Everyday Sociology Blog

Institutional Review Boards: Why Do We Need Them?

By Janis Prince Inniss

So you’ve been reading about various sociological theories and ideas. And about some sociological studies. But have you given any thought to some of the ethical issues sociologists might face as we conduct research? Have you learned anything about the issues that we face in dealing with human subjects?

Much of the research that I have conducted has involved interviews and other qualitative methods. And I have found that people love to talk when they’re being listened to. Think about it, how many people in your life really listen to you? And pay you to tell your story?

This means that sometimes I learn intimate details about people’s lives. One such example is a study I worked on to identify strategies to improve the mental health care of children in the child welfare system. Our goal with this research project was to identify individual, family, and systems-level factors and circumstances that impact the psychotropic medications and services that children in the child welfare system receive. To conduct the study we used a mixed-methods approach that included analyses of some Medicaid databases and in-depth case studies of children in the child welfare system who received mental health care.

Of course, the Medicaid database had lots of billing information, which is not the kind of information any of us would want displayed publicly if it were ours. The database has the type of services children received, their mental health diagnosis, date of birth, dates and length of service, sex, and race among other variables. Because I was working on the qualitative aspect of the study, I saw none of this raw data; someone else on the research team who was conducting the quantitative analyses and whose computer met extensive university-set security standards was allowed access to the data and would give the results to the rest of the research team.

The case studies included a small sample of children, reviews of their child welfare charts, and interviews with the children and their families, child welfare workers, and other service providers. As we reviewed the charts, we learned very personal details about these children and their families. Because the focus of the study was children in the child welfare system, all of these children had been removed from their homes because of allegations of neglect and/or abuse.

Their charts (oftentimes boxes and boxes of documents pertain to one child because of the length of time they remain in the system) chronicle police reports, child protection investigations, assessments, treatment plans, and home visits by child welfare workers. And of course, during the course of the interviews we learned more about these families –and given our focus on mental health care, we learned about psychotropic medications—exactly what was being taken, for how long, with what results, as well as other mental health care.

What if in this post, I told you about one of the youth in this study? What if I decided to give you a child’s name and told you about the abuse that child suffered and the remedies taken? What if I did that to help you understand how to treat the same condition? Would that be ethical?

Have you heard of Institutional Review Boards (IRBs)? Universities and other research institutions have them to ensure that research is conducted in an ethnical manner. There have been some atrocities committed in the name of research. The syphilis study at Tuskegee Institute began in 1932 and allowed African American men to die from syphilis more than 20 years after researchers knew that there was a cure for this disease; these study participants had been mislead about the true nature of the study. Perhaps you have learned about sociologist Laud Humphreys’ book Tearoom Trade: Impersonal Sex in Public Places. Humphreys 1960s ethnographic research on anonymous sex acts between men in public bathrooms is often noted as unethical because his “subjects” had no idea that he was conducting research as he acted as a lookout for them.

Given that these men were in public spaces, would you argue that Humphreys’ description of their behavior was ethnical? What about the fact that later, in disguise, he went to their homes? How did he know where they lived? He noted license numbers of some of their cars and with the aid of an accomplice (a friend who worked at the Department of Motor Vehicles) learned about their family lives.

Today, research participants are protected by IRBs. Researchers must undergo IRB training and take refresher courses annually. And before we can conduct any research, we must apply to our university IRB. The application includes a description of the study and explains in detail what we want to do with participants. The IRB has to have full knowledge of each proposed study: how many participants will there be, of what ages, how will they be contacted, for how much time will they be involvement, will deception be used, how much they would be paid. Risks and benefits of participant involvement must be detailed and if special populations are involved the stakes are even higher. (Can you think of why prisoners, children, and pregnant women might be considered special populations and subject to additional oversight by review boards?)

With all of this information, the IRB decides whether a study can be implemented as proposed. As you read about sociological studies, think about the ethical considerations that researchers must consider and take to IRBs.

Thinking Like a Sociologist: Deconstructing Polls

By Karen Sternheimer

A recent episode of The Daily Show satirized both left wing and right wing cable news shows for using questionable poll data in their broadcasts. Regardless of your political orientation, this clip is a great introduction to some of the core concepts sociologists use in research methods and statistics: survey construction, sampling, and margin of error. Think about these issues as you watch the video below.

 

The Daily Show With Jon Stewart	Mon - Thurs 11p / 10c
Poll Bearers
www.thedailyshow.com
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1. Survey construction

Did you notice the wording of the questions in the polls? Good surveys should not suggest how respondents should answer them, but some of the polls included wording that could certainly bias responses. Note how some of the questions in this clip tend to encourage one response or another, particularly the questions about taxes. Most people would respond negatively to a general rise in taxes. But there are a wide variety of taxes (sales and income taxes to name a few), and rates vary based on a variety of factors (such as location, income level, and family size). By contrast, the tax that excludes most potential respondents (raising taxes only on a small percentage of Americans) is more likely to generate favorable results.

A good survey question is worded as neutrally as possible and is specific so that respondents are very clear about the meaning of their response. A good question about taxes would be clear on what specific tax rate would change, by how much, and for whom. The word “tax” is so loaded that another word might even be used in its place, such as fee or levy.

2. Sampling

Let’s say we’ve written good survey questions. Our next step is to administer our survey to an appropriate sample.

What is a good sample? That depends on which group we are trying to learn about. If we want to get the opinion of sociology majors from across the country, then we certainly wouldn’t want to poll people who pass through the center of a couple campuses. For one, we would get a lot of non-sociology majors, and secondly, a small number of campuses would not adequately measure the nation’s sociology majors.

Many polls reported on the news imply that they represent views of Americans. That might seem like a daunting task, but it is possible to get a sense of public opinion this way.

You might be thinking that with a population around 300 million, it is nearly impossible to sample a thousand or so people and claim to know what Americans are thinking. To do so, pollsters need to construct a probability sample, which means that every American should have an equal opportunity to be chosen at random to be part of the sample.

Hypothetically, you can think of a random sample as similar to putting everyone in the population’s name in a huge hat which is shaken so anyone’s name can potentially be pulled.

But there isn’t a hat that big, nor is it practical for someone to write everyone’s name down on a slip of paper. Pollsters often rely on measures which are admittedly imperfect. One of the most common is random digit dialing, where a computer calls random phone numbers in hopes of getting respondents.

Have you ever gotten one of these calls? If you’re like me, you get a lot of calls that interrupt your busy day or evening, and caller id allows you to ignore the numbers you don’t recognize. This has created sampling challenges: if there are consistent patterns in who is more or less likely to participate then your survey results might be skewed.

So there are no perfect samples, but there are some really imperfect samples, like the ones in the Daily Show clip above. Some internet and television polls make no attempt to create a probability sample, so their responses are limited to the demographic already watching or logging onto their site.

There are also other factors which might make someone more or less likely to participate. For instance, if a television show asks you to text your response, viewers might be more likely to participate if their cell phone plan has generous texting privileges. Beyond that, some people are more motivated to respond than others. So these polls might be fun, but they are not very useful gauges of public opinion. That’s what “results not scientific” means if they flash it on the screen. But often shows do not.

3. Margin of Error

Even the polls with well-written questions and the best possible samples are approximations of public opinion, rather than a perfect reflection of what people really think about an issue. While we might not ever be 100% certain that a probability sample reflects the true opinion of a population, thanks to probability theory, we can be 95% confident that the actual opinion lies within a certain range.

Here’s an example. Gallup regularly conducts job approval surveys of political leaders. In an August 2009 survey, they found that 31% of Americans approve of the job Congress is doing. As you can see from the graph below, the approval rating appears to have fallen from previous months.

But every poll has a margin of error, since surveys are approximations rather than perfect reflections of a population’s beliefs. The margin of error is a measure that takes into account the sample size and the amount of variation of responses. In this case, the margin of error is ±4, meaning that we can be 95% certain that between 27% and 35% of Americans approve of the job that Congress is doing.

Now, if I were a member of Congress I wouldn’t be too excited about this range of scores, but because it is within the range of scores from earlier months we probably cannot say with confidence that Americans’ approval of Congress is declining. But no matter how you look at it, it’s pretty low.

You might notice that news shows reporting polls rarely discuss the meaning of the margin of error, if they mention it at all. Keeping this important measure in mind, you can use your sociological imagination to think critically about the next poll you hear about in the news.

Measuring Abortion Beliefs

 By Sally Raskoff

Headlines across the country recently noted that more Americans now consider themselves “pro-life” than ”pro-choice”. In the last month many polls have focused on Americans’ views on abortion, yet the Gallup poll released on May 15, 2009, got the most attention. President Obama was just about to give the commencement address at Notre Dame where a controversy had erupted; critics complained that a pro-choice politician should not have been granted an honorary degree at a Catholic institution.

The Gallup poll graphs below show the new divergence of opinion. Looking at the pattern over time, it is clear that opinions of pro-choice versus pro-life have been changing, although the trend between 1998 and 2008 is not remarkable in its variety. The change that the news signaled is that last switch in the apparent prevalence of pro-life opinions.

Sociologically, let’s look at this issue more closely. Opinions on abortion, its availability, one’s identification with the issue, and its legality are sensitive and controversial because they involve religious, political, and cultural values and very personal, often difficult situations.

Polls show a variety of support depending on the wording of the questions. Look at the poll results from the last month:

Gallup Poll. May 7-10, 2009. N=1,015 adults nationwide. Margin of Error ± 3.

"Do you think abortions should be legal under any circumstances, legal only under certain circumstances, or illegal in all circumstances?"

Legal Under any Circumstance	Legal only under Certain Circumstances	Illegal in all Circumstances	Unsure
22%	53%	23%	2%

Quinnipiac University Poll. April 21-27, 2009. N=2,041 registered voters nationwide. Margin of Error ± 2.2.

"Do you think abortion should be legal in all cases, legal in most cases, illegal in most cases or illegal in all cases?"

Always Legal	Usually Legal	Usually Illegal	Always Illegal	Unsure
15%	37%	27%	14%	7%

The wording of the questions are only slightly different (circumstances versus cases) yet the results are quite different. Note that a only a minority hold that abortions should always be illegal. “Identity” issues also frame the debate. As the following polls show, when asked whether they consider themselves pro-life or pro-choice, respondents offered slightly different results.

Here’s something sociologists need to consider: We don’t know whether these differences are statistically significant. This rather important issue is not addressed in news reports on the Gallup Poll. It may be that we have equal percents of people in each category and the oscillations over time are not statistically significant. At the very least, the reported margin of error (MoE) shows that the percent of people in these groups may not be so different after all.

FOX News/Opinion Dynamics Poll. May 12-13, 2009. N=900 registered voters nationwide. MoE ± 3.

“On the issue of abortion, would you say you are more pro-life or more pro-choice?”

Pro-life	Pro-Choice	Both/Mix	Unsure
49%	43%	6%	2%

Gallup Poll. May 7-10, 2009. N=1,015 adults nationwide. MoE ± 3.

"With respect to the abortion issue, would you consider yourself to be pro-choice or pro-life?"

Pro-choice	Pro-life	Mixed/Neither	Don't Know What Terms Mean	Unsure
42%	51%	2%	4%	1%

CNN/Opinion Research Corporation Poll. April 23-26, 2009. N=2,019 adults nationwide. MoE ± 2.

"With respect to the abortion issue, would you consider yourself to be pro-choice or pro-life?"

Pro-choice	Pro-life	Unsure about Terms	Mixed/Both/Neither	Unsure
49%	45%	1%	3%	1%

Another way to look at abortion opinions is to ask about people’s legal opinions as this poll does. The CNN poll below asked specifically about the Roe v. Wade decision. Even if more people might identify themselves as pro-life, there is still a preponderance of support for the Supreme Court decision.

CNN/Opinion Research Corporation Poll. May 14-17, 2009. N=1,010 adults nationwide. MoE ± 3.

"The 1973 Roe versus Wade decision established a woman's constitutional right to an abortion, at least in the first three months of pregnancy. Would you like to see the Supreme Court completely overturn its Roe versus Wade decision, or not?"

Yes, Overturn	No, Not Overturn	Unsure
30%	68%	1%

Here’s another piece of data to consider – the actual trends in abortions. Since the 1980s, the rates have leveled off thus abortion has not increased in use. The fact that it is has been decreasing and not increasing might lessen opinions about its availability.

To better understand how the pro-life and pro-choice opinions may be changing; take a look at these graphs from the Gallup poll and notice which lines are moving in which direction.

It seems pretty clear that more conservative, moderate, and Republican people are leaning more pro-life than they were in years past. How might we explain this? Republican leaders have stressed this issue in their attempt to solidify opposition to the Obama administration and the gains made by Democrats in the House and Senate.

From a sociological perspective, we can see that this issue is much more complex than a single headline. Before we can conclude that social change is happening, we need to examine the data available and whether our findings are statistically significant. What other methodological questions do you think we need to ask to better understand trends in public opinion?

How to Think Like a Sociologist

By Karen Sternheimer

Here’s a shortcut for those of you currently taking a sociology class (or will someday soon). If you can learn to think like a sociologist you can not only earn a higher grade but develop a much more nuanced view of the world around you. You can still be a student of sociology even if you never step foot in a sociology classroom, too.

Step #1: Never assume anything

Assumptions about the way life is might seem to be “common sense”, but if you rely only on this you are not thinking like a sociologist. Sure, even sociologists have our own assumptions, but we find out if they are verified by finding out what actual empirical evidence tells us. This means before we presume our assumptions are true, we test them  (or find results from other studies of the same phenomenon). When I first started graduate school, a professor reminded us that assumptions rely on a sample size of one, hardly sufficient to claim a consistent sociological pattern.

Step #2: Get ready to be wrong

Now that you recognize that your assumptions are just your opinions, you might be surprised to learn that your assumptions are sometimes off, or in some cases, completely wrong! In fact all scientists are supposed to presume we are wrong to begin with, which is the logic behind the concept of the null hypothesis in statistics. When doing statistical tests, we need to disprove the null hypothesis (that there is no relationship between the two variables we are testing) first before drawing any conclusions about our own hypotheses.

It may seem, for instance, that crime keeps getting worse and worse, but as I blogged about a few weeks ago, it’s actually declined a great deal in the last fifteen years. And although women victims are frequently portrayed in the news and in crime dramas, men are most likely to be victims of violence, and elderly people are among the least likely age group to be victimized.

Sociologists think beyond simply right and wrong—we also ask why. For instance, why do we tend to think crime is on the rise? That women are uniquely vulnerable? We ask questions about how misperceptions like these sometimes benefit particular groups, institutions, and the overall balance of power in society. We might consider what purpose “common sense” notions of crime serve for those who have a vested interest in the status quo.

Step #3: Ask even more questions

If at this point you fear we are reading too much into things, you are not thinking like a sociologist. Some tip-offs that you have strayed off the sociological path include responses like:

• “It’s just human nature”
• “It’s always been this way”
• “That’s just the way it is”

I confess that in my student days I occasionally used these well-worn but un-sociological answers myself. Sociologists respond to conclusions like these with more questions:

• “What makes us understand human interactions the way that we do?”
• “How, then, does social change happen”
• “Is this the way things should be?”

You might find yourself resisting these additional questions, as Sally Raskoff recently blogged about . This is completely normal, since it can feel unsettling to find out that many of the “answers” we thought we had about life were not as useful as we might have once thought.

Step #4: Make the everyday strange

Sociologists borrow some of our thinking strategies from anthropologists like Clifford Geertz, who encouraged what he called “thick description” of the cultures we observe. In order to do this, we have to be ready to think about everyday events and patterns critically. This can be very hard, particularly for people who are members of the cultures we study, because it is easy to take things for granted and not even notice them as sociological phenomena.

For some of us, this practice is not just intellectually stimulating, it’s also fun. For others, it may seem like a chore, especially if thinking critically implies that there is something wrong with what we are observing.

Take your favorite television show, for example. If you think like a sociologist, you might observe that the show presents a somewhat skewed impression of crime, or maybe only features whites, or women who are a size 0. If you’re not thinking like a sociologist, you might not even want to be aware of these aspects of your favorite show because you really like it and want to keep watching it.

Thinking like a sociologist, you might understand how this is an outcome of specific entertainment industry practices and want to learn more about how these decisions get made (as sociologists like William Bielby did). Sociologists can both understand something more deeply and still enjoy it.

If you’re not thinking like a sociologist, you might conclude that television just contains dramatic stories people want to watch, and thin women are just nicer to look at, so what’s the big deal? The big deal is everything from our daily lives contains sociological questions, and the answers to those questions help us understand our society in greater depth.

Step #5: Embrace life’s complexities

Life isn’t simple, and neither are sociological findings. Sometimes they may seem contradictory, or you might have personally observed specific situations that appear to challenge a sociological concept. Sociological theories, research, and analysis are not meant as one-size-fits-all proclamations about the way the world works all the time. We might find, for instance, that some forms of crime have declined in one city but not another; that not all explanations for trends in divorce rates make sense in all situations; or that the economic downturn can cause both higher rates of unemployment and savings. The world can be complicated, and so can sociological explanations.

Practice these five steps; challenge your own assumptions, ask questions instead of looking for simple answers, and you just might start thinking like a sociologist.

Age, Cohort, and Period Effects of Religion

By Bradley Wright

In sociological research, we often study the change of things over time. It’s reasonably easy to demonstrate how something changes over time, but it’s more difficult to explain why it changes because there are multiple causal processes that produce such change. In particular, three that are frequently described in demographic research are age, cohort, and period effects. I’ll illustrate each one using data about religious change over time.

An age effect is how people change as they get older. As people progress from childhood to adolescence to adulthood they go through various changes. Not only do their bodies change (as we start to lament once we hit middle age), but they change socially as well. For example, political beliefs can change with age; many people report being more liberal in their youth and more conservative in their older age. People tend to earn more money as they age too (at least until they hit retirement).

In terms of religion, it’s commonly observed the people become more religious as they age. To illustrate this, I examined data from the General Social Survey (GSS), a survey collected every two or three years from 1972 to the present. One of the questions asked if respondents identified with a formal religion, and, if so, which one. In the following figure, I chart how many of the respondents professed themselves to be Christians as a function of age. About 75% of the respondents in their twenties professed Christianity (the bar on the left), and this increased steadily until almost 90% of those in their seventies and eighties professed Christianity. This illustrates an age effect—adherence to Christianity increases with age.

Not only do people change with age, but they also change with when they were born. Different cohorts (or generations) act and believe differently than other generations.

Here’s an easy example: If you’re a college student, go find your parents’ high school yearbooks and get a laugh out of how they dressed. In the 1970s and 80s, boys wore their hair long, and girls had frizzy hair, and we all wore embarrassingly short shorts. If you want to see something really crazy, go back another generation and look at young people from the 1960s.

With religion, we might expect a similar effect. Maybe different generations experience religion differently, beyond how they age. To examine this, I used GSS data to look at the relationship between age and Christianity for three different birth cohorts—respondents born in the 1940s and the 1950s. The first graph replicates the graph above, levels of Christianity over age, for people born in the 1940s. The next for those in the 1950s. As you can see, the relationship between age and Christianity changes by cohort. The respondents who were born in the 1940s held steady in their profession of Christianity as they aged, but the later cohort actually declined somewhat.

In addition to age and cohort effects, there are also have history effects. Here society changes in some way that affects everyone. The classic example is the Great Depression of the 1930s. It affected people regardless of their age or their birth cohort. Various aspects of religion change with historical changes. Wars and other times of trouble might reinforce the strength of religious beliefs. The social turmoil of the 1960s led young people to question existing social institutions, including organized religion.

As a simple illustration of a historical effect, I took levels of professed Christianity by decade, for the 1970s, 80s, 90s, and the 2000s. As shown in the graph, a smaller percentage of the population is professing Christianity with each decade. (To be clear, since the population is growing, there are actually more

professed Christians in the country now than in the 1970s, they just constitute a smaller percentage.) This appears to be a historical effect—the times they are a changing.

If this weren’t confusing enough, age effects can change by both cohorts and periods. (In statistical terms, this is a called an interaction effect.) So, the relationship between age and Christianity now might be different than it was in the past. Who knows, maybe the relationship between age and cohort various by historical period.

The upshot of all of this is that it’s rather difficult to make sense of social changes over time, and this leads to a fair amount of confusion about what’s really going on in society. What seems to be an easy question, for example, changes in professed Christianity over time, is somewhat difficult to make sense of. In this post, I’ve only looked at one aspect of religion, but we could do similar analyses for other religions as well as other aspects of religion, such as belief in God, importance of religion, and attendance at religious services.

I suppose that this post serves as a warning about over-simplifying social trends. If nothing else, this difficulty will always give us sociologists something to do with our time.

Studying Subcultures using Participant Observation

By Becky Conway

Graduate student, Vanderbilt University

One of the joys of a being a sociologist is that we are never at a loss for material. People surround me every day, and they never cease to amaze me. I am forever entertained watching and learning about my fellow homo sapiens.

I recently met a group of people that utterly intrigued me. Wanting to know everything about them, and knowing virtually nothing, I didn’t know where to begin. I decided that the best way to understand them and generate questions would be to conduct participant observation. This way, I could experience their social world firsthand.

It all started about one year ago when I encountered a subculture known as furries. This phenomenon first surfaced around 1980, and many attend regional and national conventions where furs can meet other furs and attend sessions to help them improve their preferred art forms (written, visual or performing in fur suits). The largest convention in the world, Anthrocon, is held in Pittsburgh, Pennsylvania every July, and 3,390 people attended last year.

This March I attended a smaller convention as a participant observer. My foray into the field taught me how the process of gaining access and becoming a community member can aid the construction of research questions. The experience also taught me a few tips on how to implement the method successfully.

My first objective was to gain access to the community. Aside from registering for the “con,” I decided I would need my own “fursona,” or furry persona. What animal should I be? The answer, quite honestly, came faster than I expected (a white tiger, for those who are curious). My ability to quickly decide my own animal identity caused me to reflect on why I chose this animal. Did it come from my childhood experience of seeing a white tiger for the first time? Did I identify with certain aspects of this animal’s behavior? My interview with myself spurred my curiosity about other people’s identities and how they came to understand what animal they were.

My time at the convention allowed me to ask others about their own identity. Some chose an animal with characteristics that they idealized (such as strength, fearlessness, or gregariousness). Others chose to be something completely different; a male might pick a female animal, for example.

I also noticed that the group was largely comprised of white males. This observation led me to question why this was the case in a group that appears to be open to every gender and sexual classification. I also learned about different cliques that exist within the group and discovered who were the most well-known and respected members.

This information is important to have prior to constructing interview questions. If the respected members approve a study, other members are more likely to participate. And if I know that there are cliques in advance, I can stratify my sample, or look at groups separately to see if there are meaningful differences within these subgroups.

Aside from gaining a greater understanding of the group, I also learned some valuable lessons about implementing participant observation. Having never conducted such a study before, I was anxious about the process. I had the overwhelming fear that if I screwed up, I would not be able to conduct my study and my life as a researcher would be ruined. I sought the advice of a faculty mentor for help. Her words of wisdom were invaluable:

1. Become an information kleptomaniac. We can learn a lot from doing a content analysis, as Bradley Wright recently indicated in his post on sport and gender. Therefore, grab everything that is free and not nailed down. The information these items convey can become a valuable resource for understanding some of the general norms and ideas of a culture.
2. Become a photographer if it is feasible and does not violate anyone’s privacy. Taking pictures is an excellent way to bring your subjects and your experiences to life, especially to those outside of sociology as well as outside of academia. It also allows you to go back and see things that you may not have noticed in the moment.
3. Have a weak bladder. Okay, not really, but one way to achieve success in the field, especially the first time out, is to write down everything. This act needs to take place behind the scenes, such as in a bathroom stall, to avoid arousing suspicion among community members. Have paper and a pen that you can fit in a pocket or purse, and excuse yourself every 15-30 minutes to write down your observations and thoughts. Believable excuses are somewhat dependent on the context, so it helps to know the scene in which your observations will take place in advance and to have your excuses prepared. In my case, the convention took place in a hotel which afforded me the opportunity to “run up to my room for a minute” and “check to see if I left something in the car.”

These tips are just a few of the ways to have a successful first encounter as a participant observer. There are many sources that provide guidelines and other “tips” for all research methods, a few of which are:

Tricks of the Trade: How to Think About Your Research While You're Doing It by Howard Becker

Interviewing for Social Scientists by Hilary Arksey and Peter Knight

Ethnography: Principles in Practice by Paul Atkinson and Martyn Hammersley

Designing and Conducting Survey Research by Louis Rea and Richard Parker

And should you find yourself conducting participant observations in the future, just remember: be a kleptomaniac photographer with a weak bladder.

Common Sense and Doodling

By Sally Raskoff

Did your parents ever tell you to turn off your music while you were studying so that they knew that you were doing your homework? I had no headphones and my stereo had pretty big speakers so my parents were not only concerned about my study habits but also about noise pollution of their airspace.

Today we have iPods and ear buds, so parents may be less annoyed by the intrusion of their kids’ music into their own space but many still worry quite a bit about how distractions affect their children’s concentration and study time. Technological changes bring us new ways to distract ourselves hence “texting while studying” can present a new challenge for parents worried about distractions. On the other hand, perhaps they more concerned about hearing loss due to those ear buds!

In any case, parents’ main concern is often lies the diversion of attention away from academic pursuits. A recent study on doodling may offer you a way to console your parents (and teachers) and lessen their worry about such diversions.

Those who doodle during meetings (or class) may be judged as distracted and not fully paying attention to the main event. Doodlers may even hide their doodles to avoid such judgments.

But the study found that, compared with people who don’t doodle, doodlers are more likely to recall information and to perform tasks better. The study authors hypothesize that the doodling keeps daydreaming away and allows the person to retain most of their attention to the task at hand.

One might surmise that music and doodling serve the same purposes of quieting that inner dialogue or daydreaming that tempts us all. Of course, to know if this one study has results that will hold up, we would need to replicate or repeat the study and control for other factors, such as background music.

Social science research has shown us here that what may look like a distraction actually keeps distraction at bay by enabling us to more fully retain information. What appears to be common sense or obvious may not turn out to be the case when we study the phenomenon scientifically.

How people judge us is, of course, another issue. Is it easy to re-educate parents and teachers about behaviors they believe to be problematic? Using scientific findings to spark a discussion can give your argument more weight and legitimacy. Basing an argument on opinions is often less persuasive, but basing one’s points in valid and reliable scientific findings – especially when you find many studies that back up your points – can change others’ opinions.

Another twist on this situation is that people do judge others based on what they perceive to be true, and they then act on those judgments and develop expectations about those people. People may come to fulfill those expectations.

An example would be teachers who judge students as smart or not so smart and then spend their energy guiding those deemed smart into challenging activities and leaving those ”not so smart” students to repeat their basic exercises. This approach doesn’t challenge those students in the lower group, who might get bored and disengage. Even if they had abilities to do more, they won’t have access to activities that can help them improve.

The concept of a self-fulfilling prophecy has been well tested in educational settings. Students placed in the lower tracks of educational goals will do things to keep themselves there even if they are capable of doing more. This process can occur even if a teacher isn’t actually judging a student, but if the student thinks that they are being judged and labeled in some specific way. William Chambliss’ classic study, The Saints and the Roughnecks examines youth living up to the labels of others. While two groups of boys essentially engaged in the same types of rowdy behavior, one group of wealthier kids was thought to be “sowing their wild oats” while the other group of low-income kids were just thought to be bad. Chambliss found that years later the so-called “Saints” were successful, well-adjusted adults, but the “Roughnecks” had lived up to their labels as troublemakers.

Just as we might make assumptions about doodlers, what other labels do we create for people? What self-fulfilling prophesies do you think might follow?

Baby Booms: As Seen on TV?

By Karen Sternheimer

Babies and children are everywhere in the media world these days. From news coverage of the California octuplets and TLC unscripted television shows like Jon and Kate plus Eight, Table for Twelve, and Eighteen and Counting it seems like there are more people having super-sized families. Oprah recently featured the families of the Yearning for Zion polygamist sect and their multiple children. I started to wonder why there is so much focus on large families on shows like these.

A few questions came to mind:

1. Are we experiencing a new baby boom?
2. Are large families becoming more popular?
3. Are women having more multiple births (three or more babies per pregnancy)?

Let’s look at the data available to see if we can find answers.

1. Are we experiencing a new baby boom?

Thanks to the growth of social institutions, we can be fairly certain that most babies born in the United States will be accounted for. If they are not born in a hospital they are still likely to be given a social security number, so we can get a pretty good count of how many babies are born each year. In 2007, the most recent year for which we have data, the birth rate did rise slightly from 2006-- 1 percent to be exact. This was the largest number of births registered in one year in the United States.

If you take a look at the graph below you can best see this reflected in the top line, which represents the actual number of births, which is now even higher than the number during the postwar baby boom years.

Source: National Vital Statistics Reports, 2009

But before we get too carried away, look at the line below, which represents the birth rate per 1,000 women aged 15-44. A rate is a measure that takes into account the population size; since the population has grown we would expect more babies born simply because there are more people to have them. The birth rate tells us a slightly different story from the raw number above. It is far lower than the birth rate during the mid-twentieth century baby boom years, and is actually somewhat flat by comparison.

According to the Centers for Disease Control and Prevention, the average number of children per American woman decreased from 7.0 to 3.5 between 1800 and 1900. That rate declined until the baby boom after World War II (which you can clearly see in the middle of the graph below) and fell sharply in the years after. Since the mid-1970s that average has hovered below 2.0, down to an all-time low of 1.81 in several years (most recently 2007). In 2008 that number rose slightly to 1.86, but in no way does this change indicate another baby boom, at least not yet.

We can also look to see if women are having more children on average. Below is a graph that highlights the rise during the baby boom, which declined sharply after and has stayed relatively flat since. As you can see, women had an average of more than 3.5 children during the height of the baby boom years (yes, statisticians know there is no such thing as a half a person).

Source: Centers for Disease Control and Prevention, 1999

2. Are large families becoming more popular?

The data above can also help us answer the second question; the size of families has not grown in recent years, and if anything, households have fewer people now than in the past. Still, in 2006, more than 18,500 women gave birth to their eighth child or beyond. While this might seem like an incredible number of people having such big families, taking the population as a whole into account this means that only 3 in 10,000 births are to these super-sized families. The 2006 data are very similar to the 2005 numbers and the rate of 3 in 10,000 is identical. It might well be that large families get their own reality shows because they are such an anomaly.

3. Are women having more multiple births?

The birth of octuplets to Nadya Suleman sparked controversy about the problems associated with having so many babies at once. Multiple births, particularly carrying three or more babies in a pregnancy, can introduce serious health risks to both the mother and children. Stories about people desperate to bear children using new fertility technologies might suggest that this is a new and growing problem.

The graph below shows the tremendous increase in multiple births between the late 1980s and mid 1990s, as fertility technologies became more available. Also, a growing number of women now have children later in life; such women are more likely to need these fertility technologies and, even if they don’t, the likelihood of having “natural” multiples increases due to changes in an older woman’s cycle.

Source: National Vital Statistics System, 2009

The rate of multiples actually peaked in the late 1990s; the graphs above and below detail how they have actually been declining: by 16 percent since the peak in 1998. While in 1990 there were just 13 quintuplet or higher births, in 2004 there were 86 children in this category, declining to 68 in 2005. This decline is echoed in the graph below, too.

Source: National Vital Statistics System, 2009

So looking at the data we can conclude that there isn’t exactly a new baby boom, but instead a large demographic group, the children of the baby boom generation, are in their childbearing years now. Average family size isn’t growing either. And yes, women are more likely to have triplets or larger pregnancies now than in 1990 and before, but this rate is on the decline.

What other sociological reasons can you think of to explain the baby boom on TV?

Field Experiments and Racism

By Bradley Wright

When sociologists study something, we usually start by making observations. Maybe we take a survey, in which case we covert our observations to answers on a questionnaire, or maybe we’ll do fieldwork and go out into a social situation and watch what goes on. In either case, we’re not changing what we’re studying, or at least we’re not trying to, but rather we’re just watching it and recording what we learn.

In contrast to these observational studies, we could intentionally change something and then see what happens as a result. This is an experimental approach. With an experiment, you have two or more groups, and the researcher (or somebody) does something to one of the groups but not the other. What the researcher does is the independent variable (or cause). The researcher then measures the outcome of what happens—the dependent variable (or effect).

The idea of an experiment conjures up images of a mad scientist in a castle or at least well-funded psychologists in laboratories messing with introductory psychology students. Another approach, however, is called a field experiment, where the researcher conducts an experiment in a natural setting instead of laboratory.

Here’s a video that illustrates this approach. In it, the reporting team from ABC News sets up an experiment. They park an old car in a parking lot in a predominately white neighborhood. They then have several white teenagers vandalize the car for about an hour. These kids jump on the car, spray paint it, and try to break into it. During this time, several people walking by stop and talk to the kids, sometimes even telling them not to do it. However, during that period of time, only one person called the police.

Part 1:

Part 2:

Next, the reporters repeated the situation but they used African-American teens instead. The kids did the same things to the car for about the same period of time, but this time ten people called the police. The conclusion? The race of the possible offender influences whether their actions are defined as criminal, so it’s not just what people do that matters but also who they are. (Unfortunately, the news crew did not repeat the experiment in a predominately black neighborhood.)

Field experiments have a lot going for them. Like all experiments, the causality is clear. The independent variable precedes the dependent variable, and, if the study is done correctly, the change in the dependent variable is the only difference (on average) between the two groups. Sociologists call this internal validity— which means we can trust the causal story of a study.

Also, field experiments measure things that people might not report on surveys, either because they don’t want to look bad or they don’t realize that aspect of themselves. For example, imagine we gave a survey to the people in the community described above, and we asked them if they would be more likely to call police if they saw African-American kids committing vandalism. I imagine that they would all so “no”—who wants to be viewed as potentially racist? Yet, in the field experiment, that’s exactly what they did.

Finally, field experiments take place in naturalistic settings in contrast to laboratory settings which happen in small, windowless rooms in academic buildings. Now, maybe what happens in lab experiments generalizes to the real world just fine, but we’re more confident in the generalizability of field experiments because they actually happen in everyday life. Sociologists call this external validity.

So, field experiments have both high internal and external validity. Sweet deal!

This raises the question of why sociologists don’t do more field experiments. Perhaps one reason is that it’s not traditional in sociology. When I went through graduate school, I received a lot of training in survey research, some in qualitative methods, and none in experiments.

Unfortunately, it’s not always clear how to translate a sociological topic into a field experiment. Let me give you an example. I study the sociology of religion, and I am also very interested in field experiments. This makes me wonder about how to study religion using field experiments. To do this, I need to randomly assign religion, or at least the perception of religion, or randomly assign something that will change religion. Obviously I can’t just assign religious beliefs—“you’re Christian, you’re Muslim, you’re Hindu.” Also, it’s tough to assign levels of religiosity. “Could you stop going to church so much?”

So, can religion be studied using a field experiment, and, if so, how? I have some thoughts, but I would like to hear what you think. If you have some ideas, send them to me at Bradley.wright@uconn.edu. Who knows? Maybe your idea will someday be featured on a television show!

How American Congregations are Changing (and Staying the Same)

By Bradley Wright

Have you ever picked up a sociology journal and tried to read one of its articles? Well, good luck if the article uses numbers because most quantitative sociological research uses multivariate analysis such as regression that can be difficult for those without a background in statistics to understand. Now, once you get used to this type of research, these articles can make sense, but the methods do pose a barrier for most non-academics . (Qualitative studies have their own problems that typically involve using way too many big, funny sounding words that probably don’t mean anything). That’s probably why the journal American Sociological Review is not sold in supermarket checkout lines.

Every once in awhile, however, studies come along that demonstrate that some of the most important things we learn are simple percentages. Sociologist Mark Chaves provides an example with his National Congregations Study. For this study, conducted in 2006-7, Chaves interviewed pastors or other church leaders from about 1,500 churches drawn from a nationwide, random sample, and he asked them a bunch of questions about their churches. He had done a similar study in 1998, and this allowed him to measure how American congregations have changed over the last decade.

Any guesses as to how?
As reported in the Winter 2008 issue of Sociology of Religion, he and a coauthor found four main changes in congregations in the last ten years:

1) Churches use a lot more technology than they used to. They are much more likely to use e-mail to communicate with their members and web pages to advertise themselves in the community. I suppose that this change didn’t surprise me much. The church I attend now has blogs, web pages, Facebook groups, and uses something called Twitter, which may or may not involve birds. This technological change has implications for congregations. By better advertising their beliefs and values, churches might attract like-minded people from further away. This might increase the theological homogeneity of congregations—having people who have similar beliefs with one another than might have previously been the case. Technology also costs money and time, which raises the question of what are churches cutting back on to support their use of technology.

2) Worship services have become more informal. Services are now less likely to have choirs and to use written programs. Instead, they are more likely to have services featuring drums, jumping, shouting, dancing, raised hands in praise, applause, and calling out “amen.” There are some variation in which churches do which—with Catholic churches less increased informality and black churches showing more—but this increased informality appears to be a general trend in religion as it is in society as a whole. In line with this trend, probably the best known Evangelical pastor, Rick Warren, who said the invocation at Barack Obama’s inauguration, is known for wearing Hawaiian shirts when he preaches.

3) Clergy age. From 1998 to 2006, the average age of the American adults has increased by 1 year, but the average age of pastors has increased by 5 years! The median age of the head clergy in the study went from 48 years to 53 years old. That’s a big change, and it’s happening the most in Catholic and mainline Protestant churches (and least in Evangelical and black churches.) What is causing this big change? One explanation is that fewer future-pastors are going into seminary right after college, and more are taking on the ministry as a second career, after retiring from a secular career.

4) The demographic make-up of congregations is changing. Overall, the average age of congregation members is increasing faster than the general population. For example, in 2006, 30 percent of the congregants were over age 60, but in 1998, only 25% were. Also, the racial and ethnic make-up of congregations is becoming more diverse. For example, from 1998 to 2006 the number of completely white congregations dropped from 20% to 14%.

Now, so far I have focused on the changes in American churches because, for some reason, discussing changes is more interesting than thinking about what stays the same; nonetheless, the study found a number of things that have stayed about the same over the past decade. They include the median size of congregations (about 75 people), the high number of women in the pews, the low number of women in the pulpit, and involvement in social services.

There, wasn’t that interesting, and you didn’t have to read a single regression coefficient. Maybe sociology journals just need to make themselves more accessible to the general public. I’m thinking more pictures of Brad Pitt and Angelina Jolie on the cover?

(By the way, you get extra credit if you recognized the drummer pictured above).