-: Hello there, and welcome to Part 1
of the video lectures on Qualitative Research.
So, qualitative is a major,
very common kind of research
that many social scientists use
and we will use in our class project.
So here's an overview.
We're gonna speak a little bit about it,
see how it fits into mixed methods,
the balance between being an insider and an outsider.
One way of evaluating the data
and coming up with hypotheses and theories,
which is called grounded theory,
but we're gonna talk about
how to structure an interview guide
and the value of semi-structured interviews,
which are probably the most common type of interviews.
And then we're gonna talk about
what are the strengths and weaknesses
of qualitative research overall.
And think about the trade-offs of valid and reliable,
which is a major theme of this whole class.
Very often, qualitative is used as the second step
in a mixed method to study,
much like the one that our class is doing this semester.
So you start with a lit review,
so sort of do your homework, see what's already known,
what's already been done,
what can we build on,
and then go to qualitative,
where it really sort of helps you get your mind around
what are the big issues out there?
Well, what are the big themes and ideas?
And this is often done through the use of interviews,
where you can really begin to understand
what do research subjects
think, and feel, and believe, and do about this,
so it's a good way of really getting a deep understanding
of their experience of the topic that you are studying.
It also is a good way
to begin to form theories or hypotheses.
And then last,
we can jump to quantitative,
where we take those themes and those ideas,
those major issues from the qualitative part,
and sort of test them out
on a much larger sample, we can test hypotheses,
and it's also a way to count
how many folks say these things,
and then correlate answers.
So sort of how is there a relationship
between how they answered one question to another question,
or how they answered one question,
to maybe demographic variables
like your age, or gender, or race, or things like that?
So in many ways,
we all do qualitative research every day.
We observe things, we talk to people,
we use that to try to understand things
that we don't understand that well.
And for the most part,
qualitative is used to understand these things like
attitudes, behaviors, beliefs,
opinions, awareness, things like that,
and it can give you great depth of understanding,
really sort of do a deep dive into your research subjects,
understanding of this thing,
what are their attitudes, behaviors, et cetera.
Since you are in the middle of the action,
since like you are sort of being observed as a researcher,
while you're collecting these data,
some sort of special care and consideration must be made
that you don't want your behavior
to alter the responses that you want,
your job as a qualitative researcher
is to draw out your subject's own account,
in their own words, in their own thoughts,
and not sort of following what you want them to say,
or say something because they know they're being observed.
Two ways of thinking about this
are the emic and the etic perspectives.
And that is sort of how are you seeing the subjects
and what they are doing.
So the first one is the emic view,
where you really try to see it from their point of view,
you really immerse yourself in that experience
or that subject,
and really like try to understand
in a very deep way,
what is going on in this specific context.
And since you're allowing your subjects
to express things in their own words,
to the best of your ability,
it's very valid,
it's very deeply true what they are saying
for that individual.
On the other hand,
there is etic perspective
where you sort of enter more as an outsider,
much more detached,
and thinking about will what these folks are saying,
hold in other contexts, in other places,
in other times, and with other subjects,
and this can tend to be more reliable
that you're getting more of the same types of answers.
Note that it is impossible in my view,
to be completely objective.
We all bring our biases,
and these biases play out in numerous ways
in how we choose the research, how we choose what to ask,
how we interpret data,
so the most important thing
is to be aware of one's own biases.
Like we talked about a confirmation bias.
"Why am I seeing it this way?"
And maybe trying to see how others would see it,
folks that aren't you,
and what is the lenses that you bring
that may make you see this,
you know, sort of notice some things
or think some responses
are more important or less important.
One interesting way to think about it is
how involved should you be with the subjects?
And this is again, sort of this emic and etic perspectives.
We'll talk a little bit more about this in class,
but I think back to my experience
as a Peace Corps volunteer in Senegal, in the 1990s,
I lived in a very, very rural farming village
and there was no sort of,
not a lot of formal education,
and there was no school there,
and thinking about what they thought was true
and what they thought was not true.
And two examples that really stood out to me,
is they believed that there were these sort of,
these amulets that you could wear on your arm,
and they sort of have a charm of like, nobody can stab you,
like if you wear this,
that a knife won't go into your flesh.
And on the other hand,
I remember talking with my family one night
and there was a nice big full Moon,
and I said, "Oh, well, there have been humans
who have walked on the Moon."
And they were like, "No, there's not."
And they thought I was completely insane,
and it's because of the culture and the context
in which they grew up,
many believed that these amulets
could protect you from a knife wound,
but that it's completely absurd
that any human has ever walked on the Moon.
So your job is not to judge.
We as social scientists,
our job is to record and understand what they think.
We might think that what they are saying and thinking
is completely absurd,
but it's not our job to sort of call them out,
and tell 'em they're dumb and they're wrong,
our job is to understand what do they believe, and feel,
and do, and why,
like given the context
in which they are operating,
why are they saying these things?
And again, to have a really deep understanding
of what their perspective on the matter,
and that's what a good qualitative researcher does.
So two main ways that we can analyze data,
and we've talked about this before,
the deduction and the induction.
So in deduction,
you start with a theory or a hypothesis
and you say, "Well, if this is true,
then this next thing is true,
and if that is true, then this other thing is true."
And we use our data to see,
does this theory hold,
do the data support this preexisting hypothesis or theory?
That is deduction.
On the other hand,
induction is you start with the data,
you try to sort of forget about any preconceived notion,
any theory, any hypothesis,
and you let the data form the hypothesis,
and this is so-called, this is called grounded theory.
And I don't love this term,
I don't think it's very intuitive or descriptive,
but what it means is,
that you are developing theories based on the data.
It's this use of induction,
of thinking about what are the data saying,
and then forming a hypothesis based on that.
And yeah, that's the difference
between deduction and induction.
So, again, it's very common
that qualitative researchers use this
so-called grounded theory,
where you get your data, you get observations,
you get the results of interviews say,
and you compare them,
and you see sort of what are the themes that you're seeing?
You try to get interviews or data
from multiple from viewpoints, from multiple subjects,
and sort of step back and think,
"What are the patterns here?
Why are they saying what they are saying?
What would we hypothesize that would come from that?"
And therefore, and I think that's why they call it this,
that the theory that you develop from your data
is then grounded in the data,
rather than sort of preexisting,
before your study begins.
So that's the end of Part 1,
and please watch Part 2.