CHAPTER J • _•. * • • • I * a 9 9 Human Inquiry and Science Holographic Overview * All of us try to understand and predict the social world. Science—and social research in particular—are designed to avoid the common pitfalh of ordinary human inquiry, m Introduction Looking for Reality Ordinary Human Inquiry Trad i i ion Authority Errors in inquiry, and Some Solutions What's Really Real? The foundations of Social Science Theory, Nut Philosophy or Belief Social Regularities Aggregates. Not Individuals A Variable Language Some Dialectics of Social Research Idtographic and Nomothetic Explanation Inductive and Deductive Theory Qualiiauve and Quantitative Data The Ethics of Social Research Voluntary Participation No Harm 10 Subjects MAIN POINTS KEY TERMS REVIEW QUESTIONS AND EXERCISES ADDITIONAL READINGS SOCIOLOGY WEB SITE INFOTRAC COLLEGE EDITION 1« Intfodudion . 17 Introduction This book is about knowing things—noi so much what we know as how we know it. Lei's start by examining a lew things you probably know already. You know the world is round. You probably also know it's cold on the dark side of the moon, and you know people speak Chinese in China. You know that vitamin C prevents colds and thai unprotected sex can result in AIDS. How do you know? Unless you've been to ihc dark side of the moon lately or done experimental research on Uic virtue* oí vitamin C. you know diese things because somebody told them to you, and you believed what you (vere told. You may have read in Nuionai Geographic that people speak Chinese in China, and that made sense to you, so you didn't question it- Perhaps your physics or astronomy instructor told you ii was cokj on the dark side oi the moon, or maybe you read it in Some of the things you know seem absolutely obvious to you. If someone asked you how you know the world is round, you'd probably say, "Everybody knows that" There are a lot of things everybody knows. Oi course, at one time, everyone -knew" the world was "at. Most of what you ind I know Is a mailer ol agreement and belief. Linie of it is based on personal experience and discovery. A big pan o( growing up in any society in lact, is the process of learning lo accept what everybody around us "knows" is so. If you dotťl know those same things, you can'i really be a part of the group. If you were to question seriously whether 'he world Is really round, you'd quickly find yourself set apart from other people. Vou might be sent to live in a hospital with other people who question things like that. Although it's important to realize mat most ol what we know Is a maltet ol believing what we've been told, there's nothing wrong »vidi us in thai respect. It's simply the way human sociciies are structured, and it is quite a useful quality. The basis of knowledge is agreement. Because we can't learn all we need to know by means of personal experience and discovery alone, things arc set up so we can simply believe what others tell us. Vic know some things through tradition, some things from 'experts.* There are other ways of knowing things, however, in contrast to knowing things through agreement, we can know ihem through direct experience—through observation. If you dive Into a glacial stream flowing Uirough the Canadian Rockies, you don't need anyone to tell you ifs cold: you notice it aU by yourself. The first time you stepped on a thorn, you knew it hun belore anyone told you. When our experience conflicts with what everyone else knows, though, there's a good chance we'll surrender our experience in favor of ihc agreement. Let's take an example. Imagine you've come to a party at my house. It's a high-class affair, and the drinks and food arc excellent. In particular, you are taken by one of the appetizers I bring around on a tray: a breaded, deep-fried appetizer that's especially zesty. You have a couple—they're so delicious! You have more. Soon you are subtly moving around the room to be wherever 1 am when I arrive with a tray of these nibblies. Finally, you can't contain yourself any more. "What arc ihey?' you ask. "How can I get the recipe?" And I let you in on the secret: "You've been eating breaded, deep-fried worms!* Your response is dramatic Your stomach rebels, and you stifle the urge to throw up all over ihe living-room rug. Awful! What a terrible thing to serve guestst The point of the story is that both of your feelings about the appetizer were quite real. Your initial liking for them, based on your own direct experience, was certainly real. But so was the feeling of disgust you had when you found out that you'd been eating worms. It should be evident, however, thai this feeling of disgust was strictly a product of the agreements you have with those around you that worms aren't fit to eat. That's an agreement you entered into the first time your parents found you silling in a pile of din with halt of a wriggling worm dangling Írom your lips. When they pried your mouth open and reached down your throat in search of the other half of the worm, you learned ihat worms are not acceptable lood In our sodeiy. 18 - Chapter 1: Human Inquiry aadSôenct Aside from these agreements, what's wrong with worms? They are probably high in protein and low In calories Site-sized and easily packaged, they are a distributor's dream. They are also a delicacy lor some people who live in societies that lack our agreement that worms are disgusting. Some people might love the worms but be turned ofl by the deep-tried breading. Here's a question you might consider: "Are worms 'really' good or 'really' bad to eat?* And here's a more interesting question: "How could you know which was really so?" This book is about answering the second kind of question. The rest of this chapter looks at how we know what is real. We'll begin by examining inquiry as a natural human activity, something we all have engaged in every day of our lives. We'll look at the source of everyday knowledge and at some kinds ol errors we make in normal inquiry. We'll then examine what makes science—in particular, social science—dilferent. After considering some ol the underlying Ideas of social research, we'll con-dude with an Initial consideration ol issues in social research. Looking for Reality Reality is a tricky business. You probably already suspect that some of the things you "know" may not be true, bur how can you really know what's real? People have grappled with this question for thousands of years. One answer that has arisen out of that grappling is science, which offers an approach to both agreement reality and experiential reality. Scientists have certain criteria that must be met before they will accept the reality of something they Iiaven't personally experienced. In general, a scientific assertion must have both logical and empirical support: It must make sense, and it must not contradict actual observation, why do eanhbound scientists accept the assertion that its cold on the dark side of the moon? First, it makes sense, because the moon's surface heat comes from the sun's rays, and the dark side of the moon is dark because it's turned away (rom the sun. Second, scientific mea- surements made on the moon's dark side confirm this logical expectation. So, scientists accept the reality of things they don't personally experience— ih«y accept m agreement reality—but they have special standards for doing so. More to the point ol this book, however, science offers a special approach to the discovery of reality through personal experience. In other words, it oilers a special approach to the business ol inquiry. Epistcmotogy is the science of knowing; methodology {a subficld ol epistemology) might be called the science of finding out. This book is an examination and presentation ol social science methodology, or how social scientists find out about human social life. why do we need social science to discover the reality of social life? To find out. let's first consider what happens in ordinary, nonscientific inquiry. Ordinary Human Inquiry Practically all people, and many other animals as well, exhibit a desire to predict their future circumstances. Humans seem predisposed to undertake thü task using causal and probabilistic reasoning. First, we generally recognize that future circumstances arc somehow caused ot conditioned by present ones. We learn that getting an education will aHcct how much money we earn later tn life and that swimming beyond the reef may bring an unhappy encounter with a shark. Sharks, on the other hand—whether or not they reason the matter through—may learn that hanging around the reef often brings a happy encounter with unhappy swimmers. Second, people, and seemingly other animals, also learn that such patterns ol cause and effect are probabilistic In nature. That is, the effects occur more often when the causes occur than when the taiises are absent—but not always. Thus, students learn that studying hard produces good grades in most instances, but not every time. We recognize ihe danger of swimming beyond the reef without believing that every such swim will be fatal. As we'll sec throughout the book, science makes these concepts of causality and probability more explicit &\A provides techniques lor dealing with them ..::•' .'.':■■ ■■■: :, . 19 more rigorously than does casual human inquiry. It sharpens the skills we already have by making us more conscious, rigorous, and explicit in our inquiries. In looking at ordinary human inquiry, we need to distinguish between prediction and understanding. Often, we can make predictions without understanding—perhaps you can predict rain when your trick knee aches. And often, even if we don't understand why. we arc willing to act on the basis ol a demonstrated predictive ability. A racetrack buff who discovers that the third-ranked horse in the third race of the day always seems to win will probably keep betting without knowing, or caring, why it works out tliat way. Ol course, the drawback in predicting without understanding will be powerfully evident when one of the other horses wins and our buff loses a week's pay. Whatever the primitive drives or instincts that motivate human beings and other animals, satisfying them depends heavily on the ability to predict future circumstances. For people, however, the attempt to predict is often placed in a context of knowledge and understanding. If you ran understand why things are related to one another, why certain regular patterns occur, you can predict better than if you simply observe and remember those patterns. Thus, human inquiry aims at answering both "what' and "why" questions, and we pursue these goals by observing and figuring out. As I suggested earlier in ihis cliapter. our attempts to learn about the world are only partly linked to direct personal inquiry or experience. Another, much larger, pan comes from tlie agreed-upon knowledge that others give us. those things 'everyone knows." This agreement reality both assists and hinders our attempts to find out for ourselves. To see how, consider two important sources of our secondhand knowledge—tradition and authority. Tradition Each ol us Inherits a culture made up. in pan. of firmly accepted knowledge about the workings of ihe world. We may learn (rom others that planting corn in the spring will gamer the greatest assis tance from the gods, that eating too much candy wijl decay our teeth, that the circumference of a circle is approximately twcniy-two sevenths of its diameter, or that masturbation will blind us. We may test a tew of these "truths* on our own. but we simply accept the great majority of them. These are things that "everybody knows." Tradition, in «his sense ol the term, offers some clear advantages to human inquiry. By accepting what everybody knows, we are spared the overwhelming task of starting from scratch in our search lor regularities and understanding. Knowledge Is cumulative, and an inherited body of information and understanding is the jumping-off point (or the development ol more knowledge, we often speak of "standing on the shoulders of giants." that is. of previous generations. At the same time, tradition may hinder human inquiry. If we seek a fresh understanding of something everybody already understands and has always understood, we mav be marked as fools for our efforts. More to the point, however, it rarely occurs to most of us to seek a different understanding of something we all 'know" to be true. Authority Despite the power of tradition, new knowledge appears every day. Quite aside from our own personal inquiries, we benefit throughout our lives from new discoveries and understandings produced by others. Often, acceptance ol these new acquisitions depends on the status of the discoverer. You're more likely to believe the epidemiologist who declares that the common Cokl can be transmitted through kissing, for example, than to believe your uncle Pete. like tradition, authority can both assist and hinder human inquiry. We do well tn trust in the judgment of the person who has special training, expertise, and credential* in a given matter, especially In (he face ol controversy. At the same time, inquiry can be greatly hindered by the legitimate authorities who err within their own province. Biologists, after all. make their mistakes in the field of biology. Moreover, biological knowledge changes over time. 20 . Chapter 1: Human Inquiry and SoeiKt Inquiry is also hindered xvhen we depend on die authority ol expem speaking outside their realm o( expertise. For example, consider the political or religious leader with no medical or biochemical expertise who declares that marijuana can fry your brain. The advertising industry plays heavily on this misuse of authority by, for example, having popular athletes discuss the nutritional value of breakfast cereals or having movie actors evaluate the performance ol automobiles. Both tradition and authority, then, are double-edged swords in the search for knowledge about the world. Simply put. they provide us with a starting point for our own inquiry, bul they can lead us to stan at the wrong point and push us off In the wrong direction. Errors in inquiry, and Some Solutions Quite aside from the potential dangers ol tradition and authority, wc often stumble and fall when we set out to leam for ourselves. Let's look at some ol the common errors we make in our casual inquiries and at the ways science guards against those errors. Inaccurate Observations Quite frequently we make mistakes in our observations. For example, what was your methodology instructor wearing on the Hrst day ol class? If you have to guess, it's because most of our daily observations are casual and semiconscious. Tliat's why we often disagree about what really liappened. in comrasi to casual human inquiry, scientific observation is a conscious activity, simply making observation more deliberate helps reduce error. If you had to guess what your instructor was wearing on the first day of class, you'd probably make a mistake. If you had gone to the first class with a conscious plan to observe and record what your instructor was wearing, however, you'd be far more likely to be accurate. In many cases, both simple and complex measurement devices help guard against inaccurate ob-servaOons. Moreover, they add a degree of precision well beyond the rapacity of the unassisted human senses. Suppose, for example, thai you had taken color photographs of your instructor that day. Overgeneralization When we look for patterns among the specific things we observe around us. we often assume that a lew similar events are evidence of a general pattern. That is. we overgeneralWe on the basis of lim-lied observations. (Think back to our now-broke racetrack buff.) Probably the tendency to ovcrgencralize is greatest when the pressure to arrive at a general understanding is high. Vet it also occurs without such pressure. Whenever overgeneralization does occur, it can misdirect or impede inquiry. Imagine you are a reporter covering an animal-rights demonstration. Vou have orders to turn tit your story in just two hours, and you need 10 know why people are demonstrating. Bushing to the scene, you stan interviewing ihem. asking for their reasons. If the first three demonstrators you interview give you essentially me same reason, you may simply assume that the other 3.000 arc also there íor that reason. Unfortunately, when your story appears, your editor gets scores of letters from protesters who were there for an entirety different reason. Scientists guard against overgeneralization by committing themselves in advance to a sufficiently large and representative sample of observations. Another safeguard is provided by the replication of inquiry. Basically, replication means repeating a study and checking to sec whether the same results are produced each time. Then, as a further test, the study may be repeated again under slightly varied conditions. Selective Observation One danger of overgcneralizauon is that it may lead to selective observation. Once wc have concluded lhal a particular panem exists and have developed a general understanding ol why It exists, we tend to focus on future events and situations that fit the pattern, and we tend to ignore those that don't. Racial and ethnic prejudices depend heavily on selective observation lor their persistence. i.....;n0;r-^l|[, . 21 Sometimes a research design will specify in advance the number and kind of observations to be made, as a basis lor reaching a conclusion. If we wanted to learn whether women were more likely than men to support freedom to choose an abortion, we'd commit ourselves to making a specified number of observations on that question in a research projecr. We might select a thousand carefully chosen people to be interviewed on the Issue. Alternately, when making direct observations of an event, such as attending the animal-tights demonstration, social researchers make a special effort to find 'deviant cases"—precisely those who do not fit into the general pattern. Concluding that one youth became delinquent largely because ol a lack of positive adult role models draws attention to the part role models play in keeping most youths on the straight and narrow. Illogical Reasoning There are other ways in which we often deal with observations that contradict our understanding of the way things are in daily life. Surely one of the most remarkable creations ol the human mind is "the exception thai proves the rule." That idea doesn't make any sense ai all. An exception can draw attention to a rule or to a supposed rule, but in no system of logic can it prove the rule It contradicts. Even so, we often use this pithy saying to brush away connadictions with a simple stroke of illogic. What statisticians have called the gambler's fallacy is another illustration of illogic in day-io-day reasoning. Often wc assume that a consistent run of either good or bad luck foreshadows Its opposite. An evening of bad luck at poker may kindle the belief that a winning hand is just around the corner. Many a poker player has stayed in a game much too long because of that mistaken belief. Conversely, an extended period of good weather may lead you to worry that it is certain to tain on the weekend picnic Although all of us sometimes lall into embarrassingly illogical reasoning, scientists try to avoid this pitfall by using systems of logic consciously and explicitly. We'll examine the logic of science in more depth in Chapter 2. For now. it's sufficient to note that logical reasoning is a conscious activity for scientists and that other scientists arc always around to keep them honest. Science, then, attempts to protect its inquiries Irom the common pitfalls in ordinary inquiry. Accurately observing and understanding reality Is not an obvious or trivial matter Indeed, its more complicated than have I suggested. What's Really Real? Philosophers sometimes use the phrase "naive realism" to describe the way most of us operate in our daily lives. When you sit at a tabic to write, you probably don't spend a lot of time thinking about whether the table is really made up of atoms, which in tum are mostly empty* space. When you step into the street and see a city bus hurtling down on you. it's not the best time to reflect on methods for testing whether the bus really exists. Wc all live witli a view thai what's real is pretty obvious—and that view usually gets us through the day. 1 don't want this book to interfere with your ability to deal with everyday life. I hope, however, that the preceding discussions have demonstrated that the nature of 'reality" ts perhaps more complex than we tend to assume In our everyday functioning. Here arc three views on reality that will provide a philosophical backdrop (or the discussions of science to follow. They are sometimes called premsdtrn. modem, and postmodern views ol reality (W. Anderson 1990). The Premodern View This view of reality has guided most of human history. Our early ancestors all assumed that they saw things as they really were- In fact, this assumption was so fundamental that they didn't even sec it as an assumption. No cavemom said to hercavekid. "Our tribe makes an assumption thai evil spirits reside in the Old Twisted Tree." No. she said. "STAY OUT OF THAT TREE OR YOU'LL TURN INTO A TOADr AS humans evolved and became aware of their diversity, they came to recognize that others did not always share their views of things. Thus, they may 22 - Oupiefl: Human Inquiry mí Sopkc have discovered that another tribe didn't buy the wicked tree thing; in fact, the second tribe felt the spirits in the tree were holy and beneficial. The discovery of this diversity led members of the first tribe to conclude that "some tribes I could name art pretty stupid.* For them, the tree was soil wicked, and they expected that some misguided people would soon be moving to Toad City. The Modem View What philosophers call the motitni view accepts sudi diversity as legitimate, a philosophical "different strokes lor different folks." As a modern thinker, you would say. ". regard the spirits in the tree as evil, but 1 know ixhcrs regard them as good. Neither of us is nght or wrong. There are simply spirits in the tree. They are neither good nor evil, but different people have different ideas about them." Its easy for many of us to adopt the modern view. Some might regard a dandelion as a beautiful flower while others see only an annoying weed. To the prernodcrns, a dandelion has to be either one or the other. U you think it is a weed, it is reafly a weed, though you may admit that some people have a warped sense o( beauty, in the modern view, a dandelion is simply a dandelion. It is a plant with yellow petals and green leaves. The concepts 'beautiful flower" and "annoying weed" are subjective points of view imposed on the plant by different people. Neither is a quality ol the plant itself, just as "good" and "evil- were concepts imposed on the spirits in the tree. The Pottmodern View Increasingly, philosophers speak of a pasonodem view of reality, in this view, the spirits don't exist-Neither does the dandelion. All thais "real" are the images we get through out points o[ view. Put differently, there's nothing out there. It's all in here. As Gertrude Stein said of the City of Oakland. "There's no there, there." No maner how bizarre the postmodern view may seem to you on fits: reflection, it has a certain ironic inevitability. Take a moment to notice the book you are reading; notice specifically what it FIGURE 1-1 A Book looks like. Since you ate reading thexe wonts, it probably looks something likt Figure 1-1A. But does Figure 1-1A represent the way your book 'really' looks? Or does it merely represent what the book looks like from your current point o| view? Surely. Figures 1-1B. C. and D are equally valid representations. But these views o! the book are so different from one another. Which i$ the "reality"? As tins example illustrates, 'here is no answer to the question. "What does the book really look like?" All we Cín offer is the different ways it looks from different points of view. Thus, according to the rxistrnodern view, there is no "book." only van-ous images of it from different points ol view. And all die different images are equally 'true." Now let's apply this logic to a sijcial situation. Imagine a husband and wife arguing. When she looks over at her quarreling husband. Figure 1-2 is what the wife sees Take a minute to Imagine what you would (eel and think if you were the woman in (his drawing. How would you explain later to your best fnend what had happened? What solutions to the conflict would seem appropriate il you were this woman? 01 course, what the woman's husband sees is another matter altogether, as shown in Figure I-J. Take a minute to imagine experiencing the situation from his point of view, what thoughts and feelings would you have? How would you tell your letting forRtalit* . 23 FIGURE 1-2 Wife's Point of View best friend what had happened? What solutions would se«m appropriate for resolving the conflict? Now consider a third point of view. Suppose you are ail outside observer, watching this interaction between a wife and husband. What would it look like to you now? Unfortunately, we can't easily portray the third point of view without knowing something about the personal feelings, beliefs, past experiences, and so forth that you would bring to your task as "outside' observer. (Though I call you an outside observer, you are. of course, observing from inside your own mental system.) To take an extreme example, il you were a confirmed male chauvinist, you'd probably see the fight pretty much the same way that the husband saw it. On the other hand, if you »ere committed to the view tliat men are generally unreasonable bums, you'd see things the way the wife saw them in ihe earlier picture. But Imagine that instead you see two unreasonable people quarreling irrationally with each another, would you see them both as irresponsible jerks, equally responsible for the conflict? Or would you see ihem as (wo people facing a difficult human situation, each doing the best he or she can to resolve it? Imagine feeling compassion for them and noticing how each of them attempts to end the hostility; even though (he gravity of the problem keeps them lighting. Notice how different these several views 3re. Which IS a "true" picture of what is happening between the wife and the husband? You win ihe prize it you notice that the personal viewpoint you bring (o the observational task will again color your perception of wliat is happening. The postmodern view represents a critical dilemma fot scientists. While their task ts to observe and understand what is "really" happening, they are all human and. as such, bring along personal orientations (hat will color wliat they observe and how they explain it. There Is ultimately no way people can totally step outside their humánne» to 24 . Chapter i: Human Inquiry and Swore FIGURE 1-3 Huibanďs Pane of View sec and understand the world as U "really' is—thai is. independently oí all human viewpoints. whereas the modem view acknowledges the inevitability o( human subjectivity, the postmodern view suggests there is actually no "objective" reality to be observed In the first place. There are only our several subjective views. You may want to ponder these three views ol reality on your own for awhile. We'll return to them In Chapter 2 when me locus on more specific scientific paradigms. Ultimately, two points will emerge. First, established scientific procedures Sometimes allow us to deal cifcciively with this dilemma—that is, wc can study people and help them through their difficulties without being able to view "reality" directly Second, different philosophical stances suggest a powerful range ol possibilities for structuring our research. Let's turn now from general philosophical ideas to the foundations of social scientific approaches to understanding in particular. A consideration of these underpinnings of social research will prepare the way lor our exploration of specific research techniques. The Foundations of Social Science Science is sometimes characterized as loglco-empirical. This ungainly term carries an important message: As we noted earlier, the two pillars of science are logic and observation. That is. a scienrific understanding of the world musí both make sense and correspond to what we observe. Both elements are essential to science and relate to the three major aspects of social scientific enterprise: theory, data collection, and data analysis. To oversimplify just a bit. scientific theory deals with the logical aspect of science, whereas data col- li* foundations GfSodalSden« - 25 lection deals with the observational aspect. Data analysis looks for patterns in observations and. where appropriate, compares what is logically expected with what is actually observed. Although this book is primarily about data collection and data analysis—that is, how to conduct social research—the rest of Part I is devoted to the theoretical context of research. Parts 2 and 3 then focus on data collection, and Part 4 offers an introduction to the analysis of data. Underlying the concepts presented in the rest of the book are some fundamental ideas thai distinguish social science—theory, data collection, and analysis—from other ways of looking at social phenomena. Lcťs consider these ideas. Theory, Hot Philosophy or Belief Today, social theory has to do with what is. not with what should be. For many centuries, however, social theory did not distinguish between these two orientations. Social philosophers liberally mixed their observations of what happened around them, their speculations about why, and iheir ideas about how things ought tobe. Although modern social researchers may do the same from «me 10 lime, as scientists they locus on how things actually are and why. This means that scientific theory—and, more broadly, science itself—cannot settle debates about values. Science cannot determine whether capitalism is better or woise lhan socialism. What it can do is determine how these systems perform in terms of some sei off agreed-upon criteria. For example, we could determine scientifically whether capitalism or socialism mosi suppons human dignity and freedom only if we first agreed on some measurable definitions of dignity and Ireedom. Our conclusions would then be limited to the meanings specified in our definitions. They would have no general meaning beyond thai. By ihe same token, if we could agree that suicide raics, say. or giving lo charily were good measures of the quality of a religion, ihen we could determine scieniificaliy whether Buddhism or Christianity is the beticr religion. Again, our con- clusion would be inextricably lied (o our chosen criteria. As a practical maner, people seldom agree on precise criteria for determining issues of value, so science is seldom useful in settling such debates. In fact, questions like ihese arc so much a matter of opinion and belief thai scientific inquiry is often viewed as a threat to what is "already known.' We'll consider this issue in more detail in Chapter 12. when we look at evaluation research. As you'll sec. researchers have become increasingly involved in studying social programs that refleci ideological points of view, such as alhrrnative action or welfare reform. One of the biggest problems they face Is getting people to agree on criteria of success and failure. Yet such criteria are essential if social research is to tell us anything useful about mailers of value. By analogy, a stopwatch cannot tell us if one sprinter is better tlian another unless we first agree ihai speed is the critical criterion. Social science, then, can help us know only what is and why. we can use it to determine what ought to be only when people agree on the criteria for deckling what outcomes are beuer others—an agreement that seldom occurs. As 1 indicated earlier, even knowing 'what is and why" is no simple lask. Let's turn now to some of ihe fundamental ideas that underlie social science's efforts to describe and understand social reality. Social Regularities In large part, social research aims ty find paucrns ol regularity in social life. Although that aim is shared hy all science, it is sometimes a barrier for people when they first approach social science. Certainly at first glance the subject maner of the physical sciences seems to be more governed by regularities than does that of the social sciences. A heavy object falls 10 earth every time we drop it. but a person may vote lor a particular candidate in one election and against that same candidate in the next. Similarly, ice always melts when heated enough, but habitually honesi people sometimes steal. Despiie such examples, however, social affairs do exhibit a high degree of regularity that 26 . Chapter 1: Humar. Iiujt-y ind Stieme can be revealed by research and explained by theory. lb begin wiih. a vast number of formal norms in sociecy create a considerable degree of regularity. For example, traffic laws in the United States induce the vast majority ol people to drive on the right side of the street rather than the left. Registration requirements for voters lead to some predictable patterns in which classes of people vote in national elections. Labor laws create a high degree of uniformity in the minimum age of paid workers as well as the minimum amount they are paid. Such formal prescriptions regulate, or regularize, social behavior. Aside from formal prescriptions, we can observe other social norms that create more regularities. Among registered voters. Republicans are more likely than Democrats to vote for Republican candidates. University professors tend to earn more money than do unskilled laborers. Men tend to earn more than women. And so on. Three objections are sometimes raised in regard to such social regularities. First, some of the regularities may seem trivial. For example. Republicans vote (or Republicans; everyone knows thai. Second, contradictory cases may be cited, indicating that the "regularity* isn't totally regular. Some laborers make more money than do some professors. And third, it may be argued that, unlike the heavy objects that cannot decide net to fall when dropped, the people involved in the regularity could upset the whole thing if they wanted to. Let's deal with each of these objections in turn. The Charge of Triviality During World War IL Samuel Stouffer. one of the greatest social science researchers, organized a research branch in the U.S. Army to conduct studies in support of the war effort (Stouffer et al. 1949-19901. Many of the studies concerned the morale among soldiers. Stouffer and his colleagues found there was a great deal of "common wisdom* regarding the bases of military morale. Much of their research was devoted tu testing these "obvious" truths For example, people had recognized for a long rime that promotions affect morale in the military. when military personnel get promotions and the promotion system seems fair, morale rises. Moreover, it makes sense thai people who are getting promoted will tend to think the system is fair, whereas those passed over will likely think the system is unfair. By extension, it seems sensible that soldiers in units with slow promotion rates will tend to think the system is unfair, and those in units with rapid promotions will think the system is fair. But was this the way they really fell? Stouffer and his colleagues focused their studies on two units: the Military Police (MPs), which had the slowest promotions in the Army, and the Army Air Corps (forerunner of the U.S. Air Force), which had ihe fastest promotions. It stood to reason that MPs would say the promotion system was unfair, and the air corpsmen would say it was fair. The studies, however, showed just the opposite. Notice the dilemma faced by 3 researcher in a situation such as this. On the one hand, the observations don't seem to make sense. On th« other hand, an explanation that makes obvious good sense isn'r supported by the facts. A lesser person would have set the problem aside "for further study.* Siouffer. however, looked (or an cxplanaiion for his observations, and eventually he found It. Robert Merton and some other sociologists at Columbia University had begun thinking and writing about something they called reference group ikeory. Tltis theory says thai people judge their lot in life less by objective conditions than by comparing themselves with others around ihem—their reference group. For example, if you lived among poor people, a salary of $50.000 a year would make you (eel like a millionaire. But if you lived among people who earned S500.0QO a year, that same $50.000 salary would make you feel impoverished. Siouffer applied this line of reasoning to ihe soldiers he had studied. Even If a particular MP had not been promoted (or a long tlnte, it was unlikely that he knew some less deserving person who had gotten promoted fasier. Nobody got promoted in the MPs. Had he been in the Air Corps^even if he had gotten several promotions in rapid succession—he would probably be able to point to someone less deserving who had gotten even (aster pro- The foundations of SoculSoencr . 27 motions. An MP* reference group, then, was his fellow MPs. and the air corpsman compared himself with fellow corpsmen. Ultimately, then. Stouffer reached an understanding ol soldiers' attitudes toward the promotion system that (I) made sense and (2) corresponded lo the facts. This story shows that documenting the obvious is a valuable function of any science, physical or social. Charles Darwin coined the phrase "fool's experiment" to describe much of his own research— research in which he tested things that everyone else 'already knew.' As Darwin understood, all too often, the obvious rums out to be wrong; thus, apparent triviality is not a legitimate objection io any scientific endeavor. What about Exceptions? The objecrion that there arc always exceptions to any social regularity does not mean that the regularity itself is unreal of unimportant. A particular woman may well cam more money than most men. but that will be a small consolation to the majority of women, who earn less. The paitem still exists. Social regularities, in other words, are probabilistic patterns, and they are no less real simply because some cases don't fii the general pattern. This point applies in physical science as well as social science. Subatomic physics, for example, is a science of probabilities. In genetics, the mating of a blue-eyed person with a brown-eyed person will probably result in a brown-eyed offspring. The birth of a blue-eyed child docs not destroy the observed regularity, because the geneticist states only that the brown-eyed offspring is more likely and. further, that brown-eyed offspring will be born in a certain percentage of the cases. The social soemisi makes a similar, probabilistic prediction—thai women overall arc likely to earn less than men. Once a pattern like this is observed, ihe social scientist has grounds for asking why it exists. People Could Interfere Finally, the objection that observed social regularities could be upset through the conscious will of the actors is not a serious challenge to social sci- ence, even though there d«es not seem to be a parallel situation in the physical sciences. (Presumably physical objects cannot violate the laws ol physics, although the probabilistic nature of subatomic physics once led some observers to postulate that electrons had free will.) There is no denying that a religious, right-wing bigot could go to the polls and vote lor an agnostic left-wing African American If he wanted to upset political scientists studying the election. All voters in an election could suddenly switch to the underdog jusi to frustrate the pollsters. Similarly, workers could go to work eariy or stay home from work and thereby prevent the expected rush-hour traffic. But these things do not happen often enough to threaten seriously the observation of social regularities. Social regularities, ihen. do exist, and social scientists can detect them and observe iheir effects. when these regularities change over time, social scientists can observe and explain those changes. Aggregates, Not Individuals The regularities of social life that social scientists study generally reflect the collective behavior of many individuals. Although social scientists often study motivations thai affect individuals, the individual as such is seldom the subject of social science. Instead, social scientists create theories about the nature of group, rather titan individual, life. Similarly, rhe objects of iheir research are typically aggregates, or collections, raiher than individuals. Sometimes the collective regularities are amazing. Consider ihe birthrate, lor example. People have babies for any number of personal reasons. Some do it because their own parenis want grandchildren. Some feel it's a way of completing their womanhood or manhood. Others want io hokJ their marriages together, enjoy the experience ol raising children, perpetuate the (amily name, or achieve a kind of immortality. Still others have babies by accident. If you have fathered or given birth to a baby, you could probably rell a much more detailed, idiosyncratic story. Why did you have the baby when you did. rather than a year earlier or later? Maybe 28 . Chapter 1: Hurrian Inquiry and Science TABLE 1-1 Birthrates. Untied States:1977-1996 1977 15.1 1987 15.7 1978 15 1 1988 16.0 1979 15.fi 1989 16.4 1980 15.3 1990 16.7 I9S1 15-i 1991 16J 1982 15.9 1992 15.9 1983 15.6 1993 15.5 1984 15.6 1994 15.2 1935 15 í ■w, 148 ■9ĚĎ 15.6 1996 14" üirtr (enim Hi Dit*«* Ccnirot aid PtewíOoň lUlioud tMiltf for Hum iariiTOllWW^ifcwnVWrftaWiatowídt.SuspIJ:» you losí your Job and had lo delay a year before you could aßord to have the baby. Maybe you only felt (he urge io become a parent afier someone dose io you had a baby. Everyone who had a baby lasi year had their own reasons for doing so. Yet. despite this vast diversity, and despite (he idiosyncrasy ol each individuals reasons, the overall birthrate In a society— the number ol live births per 1,000 population—is remarkably consistent from year to year. See Table 1-1 (or 20 years oi birthrates for the United Slates. If the US. birthrate were 15.9. J5.6. 7.S. 28.9. and 16.2 in live successive years, demographers would begin dropping iike flies. As you can sec. however, social life is far more orderly than that. Moreover, this regularity occurs without soctcty-widc regulation. No one plans how many babies will be bom or determines who will have them. You do not need a permit to have a baby; in fact, many babies arc conceived unexpectedly, and some are borne by unwilling mothers. Social scientific theories, then, typically deal with aggregated, not individual, behavior. Their purpose is to explain why aggregate patterns of behavior are so regular even when the Individuals participating in them may change over time. It could be said thai social scientists don't even seek to explain people. They try to understand the systems in which people operate, the systems that explain why people do what they do. The elements in such a system are not people but variables. A Variable Language Our most natural attempts at understanding usually take place at the level ol the concrete and idiosyncratic. That's just the way we think. Imagine that someone says to you. "Women ought to get back into the kitchen where they belong.' You are likely to hear that comment in terms of what you know about the speaker. II its your old uncle Harry who, you recall, is also strongly opposed to daylight saving time, zip codes, and personal computers, you are likely to think his latest pronouncement simply fits into his rather dated point of view about things in general. If, on the othei hand, the statement was muttered by an incumbent politician who was trailing a female challenger in an election race, you would probably explain his comment in a completely different way. In both examples, you're trying to understand the behavior of a particular individual. Social research seeks insights into classes or types ol individuals. Social researchers would want to find out about the kind of people who share that view of women's 'proper' role. Do those people have other characteristics in common that may help explain their views? Even when researchers focus their attention on a single case study—such as a community or a juvenile gang—their aim is to gain insights that would help people understand oilier communities and other juvenile gangs. Similarly, the attempt to fully understand one individual carries the broader purpose of understanding people or types of people in general. When this venture into understanding and explanation ends, social researchers will be able to make sense out of more than one person. In understanding what makes a group of people hostile to women who are active outside the home, they gain insight into all the individuals who share thai characteristic. This is possible because, in an important sense, they have not been studying amifemi-nists as much as ihcy have been studying antifemi-nistn. It might be then turn out that Uncle Harry foe fixations olSctial Some ■ 29 and the politician have more in common than first appeared. Antifeminism is spoken of as a variable because it vanes. Some people display the attitude more than others. Social researchers are interested in understanding the system of variables that causes a particular anitude to be strong in one instance and weak in another. The idea of a system composed of variables may seem rather strange, so let's look at an analogy. The subject of a physician's attention is the patient. If the patient is ill, the physician's purpose is to help the patient get well. By contrast, a medical researcher's subject matter is different: the variables that cause a disease, for example. The medical researcher may study the physician's patient, but for the researcher, that patient is relevant only as a carrier of the disease. Thai is not to say that medical researchers don'i care about real people. They certainly do. Their ultimate purpose in studying diseases b to protect people from them. But in their research- they are less interested in individual patients titan they are in the patterns governing the appearance of the disease. In fact, when they can study a disease meaningfully without involving actual patients, they do so. Social research, then, involves the study of variables and their relationships. Social theories arc written in a language ol variables, and people get involved only as the 'carriers' of those variables. Variables, in turn, have what social researchers call attributes or values. Attributes are characteristics or qualities that describe an object—in litis case, a person. Examples include female, Asian, alienated, conservative, dishonest, intelligent, and farmer. Anything you might say to describe yourself or someone else involves an attribute. Variables, on the other hand, are logical groupings of attributes. Thus, for example, male and female are attributes, and sex or gender are the variables composed of those two attributes. The variable cauptaicn is composed of anributes such as farmer, professor, and truck driver. Soäaldasí is a variable composed oía set of attributes such as upper dass, middle dass, and lower class. Sometimes It helps to think of attributes as the 'categories' FIGURe 1-4 Variables and Attributes. In social research and theory, both variables and attributes represent social concepts. Variables are sets of related values, or attributes. Some Common Social Concepts female Ag< Upper da» African í/ner>can Voting Occupation Social da» Gender fücf/ethnkit» FTumbet * var.'ľ .: Attributes Ac* Youno,,iN4&-a9ed,oM Gender Female, male Occupation f1umbef,ljw¥« «a-entry deit. .. Rate/ethnoty Aman-Amef«n,*'Jan, Caucasun, UOno... íwndíii IJDIiľr.rmaali! ÍM! . that make up a variable. (See Figure 1-4 for a schematic review of what sodal scientists mean by variables and attributes.) The relationship between attributes and variables lies at the heart ol both description and explanation in science. For example, we might describe a college class in terms of the variable gender by reporting ihe observed frequencies ol tlie attributes male and female: 'The class is 60 percent men and 40 percent women." An unemployment rate can be thought of as a description ol the variable employment status of a labor/era in terms of the attributes employed and unemployed. Even the rcpoii of {amity income for a city is a summary ol attributes composing that variable: $3.124; S1O.9S0; $35.000; and so forth. Sometimes the meanings of the concepts that lie behind social science concepts are immediately clear. Other times they aren't. This point is discussed in the box "The Hardest Hit Was..." The relationship between attributes and variables is more complicated in the case of explanation '(.«imiiuVtjnmoľixialScience . 31 30 . Quptttl: HurwninauirríndSnencr The Hardest Hit Was.« In early 1982.a deadly storm ravaged the San Francisco Bay Area, leaving an after math of death, injury, and property damage. As the mass media sought to highlight the most tragic results of the storm, they sometimes focused on several people who were buried alive in a mud slide in Santa Cruz. Other times, they covered the plight of the 2,900 made homeless in Marin County. Implicitly, everyone wanted to know where the worst damage was done, but the answer was not clear. Here are some data describing the results of the storm in two counties: Marin and Santa Cruz. Look over the comparisons and see if you can determine which county was "hardest hit." •cr.nC';: Businesses destroyed S15-0 million $56i million 'eople killed 5 22 ?eople injured 379 % People displaced 370 -CO Homes destroyed ZS 135 Homes damaged 2.900 ;:o Businesses destroyed 25 N Businesses damaoed 800 35 Private damages $65.1 m«ion $50.0 million Public damages $55.0 million $56-5 million Certainly, in terms of the loss of life. Santa Cruz was the "hardest hit" of the two counties, Yet more than seven times as many people were injured in Marin as in Santa Cruz: certainly, Marin County was "hardest hit*in that regard. Or consider the number of homes destroyed (worse in Santa Cruz) or damaged [worse in Marin): It matters which you focus on.The same dilemma holds true for the value of the damage done: Should we pay more attention to private damage or public damage? So which county was "hardest hit'? Ultimately, the question as posed has no answer. While you and I both have images In our minds about communities that are"devas-tated"or communities that are only "lightly touched," these images are not precise enough to permit rigorous measurements. The question can be answered only if we can specify what we mean by "hardest hit." If we measure it by death toll, then Santa Cruz was the hardest hit. If we choose to define the variable in terms of people injured and/ or displaced, then Marin was the bigger disaster The simple fact is that we cannot answer the question without specifying exactly what we mean by the term hardest hit This is a fundamental requirement that will arise again and again as we attempt to measure social science variables. DMfMftrSat Ana's» Utmtíe Jimmy 13.1983. a 16. and gets to the heart ol ihc variable language ol scientific theory. Here's a simple example, involving two variables, education and prejudice For the sake of simplicity, let's assume that the variable education has only two attributes: educated and uneducated. Similarly, let's give the variable prejudice two attributes: prejudiced and unprejudiced. Now let's suppose that 90 percent of the uneducated are prejudiced, and the other 10 percent arc unprejudiced. And lei's suppose that 30 percent of ihc educated people are prejudiced, and 'he other 70 percent are unprejudiced. Thb is illustrated graphically in Figure 1-5A. Figure 1-5A illustrates a relationship or association between the variables educaacn and prejudice This relationship can be seen !n terms of the pairings oi attributes on the two variables. There are [wo predominant pairings: 11) those who are edu- thrloun&ttionicrf$o«ulS* 1*1*1 Vl Jnp->;jdiť::I I B. There Is no apparent relationship wtween educator and prejudic« Educaľ , Uneducated Prejudiced Unprejudiced catcd and unprejudiced and (2> those who are uneducated and prejudiced. Here arc two other useful ways ol viewing that relationship. First, let's suppose that we pUy a game in which we bet on your ability to guess whether a person is prejudiced or unprejudiced. I'll pidc the people one at a rime (not telling you which ones I've picked), and you have to guess whether each person is prejudiced. We'll do It for all 20 people in Figure 1-5A Vour best strategy in this case would be to guess prejudiced each time, since 12 out of the 20 are categorized that way. Thus, you'll get 12 righi and 8 wrong, for a net success of 4. Now let's suppose that when I pick a person from the figure. I have to tell you whetlier the per- son 1«. educated or uneducated. Your best strategy now would be to guess prejudiced for each uneducated person and unprejudiced lor each educated person. If you followed that strategy, you'd get 16 right and 4 wrong. Your improvement in guessing prejudice by knowing education is an illustration of what it means to say that ihe enables arc related. Second, by contrast. let's consider how the 20 people would be distributed if education and prejudice were unrelated to one another. This is illustrated in Figure 1 -58. Noiice that half the people arc educated, and half are uneducated. Also notice thai 12 of the 20 (60 percent) are prejudiced. H 6 ol the 10 people in each group were prejudiced, we would condude that the two variables were 32 • ChapWf 1: Human Inquiry and Seen« unrelated 10 each other. Then knowing a person's education would not be of any value to you in guessing whether that person was prejudiced. we'll be looking at the nature of relationships between variables in some depth in Pan 4. In particular, we'll explore some of the ways relationships can be discovered and interpreted in research analysis. For now, though, a general understanding of relationships is important so thai you can appreciate the logic of social scientific theories. Theories describe the relationships we might logically expect between variables. Often, the expectation involves the idea of causation. That is. a person's attributes on one variable are expected to cause, predispose, or encourage a particular attribute on another variable. In the example just illustrated, we might theorize that a person's bring educated or uneducated causes a lesser or greater likelihood ol that person seeming prejudiced. As I'll discuss in more detail later in the book, education and prejudice in this example would be regarded as independent variables and depended variables, respectively. These two concepts are Implicit in causal, or deterministic models- In this example, we assume that the likelihood of being prejudiced is determined or caused by something. In other words, prejudice depends on something else, and so it is called the dependent variable. What the dependent variable depends on is an independent variable. In this case, education. For the purposes of this study, education is an 'independent" variable because it is independent ol prejudice f that is, people's level of education is not caused by whether or not they are prejudiced). Of course, variations in levels of education can. in tum, be found to depend on something else. PeOp'e whose parents have a lot ol education, for example, arc more likely to gel a lot of education than are people whose parents have little education. In this relationship, the subjects education is the dependent variable, and the parents' education is the independent variable. We can say the independent variable is the cause, the dependent variable the effect. Returning to our first example, the discussion of Figure I -5 has involved the interpretation of data- We looked at the distribution ol the 20 people in terms ol the two variables. In constructing a social scientific theory, we would derive in expectation regarding the relationship between the two variables based on what we know about each. We know, for example, that education exposes people to a wide range of culture variation and to diverse points of view—in short, it broadens their perspectives. Prejudice, on the other hand, represents a narrower perspective. Logically, then, we might ex-pect education and prejudice to be somewhat incompatible. We. might therefore arrive at an expectation that increasing education would reduce the occurrence of prejudice, an expectation that would be supported by our observations. Since Figure 1-5 has illustrated two possibilities—that education reduces the likelihood ol prejudice or that it has no effect—you might be interested in knowing what is actually the case. As one measure of prejudice, the 1996 General Social Survey asked a national sample of adults in the United States how they felt about the opinion. -White people have a right to keep Blacks out of their neighborhoods if they want to and Blacks should respect that right/ Only 6 percent of the sample agreed strongly with the statement, with another 5 percent agreeing slightly. The majority—71 per-cent—strongly disagreed- Table 1-2 presents an analysis of those data, grouping respondents according to their levels of educational attainment. The easiest way to read this table is to locus on the last line ol percentages: those disagreeing strongly with the statement. Strong opposition to segregation increases steadily from 62 percent among those who had completed high school (or less) to 85 percent among college graduates. This finding dearly supports the view thai education reduces prejudice, as prejudice was measured in this study. Notice that the thenry has to do with the two variables education and prejudice, not with people as such. People are the carriers of those two variables, so the relationship between the variables can only be seen when we observe people. Ultimately, however, the theory uses a language of variables. It describes the associations that we might logically expect to exist between particular attributes of dif-fere n i variables. SflmfOialKtio of Social Rtfemh . 33 TABLE 1-2 Education and Support for Segregation rüuraftviaf Lent ctfteyatfenit lea [baa Some r'A'jf HSCmOuaie HSGiQůusie G/oduoie Agree strongly 10% 7% 6% 1% Agree sligfitly 8 5 S 4 Disagree slightly 9 26 IE '0 li'.iirPfritT/Ki)' 62 -.; 70 :;- 100% ■• (98) ■ 6Í\ (190) (1931 Some Dialectics of Social Research There is no one way to do social research. (II there were, this would be a much shorter book.) In fact, much of the pow-er and potential ol social research lies in the many valid approaches il comprises. Three broad and interrelated distinctions, however, underlie the variety ol research approaches. Although these distinctions can be seen as competing choices, a good social researcher learns each of these orientations. This Is wltat ■ mean by the 'dialectics'' of social research: There is a Iruitlul tension between the complementary concepts I'm about to describe. Idiographic and Nomothetic Explanation All of us go through life explaining things. We do it every day. You explain why you did poorly or well on an exam, why your favorite team is winning or losing, why you may be having trouble getting good dates or a decent job. In our everyday explanations, we engage in two distinct forms of causal reasoning, though we do not ordinarily distinguish them. Sometimes we attempt to explain a single situation exhaustively. Thus, lor example, you may have done poorly on an exam because 11) you had forgotten there was an exam thai day. |2) it was in your worst subject. (i) a traffic jam made you late lor class. |4) your roommate kept you up the nighl before the exam by playing loud music, (5) the police kept you until dawn demanding to know what you had done with your roommate's stereo—and what you had done with your roommate, lor that matter—and (61 a wild band of coyotes ate your textbook. Given all these circumstances, it's no wonder you did poorly. This type o' causal reasoning is called an idiographic explanation. Idio- in this context means unique, separate, peculiar, or distinct, as in the word idiosyncrasy, when we have completed an idiographic explanation, we feel that we fully understand the causes ol what happened in this particular instance- At the same time, the scope of our explanation is limited to the single case at hand. While parts of the idiographic explanation might apply to other situations, our intention is to explain one case fully. Now consider a different kind of explanation. (1) Every lime you study with a group, you do better on the exam than il you study alone. (2) Your favorite team does better at home than on the road. (3) Fraternity and sorority members get more dates than do members of the biology dub. This type of explanation—labeled nomothetic—seeks to explain a class of Situations or events rather than a single one. Moreover, it seeks to explain "economically," using only one or just a few explanatory lac-tors. Finally, it settles for a partial rather than a full explanation. In each of these examples, you might qualify your causal statements with such words or phrases 34 . a understanding. Social scientists, though- can access two distinct kinds of explanation. Just as physicists treat light sometimes as a panicle and other times as a wave. so social scientists can search for broad relationships today and probe the narrowly particular tomorrow Both are good science, both are rewarding, and both can be fun. Inductive and Deductive Theory Like idiographic and nomothetic forms of explanation. Inductive and deductive thinking both play a rote in our daily lives. They. too. represent an important variation in social research. Thete are two routes to the conclusion that you do better on exams if you study with others. On the one hand, you might find yourself puzzling, halfway through your college career, why you do so well on exams sometimes but poorly at other times. You might list all the exams you've taken, noting how well you did on each. Then you might try to recall any circumstances shared by all the good exams and by all the poor ones. Did you do beitcr on multiple-choice exams or essay exams' Morning exams or afternoon exams? Exams in the natural sciences, the humanities, or the social sciences? Times when you studied alone or... SHAZAM! Ii occurs to you thai you have almost always done best on exams when you studied with others. This mode of inquiry is known as induction. Inductive reasoning, or induction, moves from the particular lo the generaL Írom a set of specific observations w the discovery ol a panem that represenis some degree of order among all the given events. Notice, incidentally, that your diseov- SdM DWKtKSSfSoa.il ř.r-"a>ci - 35 FIGURE 1-6 The Wheel of Sciente.The theory and research cycle can be compared to a relay rare." although all participants do not necessarily stan or stop at the same point, they share a common goal—to examine all levels of social life. Ge->e*alizalons 'Theories- Qbservai'ons- Hypotheses £ SomUipMlmV^«ilii%lfeiiytŕSGmYBJtai^ ery doesnl necessarily tell you why the pattern exists—just ihat iidoes. There is a second and a very different w»y that you might arrive at the same conclusion about studying for exams. Imagine approaching your first set of exams in college. You wonder about the best ways to study—how much you should review the readings, how much you should locus on your class notes. You learn that some students prepare by rewriting their notes in an orderly lashion. Then you consider wheiher you should study at a measured pace or else pull an all-nighter just before the exam. Among these kinds of musings, you might ask whether you should get together with other students in the class or just study on your own. You could evaluate the pros and cons of both options. Studying with others might not be as efficient, because a lot of time might be spent on things you already understand. On the other hand, you can understand something even better when you've explained it to someone else. And other students might understand pans of the course that you havcn'i gotten yet. Several minds can reveal perspectives that might have escaped you. Also, your commitment to study with others makes ii more likely that you'll study rather than waieh the special Brady Bunch retrospective. in this fashion, you might add up the pros and the cons and conclude, logically, that you'd benefit from studying with others. It seems reasonable lo you, the way it seems reasonable that you'll do better if you study rather than not. Sometimes, we say things like this are true "in theory." To complete the process, wc test wheiher they are true in practice. For a complete test, you might study alone for hall your exams and study with others lor the other exams. This procedure would test your logical reasoning. This second mode of inquiry, known as deductive reasoning Of deduction, moves Irom the general to the specific. It moves from (11 a pattern that might be logically or theoreucally expected to i2) observations that test whether the expected pattern actually occurs. Notice that deduction begins with "why" and moves to "whether," while induction moves ill the opposite direction. These two very dilferent approaches arc both valid avenues for science. Moreover, they frequently work together to provide ever more powerful and complete understandings, as pictured in Figure 1-6. Notice, by the way. thai the distinction between deductive and inductive reasoning is not necessarily linked to the distinction between nomothetic and idiographic modes of explanation. These four characterizations represent (our possibilities, in everyday life as much as in social research. For example, idjographically and deductively, you might prepare for a panicular date by taking into account everything you know about the person 3Ů . Chapter 1: Human toquiri and Science you're dating, trying to anticipate logically how you can prepare—what kinds of doihing, behavior, hairstyle, oral hygiene- and so forth ate likely to produce a successful date. Or. idiographically and inductively, you might try to figure out what it was exactly that caused your date to call 911. A nomothetic, deductive approach arises when you coach others on your "rules of dating.* when you wisely explain why their dates will be impressed to hear them expound on the dangers of satanic messages concealed in rock and roll lyrics. When you later review your life and wonder why you didn't date more musicians, you might engage in nomothetic induction. we'll return to induction and deduction in Chapter 2. Lets turn now to a third broad distinction that generates rich variations In social research. Qualitative and Quantitative Data The distinction between quantitative and qualitative data w social research is essentially ihc distinction between numerical and nonnumcrical data, when we say someone is intelligent, we've made a qualitative assertion. A corresponding assertion about someone less fortunately endowed would be that he or she is "unintelligent." When psychologists and others measure intelligence by IQ scores, they are attempting io quantify such qualitative assessments. For example, the psychologist might say-that a person has an IQ of 120. Every observation is qualitative at the outset, whether it is our experience of someone* intelligence, the location of a pointer on a measuring scale, or a check mark entered in a questionnaire. None of these things is inherently numerical or quantitative, but sometimes it is useful to convert them to a numerical form. Quantification often makes our observations more explicit. It also can make it easier to aggregate, compare, and summarize data. Further, it opens up the possibility of statistical analyses, ranging from simple averages to complex formulas and mathematical models. Quantitative data, thea have the advantages that numbers have over words as measures of some quality. On the other hand, they also have the dis- advantages that numbers have, including a potential loss in richness of meaning. For example, a social researcher might want to know whether college students aged 18-22 tend to dale people older or younger than themselves. A quantitative answer to this question seems easily attained. The researcher asks a number of college studeníš how old each of their dales has been, calculates an average, and compares it with the age of the subject. Case Or is il? while 'age" here represents the number of years people have been alive, sometimes people use the term differently; perhaps for some "age" really means 'maturity." Though your dales may tend to be younger than you, you may date people who act more maturely and thus represent the same "age." Or someone might sec "age* as how young or old your dates look or maybe the degree of variation in their life experiences and worldlincss- These latter meanings would be losí in the quantitative calculation of average age. Qualitative data, in short, can be richer in meaning than quantified data. This is implicit in the cliche. "He Is older than his years." The poetic meaning of this expression would be lost in attempts to specify how much older. On the other hand, qualitative data can have the disadvantages of purely verbal descriptions. For example, the richness of meaning I've mentioned is partly a function of ambiguity. If the expression "older than his years" meant something to tou when you read it, that meaning arises from your own experiences- from people you have known who might fit the description of being "older than their years" or perhaps the times tou have heard others use that expression. Two things are certain: (I) You and ! probably don't mean exactly the same thing, and (2) you don't know exactly what I mean, and vice versa. I have a young Iriend. Ray Zhang, who was responsible for communications at the 1989 freedom demonstrations in Tiananmen Square. Beijing. Following the Army dampdown. Ray lied south, was arrested, and was then released with orders to return to Beijing. Instead, he escaped from China and made his way to Paris. Eventually he came to the United Slates, where he resumed the graduate ThfEthksofSooalBesfiith - 37 studies he had been forced to abandon in fleeing his homeland. 1 have seen him deal with the difficulties of getting enrolled in school without any transcripts from China, studying in a foreign language, meeting his financial needs—all on his own. thousands of miles from his family. Ray still speaks of one day returning io China io build a system of democracy. Ray strikes me as someone "older than his years." You probably agree. The additional detail in my qualitative description, while it fleshes oui ihe meaning of the phrase, still docs not equip us to say how much older or even to compare two people in these terms without the risk of disagreeing as to which one is more "worldly." It might be possible to quantify this concept, however. For example, we might establish a list of life experiences thai would contribute to what we mean by worldlincss. for example; Getting married Getting divorced Having a parent die Seeing a murder committed Being arrested Being exiled Being fired from a job Running away with the circus We might quantify people's woridlincss as the number of such experiences they've had: the more such experiences, the more worldly we'd say ihcy were. If we thought of some experiences as more powerful than others, we could give those expert-enecs more points. Once we had made our list and point system, scoring people and comparing their worldlincss on a numerical scale would be straightforward. We would have no difficulty agreeing on who had more points than whom. To quantify a nonnumcrical concept like world-liness. then, we need to be explicit about what the concept means. By focusing specifically on what we will indude in our measurement of the concept, however, we also exclude any other meanings. Inevitably, ihcn. we face a trade-off: Any explicated, quantitative measure will be less rich in meaning than the corresponding qualitative description. What a dilemma! Which approach should we choose? Which is better:- which is more appropriate to soda! research? The good news is that we don't need to choose. In fact, we shouldn't. Both qualitative and quantitative methods are useful and legitimate in social research. Some research situations and topics are most amenable to qualitative examination, others to quantification. while researchers may use both, these two approaches call for different skills and procedures. As a result, you may find that you feel more comfortable with—and become more adept in—one or the other. You will be a stronger researcher, however, :o the extent that you can use both approaches effectively. Certainly, all researchers, whatever their personal inclinations, should recognize the legitimacy of both. You may have noticed that the qualitative approach seems more aligned with idiographic explanations, while nomothetic explanations arc more easily achieved through quantification. Although this is true, these relationships are not absolute. Moreover, both approaches present considerable "gray area." Recognizing the distinction between qualitative and quantitative research doesn't mean dial you must identify your research activities witli on<: to the exdusion of the other. A complete understanding of a topic oficn requires both techniques. The Ethics of Social Research Most of this book is devoicd io the logic and skills ol doing sodal research, the various icchniques preferred by sodal researchers, and the reasons why researchers value them. There are. however, some vital nonsoentific concerns that shape the activities of social researchers. A key concern is ihe matter of ethics in research. Chapter 18 of this book deals extensively with research ethics, and other chapters will refer to ethical issues as appropriate. Here. I want io introduce two basic ethical issues to keep in mind as you read the rest of this book.