical

sections of a research paper.
12.4 Identify common terms and language for

things related to publications.
12.5 Describe two major outlets for the

dissemination of social scientific research
information.
Suppose you were to do extensive research on people
trying to solve the Rubik’s Cube. And suppose you discovered something from that. Would you want to tell the
world, “I just learned something about the Rubic’s Cube”?
Or, would you rather say, “I just learned something about
how people solve puzzles”?
Qualitative research can result in improved social
scientific understanding, in trivial descriptions of things
nobody needs to know, or even in meaningless gibberish.
Which of these outcomes you get depends on two things:
the quality of work you do and your ability to explain it.
This chapter is about the second part. It is designed to help
researchers to offer up their work for inspection by others
in an understandable and meaningful fashion—to tell the
world what you have found and why it matters. But writing about research involves far more than just posting your
data somewhere. The goal of this chapter is to enable you
to write up the research so that it can be disseminated in
an understandable form to appropriate audiences. Before
actually getting to the mechanics of writing up research
papers, I believe it is important to write a few lines on the
perils of poor writing.

12.6 Recognize the importance of making the

research writing interesting.
12.7 Examine the relevance of multiple drafts of

the research writing.
12.8 List the common mistakes made

by students while writing research
papers.
12.9 Summarize the points that need to be

highlighted while writing about
research.

Even the best research can be rendered useless by poor
communication. It is hard enough for nonresearchers to
understand the implications of our work when it’s clearly
presented, as I have stressed already in earlier chapters.
With less than clear reporting, misunderstandings are
pretty much guaranteed.
For example, suppose your work showed that elder
retirees who participate in social activities with people
they like have greater health outcomes. (I don’t know if
that’s true, but it seems likely.) And suppose that you did
your research in conjunction with senior centers, distinguishing between those seniors who regularly participated
in activities and those who didn’t. If you merely report
the outcomes, that active members of senior centers were
doing better, people will think that health depends on
senior centers, missing the real point that health depends
on social life. Reporting the “what” of a study is trivial.
The real work is in demonstrating the “why.”
A further difficulty we face as research writers is that
people may read our work with more of a defensive eye
than a merely critical one. We can’t assume that our conclusions speak for themselves. We have to make a strong

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case. And we have to remember as we do so that most
people are not in the habit of analyzing data. Until we are
trained, people are actually pretty bad at drawing logical
conclusions from subtle patterns hidden within masses of
information.
On the other hand, one thing that people are surprisingly good at is justifying our own beliefs. We might like
to imagine that we look at the evidence and then draw
conclusions. Yet, often it seems that we do the opposite:
attach ourselves to a conclusion and then search for evidence to justify it. Was a novel that you recently read dense
and hard to follow? That was probably because the author
ignored conventional structure and messed around with
chronology. Was a different book brilliant and captivating?
That’s probably because the author ignored conventional
structure and chronology. Either way doesn’t matter, as
long as I can use the observed fact to support my conclusion. That’s how justification works. In the case of research,
as I find with my students, people are happy to trust the
methodologies and analyses of work with which they
agree, but are highly critical and suspicious of anything
that draws a challenging conclusion. If they don’t like the
results, then there must have been something wrong with
the sampling.
As researchers, our first challenge is to get away from
that kind of thinking. That can be difficult. Our second
challenge is to present our evidence in such a clear and
compelling fashion that we can overcome other people’s
tendency to only see in it what they want to see. That is
much harder. And third, we need to be aware of and more
or less follow the rules and conventions of scientific writing. We’ll start this chapter with some rules. The first and
most important of which is to clearly distinguish between
other people’s work and our own original contributions
to the topic. Failure to do so constitutes plagiarism, and it
thoroughly invalidates whatever else we might be trying
to communicate.

12.1: Plagiarism: What It Is,
Why It’s Bad, and How to
Avoid It
12.1 Evaluate the evils of plagiarism
Ironically, depending upon the source, you are likely to
find a range of meanings and definitions for the term
plagiarism. Regardless of these variations, at their root
these definitions share the notion that plagiarism involves
passing off the ideas and words of others as your own
without clearly acknowledging the actual source of those
ideas and words. Importantly, in academe as in the world

of the social sciences, journalism, the arts, the natural sciences, and virtually everywhere else, plagiarism is considered very bad regardless of whether it is done intentionally or unintentionally.
The label of plagiarism can describe any of the following actions:
• Turning in someone else’s written work as your
own (regardless of whether you have their permission to do so)
• Purchasing a written work from a professional paper
mill, your sorority or fraternity, the smart kid in class, or
any other source, and passing it off as your own work
• Copying sentences, paragraphs, or whole pages from
a textbook, Web site, or other written source without
indicating the actual source of this material
• Copying sentences, paragraphs, or whole pages from
a textbook, Web site, or other written source without
including proper quotation marks, page references,
or indentation (in the case of longer excerpts)—even
when proper citation of the actual source is offered
• Paraphrasing sentences, paragraphs, or whole pages but
failing to provide proper citation of the original source
• False paraphrasing (changing one or two words) in
sentences, paragraphs, or whole pages and failing to
provide proper citation of the original source

12.1.1: Why Plagiarism Occurs
It is likely that much of the plagiarism that occurs in colleges
and universities, and perhaps even among some professional
researchers, is what we classify as innocent or just stupid plagiarism; still, some is intentional and undertaken for a variety
of reasons. Some of the more common intentional reasons
for plagiarism include the following: “I was running out of
time, and the source said exactly what I wanted to say.”; “The
source said it so much better than I possibly could have.”; “It
was a stupid assignment, and I have more important things
to do with my time.”; “Everybody else was doing it.”
From time to time we also hear about professional
researchers, writers, or journalists who are also found to
have plagiarized other works. Among the most common
explanations given by these authors is that they were
writing from their notes, not the original sources, and
could not clearly distinguish between the words they
had come up with on their own while writing these notes
and the phrases they had simply copied over more or less
unchanged. This sort of plagiarism is understandable, but
just as stupid. Surely, after a writer has struggled once or
twice with the inconvenience of having to return to the
original source just to find the one sentence they wanted to
quote, you would hope they would have developed more
careful note-taking practices.

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Innocent or plain stupid plagiarism involves errors in
citation because the writers simply do not understand that
their actions constitute plagiarism. Either way, authorities
are typically no less sympathetic to stupid plagiaristic mistakes than they are to intentional ones. However, stupid
mistakes are easier to correct because once you learn the
errors of your ways, you can consciously avoid making
stupid mistakes of plagiarism.

12.1.2: How to Avoid Plagiarism
“So now that you know how it’s done, don’t do it!”1
Avoiding the first two items in the previous list seems
like a no-brainer. Obviously, if you go out and borrow
or buy someone else’s work, you have intentionally plagiarized these works, and there is no lenience for you.
These  are clear-cut examples of academic fraud. Some
people get away with it, but you should understand
that the action of intentional plagiarism is seldom taken
lightly, and in some schools, it can result in suspension
or expulsion. In the real world, getting caught in such an
act could result in the loss of a job or career, or at the very
least the loss of trust in your work, probably forever.
Let us therefore concern ourselves with the remaining
four items on the list, which do frequently occur among
students and other writers as stupid mistakes. The first
of these four items states: Copying sentences, paragraphs,
or whole pages from a . . . written source without indicating the
actual source of this material. In truth, this one walks a thin
line between a stupid mistake and an intentional one and
may from time to time fall into either of these camps.
However, in our combined 45 years of teaching in colleges
and universities, we have heard some very sincere students
claim they were unaware that lifting a few sentences or a
paragraph here and there and dropping them into their
own writing was plagiarism. Some of the blame for this
rests with certain elementary school teachers who insist
that their students look up the definition of words and
write out the full definition without citing the dictionary
as the source, or who encourage students to write topical
papers using an encyclopedia as a source. Students who
dutifully copy and paste the passages verbatim receive
an A for their efforts but, again, do not bother to cite their
source. Those teachers may have been trying to teach you
useful facts, but they did not help you learn to write.
Regardless of why many students believe this sort of
plagiarism is acceptable, it simply is not. It is plagiarism—
but with a simple fix. Never use someone else’s written
work without giving credit to that original author or
authors. Use it; but credit it. This brings us to the next item
on our list: Copying sentences, paragraphs, or whole pages from
a . . . source without including proper quotation marks, page references, or indentation—even when proper citation of the actual
source is offered.

Writing Research: Finding Meaning in Data 203

The usual rule of thumb is that when a quoted section
is five lines or less, you encapsulate it between quotation
marks (“quoted passage”). Following this quoted section,
you cite, in text, the name of the author, the date of the
publication, and the page reference where the original
work appears. If you are quoting more than five lines
of text, you should indent the passage on both sides—
but without quotation marks; it’s one or the other, not
both—either indent or use quotation marks. Following
the indented passage (typically on the next line and right
justified), the citation is enclosed in brackets ([citation
material]). Again, this citation should include the name of
the author or authors, the date of the publication, and the
page reference where the original passage appears. Since
the material you are referencing includes a specific set of
words exactly as they had appeared on some other page,
your citation has to include the page number.
The next item on our list is, Paraphrasing . . . but failing
to provide proper citation of the original source. Apparently,
many students believe that if they steal someone’s ideas,
but do not use every word in the same order as the
original author or authors set the material down, it is
not plagiarism; this is a very wrong assessment. This
one, however, is at least a bit more understandable as a
simple mistake. The fact of the matter is, if you take
another author’s idea(s), you need to reference that
author. In fact, in research citing someone else properly
is more about giving them credit for their ideas than for
their particular choice of words. This is often done with
what are hopefully familiar phrases, such as, “According
to Jo Jones (2006) . . . ” or “In a similar fashion, Marshal
and Cates (2006) found . . . ” The material following these
sorts of statements can be heavily paraphrased, almost
unidentifiable with the original, but if the main points
have actually been lifted from the original version, it
is proper to cite these original authors. It is also a solid
way to document your writing. However, if the ideas are
developed throughout portions of your source, rather
than in one particular paragraph, then there is no need
for a page reference in the citation. You are citing the
body of work, not a statement within it.
Here it is worth noting the relationship between credit
and credibility. If you wish to take credit for ideas that are
not your own, you obviously risk losing credibility if you
are found out. The reverse is also true. When you give
credit to others for the work that you are using, you gain
credibility. It shows that you are both honest and well read.
Researchers are supposed to be familiar with the work of
others. Building your work on a solid foundation of past
research is more respectable than trying to build your
whole project out of nothing. As well, it saves you from
having to justify some of your claims, since others have
already done that. This is particularly important when
what you are saying, using the other author or author(s)’