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Do you think you're middle class?
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If you're American, there's a pretty good chance that you do.
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In a survey conducted by the Pew Research Center in 2015, 87% of those surveyed identified themselves as middle class.
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That's a pretty big middle.
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But your intuition about what the middle class is – like who it includes, and what constitutes a middle class lifestyle – probably isn't the full picture.
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And a lot of questions that sociologists try to answer are questions just like this – questions that you think you know the answer to already.
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Many a person has played the armchair sociologist at some point in their lives –
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spouting off about how they think “Society Really Works” because of their own experience.
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Or the experience of their friend's brother's roommate.
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We all do it.
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But having personal opinions about the world doesn't make you a sociologist.
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Sorry.
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This is where sociological research comes in:
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It helps us understand society's patterns, even when they go against our intuitions.
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Rather than using our gut to answer questions, we use a research method, a systematic plan for gathering and analyzing observations about the world.
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This is where we're gonna learn how to do sociology!
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[Theme Music]
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First things first: Research starts with a question.
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And the key to deciding on a question is defining the concepts that you're studying, and making sure that both you and your audience agree on what those concepts mean.
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It's like that thing with The Dress.
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Some people thought it looked black and blue, and other people thought it looked white and gold.
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It turns out that some things that seem totally objective just aren't.
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And this becomes infinitely more complicated when you replace the concepts of blue or gold with concepts like the economy, poverty, parenting, education, or love.
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So, what if the way I am defining poverty isn't how you're imagining poverty?
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What if we're all seeing different levels of well-being as being “poor,” but we refer to them all as “poverty”?
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That won't work.
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So you have to define your concepts, which becomes even more important when you get to the next part of the research process:
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Stating a hypothesis – a statement of a possible relationship between two variables.
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A variable is just something that can take on many different values – it varies.
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Hence, the name!
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So before you can assign a value to a variable, you have to operationalize it.
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That is, you have to define the exact variable you're going to measure, and exactly how you will measure it.
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For example, you can operationalize a variable that you want to use to understand relationships, by defining it as “reported marital status.”
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Only then can you assign each person in your sample a number corresponding to their relationship status.
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Like 0 if they're married, 1 if they're divorced, 2 if they've never been married, etc., etc., until every person is labelled.
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And what value a variable takes on is called its measurement.
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You can measure someone's height, you can measure someone's income, and you can measure someone's relationship status.
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It doesn't matter how many categories your variable has: 0, 1, 2, 3, 4 whatever.
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What's important is that the way you define your categories is both reliable and valid.
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Suppose you decide to use Facebook relationship status as your measure of relationship status among your subjects.
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For your measurement to be reliable, you have to be consistent in how you measure the variable.
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So, here's what not to do:
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Say you have two categories for relationship status: Single or Not Single.
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Two different sociologists are going through the data, assigning values based on Facebook status.
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One decides that people who say “It's Complicated” get the label “Not Single,”
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while the other decides that these people should be called “Single.”
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That's not consistent.
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Every person with the same characteristics – in this case, the same relationship status – needs to be assigned the same value.
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And for your measurement to be valid, it has to actually measure something that directly reflects the concept that you're trying to study.
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Facebook relationship status may be a useful measure of whether someone's single or not,
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but it's not a valid measure of, say, their political views.
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Once you know how you want to measure your variables, your hypothesis will be an educated guess about how they're related – often using an if-then statement.
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Here's an example of a hypothesis, based on what I was talking about earlier:
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If someone lives in a city, then they are less likely to refer themselves as middle class.
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In this case, geographic location is what we call the independent variable;
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it's the variable that we think is affecting the change in how people describe themselves.
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But you can also have variables that you believe are affected by changes in your independent variable; these are your dependent variables.
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Your hypothesis is that they change when the independent variable changes.
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But you have to be careful because correlation does not always equal causation.
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Correlation is what happens when two variables move together.
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It can be easy to misinterpret a correlation to conclude that one thing causes the other, when it really doesn't.
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For example, murder rates tend to be high when ice cream sales are high.
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But it's ridiculous to think that more ice cream causes more violence – or vice versa.
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What's missing is a third variable: heat.
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More people commit crimes during hot months, and more people buy ice cream then too.
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OK! Once you have your hypothesis, and you know what types of variables you need to test it, you're at your next step:
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Collecting your data.
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There are four main ways that sociologists collect data:
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Experiments, Surveys, Participant Observation, and Existing Resources.
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Experiments in sociology work much as they do in the natural sciences, just with humans as subjects instead of mice or atoms of beryllium.
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Let's go to the Thought Bubble to see a real life example of how a sociology experiment works!
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In the 1990s, the US Department of Housing and Urban Development conducted an experiment known as The Moving to Opportunity study.
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In it, social scientists randomly assigned low-income families into a control group or one of two experimental groups.
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One group was a control group, which means nothing was changed in their environments.
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This allowed for a comparison between them and the experimental groups.
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They received a housing voucher that allowed them to move to cheaper housing –
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often in a better neighborhood than they were currently in – if they wanted to.
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Then, a whole bunch of data was collected – and is still being collected –
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on many different short and long term outcomes, including earnings, children's educations, and health outcomes.
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These outcomes are the experiment's dependent variables.
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So we have one independent variable – receiving the voucher or not –
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and a bunch of possible dependent variables, like earnings, education, and health outcomes.
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In an experiment, if the change you predicted occurs for the experimental group but not for the control group, then your experiment supports your hypothesis.
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And in the HUD experiment, sociologists compared how the measures of well-being changed for the control group, compared to those for the experimental group.
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One of the findings:
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those who received a voucher had better mental health outcomes – such as lower rates of depression – than those who didn't.
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The data from Moving to Opportunity continues to be studied to this day and is a key source of research into how neighborhoods affect families' well-being.
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Thanks Thought Bubble!
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The second method that researchers use is a survey, where people respond to a set of prepared questions.
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Typically, researchers are interested in the responses of a specific group of people – what we call the population of interest.
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Women aged 18 to 35. Veterans. Left-handed people. Youtubers.
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Whoever your research question is about, this is your population.
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But it's unlikely you'll be able to survey the WHOLE population.
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Even government-run surveys, like the Census, don't reach everyone.
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So instead, you survey a sample – a smaller group that's representative of the population.
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And a survey can take many forms.
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There can be open-ended questions, or Yes or No questions.
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The questions can appear in many different orders, or be phrased in different ways.
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So, sociologists have to think carefully about these things –
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and about whether the structure of their survey might bias the respondents' answers.
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Now, some research takes place in a much less controlled environment.
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Tons of sociology research is done “in the field,” through our third method, participant observation.
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Participant observation is when researchers observe people by joining them in their daily routines.
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The result of this type of research is called an ethnography.
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Researchers try to integrate themselves into a community, hanging out with their subjects, working with them, and so on.
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They're both observers and participants.
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This type of data-collection tends to be exploratory and descriptive.
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You're not trying to prove a specific hypothesis.
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Instead you're trying to understand the lifestyle of your subject.
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Some say that this type of research is too subjective,
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but a major benefit of doing fieldwork is that it lets you to gain insights into people's behavior, in the real world, in a way that experiments won't.
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Take, for example, sociologist Alice Goffman's field work in Philadelphia.
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She spent six years living in a low-income, crime-ridden neighborhood in West Philadelphia
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where she befriended and lived with two young African American men
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and documented the ways the criminal justice system intersected and disrupted the lives of them, their families, and other members of the neighborhood.
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The documentation of lived experience like that can provide insights that you just couldn't get simply from looking at statistics.
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Now, there's one thing that's important note about these three types of research:
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When researchers interact with their subjects, whether it's through an experiment, an interview,
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or participant observation, they have to take seriously the ethics of their research.
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Sociologists are answerable to an Institutional Review Board,
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which ensures that all researchers take the privacy and well-being of their subjects into consideration when they design their research methods.
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For example, informed consent of the subject is a must.
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This means that your subjects must know you're observing them, and must be made aware of any risks they take by being part of your study.
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Not all research methods require you to interact with subjects though, or even collect your own data.
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Many sociologists analyze existing sources of data, collected by others.
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The most common of these sources is government agencies, which collect statistics on income, health, education, employment, marriage, fertility –
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I could keep going.
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The point is, these data sets are much larger and cover more years than an individual researcher could collect on their own.
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Plus, it saves time and money for the researcher.
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Once you've collected your data using one of these methods, the final step is turning that data into information that helps answer your question of interest.
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You can do this in two ways: through inductive or deductive logical thought.
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Inductive logical thought takes your observations and uses them to build a theory.
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You start with data and then use them to form an idea about how the world works.
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For example, seeing the results of the Moving to Opportunity study might prompt a researcher to theorize that the neighborhood a person lives in is a key factor in their mental health.
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Deductive logical thought, meanwhile, uses an existing theory to inform the hypothesis you test.
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In this case, you start with a theory and you collect data that allows you to test the theory.
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Theories about the relationship between where you live and your child's well-being is part of what prompted the government to not just collect data on the heads of household in the HUD study, but also on their children.
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And these two types of reasoning are not mutually exclusive;
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within one study, a researcher will use both to develop theories about the social world.
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And guess what? You're done!
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Today we discussed the research method:
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form a question and a hypothesis, collect data, and analyze that data to contribute to your theories about society.
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Crash Course Sociology is filmed in the Dr. Cheryl C. Kinney Crash Course Studio in Missoula, MT, and it's made with the help of all these nice people.
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Our animation team is Thought Cafe and Crash Course is made with Adobe Creative Cloud.
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If you'd like to keep Crash Course free for everyone, forever, you can support the series at Patreon, a crowdfunding platform that allows you to support the content you love.
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Speaking of Patreon, we'd like to thank all of our patrons in general, and we'd like to specifically thank our Headmaster of Learning David Cichowski.
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Thank you for your support.