Chapter 2: Process and Problems of Social Research Question? Strategy? Theory? Design? Ethical? The text presents this information in a slightly different order. The type of research question will determine the research strategy, deductive, inductive or descriptive, whether or not you will be testing a theory, and if your study is a cross-sectional or longitudinal design.

The Question Do mandatory arrest policies decrease domestic violence recidivism? Does how much a person loves his or her dating partner influence the frequency of lying? What factors influence men’s and women’s level of retirement income? From Text: Beginning in 1981, The Police Foundation and the Minneapolis Police Department began an experiment to find the answer. The Minneapolis experiment was first and foremost scientifically relevant: it built on a substantial body of contradictory theorizing about the impact of punishment on criminality (Sherman & Berk, 1984).

What Makes a Question “Good”? 1. Feasibility Resources Time From Text: Many social scientists evaluate their research questions in terms of three criteria: feasibility given the time and resources available, social importance, and scientific relevance (King, Keohane, & Verba, 1994):

2. Social Importance Make a difference Help understanding

3. Scientific Relevance Resolve contradictory research findings Modify social theory? *

Deductive, Inductive, or Descriptive? The Strategy The Circle of Science includes the following components: Theory A logically interrelated set of propositions about empirical reality. Hypothesis A tentative statement about empirical reality, involving a relationship between two or more variables. Variable A characteristic or property that can vary (take on different values or attributes). Independent variable A variable that is hypothesized to cause, or lead to, variation in another variable. Dependent variable A variable that is hypothesized to vary depending on or under the influence of another variable. Data include the systematically gathered evidence. Science requires evidence to be obtained empirically—through the senses. In the social sciences this usually means through “hearing” respondents’ answers to survey or interview questions or through “observing” behavior or artifacts. Empirical generalizations are the organized patterns we observe in the data. We formulate these generalizations through analyses, qualitative or quantitative. Deductive, Inductive, or Descriptive?

Strategy #1: Deductive Research Deductive research starts with a theory and deduces a specific expectation. From text: deductive research starts with a theoretical premise and deduces a specific expectation.

Strategy #2: Inductive Research Inductive Research starts with data. From Text: In contrast to deductive research, inductive research begins with specific data, which are then used to develop (“induce”) a theory to account for the data. One way to think of this process is in terms of the research circle: rather than starting at the top of the circle with a theory, the researcher starts at the bottom of the circle with data and then develops the theory.

Inductive Research If police noticed that arresting at least one person from the scene of a domestic violence case resulted in fewer subsequent calls to that same scene, The police officers might develop a theory that mandatory arrests decrease domestic violence recidivism. * Using the inductive research strategy to understand the effects of mandatory arrests would require us to start with data already collected on this phenomenon.

Strategy #3: Descriptive Research Descriptive research starts with data and proceeds only to making generalizations, not generating entire theories. From Text: Both deductive and inductive research connect theory with data. Descriptive research by itself does not, but is still part of the research circle. As this graphic indicates, descriptive research starts with data and proceeds only to the stage of making empirical generalizations, not generating entire theories. Valid description is actually critical in all research. Much important research for the government and private organizations is primarily descriptive: How many poor people live in this community? Is the health of the elderly improving? How frequently do convicted criminals return to crime? Description of social phenomena can stimulate more ambitious deductive and inductive research. Simply put, good description of data is the cornerstone for the scientific research process and an essential component for understanding the social world.

Descriptive Research “How frequently do those arrested for domestic violence return to violence?” Description of social phenomena can stimulate more deductive and inductive research Good descriptions of data are the basis for scientific research process and An essential component for understanding the social world. * Here’s how a descriptive strategy might be applied with our example of mandatory arrests in domestic violence cases.

The Theory Social theory: A logically interrelated set of propositions about empirical reality (i.e., the social world as it exists) Theories and Research Make connections to: Social processes (reality) Large bodies of research Creating and evaluating theory Ask student to explain what a theory is. Then present this information.

Example of Theory

What Is the Design? Cross-sectional Longitudinal Once you’ve chosen a: Research question, Strategy, and Theory Decide on a research design Cross-sectional Longitudinal In addition to the question strategy and theory, a researcher has to decide on the design. Will you study a cross-section, a snapshot of the phenomenon of interest? Or will you observe changes over time?

Cross-Sectional Design Data collected at one point in time.

Cross-Sectional Design

Cross-Sectional Design Application To study the effects of mandatory arrests Take “cross-section” of all domestic violence cases and Examine whether arrests affected recidivism*

Strengths of Cross-Sectional Design Relatively quick and easy to conduct Data collected on different kinds of people in relatively short time. Good for descriptive analyses Good for generating hypotheses. Large samples enable use of inferential statistics (e.g. to compare subgroups within the sample).

Weaknesses of Cross-Sectional Design Difficult to establish time order Unable to chart individual variations in development or changes Unable to chart changing social processes over time.

Longitudinal Designs

Longitudinal Designs: The Panel Design A sample (called a panel) is drawn from a population at time 1, and data are collected from the sample (for instance, 100 arrestees from domestic violence cases are selected and interviewed). 2. Time passes, some panel members become unavailable for follow-up (move or refuse to continue participating). 3. At time 2, data are collected from the same people (the panel) as at time 1—except for people who cannot be located (the remaining arrestees are re-interviewed).

Weaknesses of Panel Designs Expense and Attrition Expensive to keep track of individuals for long periods of time Panel members who can be located declines over time. Subject fatigue Weary of repeated interviews and drop out Used to answering questions--Start giving stock answers Expensive and attrition - Miller 1991: 170 Subject fatigue – Campbell 1992

Longitudinal Designs: Repeated Cross-Sectional Design (Trend study) 1. A sample of domestic violence cases is drawn from a population of cases at time 1, and data are collected from the sample. 2. As time passes, some people leave the population and others enter it. 3. At time 2 a different sample of cases is drawn from this population.

Longitudinal Designs: A Cohort Study Cases in Cases in In a cohort study, the follow-up samples (at one or more times) are selected from the same cohort— Cohort: People who have experienced a similar event or a common starting point (Example: Baby Boomers, Gen-Xers) Finally, another design, the cohort study. A cohort From Text: Or the population may be defined narrowly, as when members of a specific age group are sampled at multiple points in time (a cohort study). The frequency of follow-up measurement can vary, ranging from a before-and-after design with just one ­follow-up to studies in which various indicators are measured every month for many years. Cohort:: Individuals or groups with a common starting point. Examples include college class of 1997, people who graduated from high school in the 1980s, General Motors employees who started work between 1990 and the year 2000, and people who were born in the late 1940s or the 1950s (the “baby boom generation”).

Example of a Cohort

Real-life Example Data collected from high school students from Baltimore, Maryland Studies the difference in initiation of tobacco use between a cohort of adolescents that started working for pay and a cohort of adolescents that did not work. The results suggest that adolescents who work for pay have a higher risk of initiating tobacco use. Ramchand, R., Ialongo, N. S., & Chilcoat, H. D. (2007). The effect of working for pay on adolescent tobacco use. American Journal of Public Health, 97(11), 2056-2062.

Unit of Analysis Major entity you are analyzing in study. Any of the following could be a unit of analysis: Individuals Groups Artifacts (books, photos, newspapers) Geographical units (town, census tract, state) Social interactions (dyadic relations, divorces, arrests)

Units of Analysis and the Domestic Violence Example Cases = individual arrests Cases =precincts Precinct #1 Precinct #2 Precinct #3 From Text: There is one final concept you need to understand in planning the overall design of your project: “the unit of analysis.” Most sociological and psychological studies gather data from, and formulate conclusions about, individuals—so individuals are called the units of analysis. The researcher may collect survey data from individuals, analyze the data, and then report on, say, how many individuals felt socially isolated and whether drug abuse by individuals was related to their feelings of social isolation. Both data and conclusions would be about individuals, not groups. One could also then generalize about individuals; for example, perhaps you find that women are less likely to be isolated than men. The finding talks about many people (women vs. men), but still points to a phenomenon occurring within individuals—that is, that individual women are less likely to be isolated then individual men. Individuals remain the unit of analysis. But some research gathers data about groups of some sort, such as families, schools, work organizations, towns, states, or countries. In this case, groups are the units of analysis. One may find, for instance, that smaller high schools have lower levels of student violence than large schools. In this case, the finding is not about students, but about certain kinds of schools. Here, the organization, not the individual, is the unit of analysis. It’s important to recognize your units of analysis, in order to avoid logical errors in your analysis. In Chapter 5, we’ll discuss the logical errors that can result when we use aggregate data Individuals as Unit of Analysis Groups as Unit of Analysis

Two Research Fallacies A fallacy is an error in reasoning Ecological fallacy occurs when you make conclusions about individuals based only on analyses of group data. You measured math scores of a class and found that they had the highest average score in the district. Later you meet one of the kids from that class and you think "she must be a math genius.” Fallacy! Just because she comes from the class with the highest average doesn't mean that she does well in math. She could be the lowest math scorer in a class that otherwise consists of math geniuses!

Two Research Fallacies An Exception fallacy is sort of the reverse of the ecological fallacy. Occurs when you reach a group conclusion on the basis of exceptional cases. This fallacious reasoning is at the core of a lot of sexism and racism (stereotypes). The man who sees a woman make a driving error and concludes that "women are terrible drivers. Fallacy!

Errors in Reasoning

Ethical Considerations Honesty and Openness Should not conceal motives to subject Full disclosure of researcher identity The Uses of Science How will findings be used? Who controls final report? Who controls publicity? Confidentiality Informed consent agreement Identifying information is available only to designated research personnel for specific research needs Institutional Review Board (IRB) Federally funded research

Conclusion: The Process of Researching the Effects of Mandatory Arrests

For Your Own Research… Contemplate: the question, the strategy, the theory, the design, and the ethics of the project.

Populations and Samples