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Lecture 3

Week 3 Babbie.docx

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University of British Columbia
SOCI 217
Amin Ghaziani

Week 3 Babbie. Chapter 4: Research Design and the Logic of Causation Three Purposes of Research 1) Exploration (New interest, further research) - To explore a topic, to familiarize researcher with that topic typically when it is either NEW or NEW INTEREST - Appropriate for more persistent phenomena - Methodology: focus groups, guided small group discussions - 3 purposes: 1) to satisfy the researcher’s curiosity and desire for better understanding, 2) to test the feasibility of undertaking a more extensive study, 3) to develop methods to be employed in any subsequent study - Problem: representatitveness: the people studied may not represent the general population 2) Description (wide variety of characteristics, computation) - To describe situations and events observed - Example of descriptive social research: Canadian census  Goal: to describe accurately and precisely a wide variety of characteristics of the Canadian population, as well as the population of smaller are - The data will mostly involve computation without actually seeking to explain 3) Explanation (why) - To explain things (what, where, when, how) - Distinguishing between Explanation, Descriptive, and Exploration  Descriptive : reporting the voting intentions of an electorate  Explanation : reporting why some people plan to vote Candidate A and others for Candidate B  Descriptive : reporting the crime rates of different cities  Explanatory : identifying variables that explain why some cities have higher crime rates than others  Explanatory : why an anti-abortion demonstration ended in a violent confrontation The Logic of Causation - Causation in Idiographic and Nomothetic Models of Explanation  Idiographic: explaining one event by considering many factors  Nomothetic: discover those considerations that are most important. Aims to provide a the greatest amount of explanation with the fewest number of causal variables to uncover general patterns of cause and effect. E.g: which variables had the strongest impact on university satisfaction - Criteria for Nomothetic Causality 1) Correlation – when x occurs or changes, y also changes 2) Time order –cause precedes the effect in time 3) Nonspurious relationship – the observed empirical correlation between two variables cannot be explained in terms of some third variable. E.g: when the selling of ice cream increases, the rate of drowning increases.  this factor can be pointed by the fact that it’s summer and it’s hot. So, people go swimming - False Criteria for Nomothetic Causality  Complete Causation: identifying whether the cause is the only one or one of many  Exceptional Cases: some rare cases don’t disconfirm the causal pattern of a research result  Majority of Cases: causal relationships can be true even if they don’t apply in a majority of cases. Have to compare the likeliness for x to occur if y is/is not done  Necessary and Sufficient Cases: necessary  a condition that must be present. Sufficient  doing x doesn’t guarantee you to get y. You may have to do z Sufficient simply means: if you do z you will get the result. E.g: Being female is a necessary condition to get pregnant but it’s not sufficient because you will have to have intercourse or do IVF etc. A sufficient cause is not the only possible cause of a particular effect. A cause can be sufficient but not necessary. Units of Analysis - Important to distinguish between units of analysis and the aggregate that we generalize about. What we want to generalize ≠what we study to arrive to that generalization - Unit of analysis (units of observation – but their relationships are not simultaneous; they are indirect): the specific observation you make and the kind of behavior that you want observe. E.g: A researcher observes 10 different groups of individuals with different backgrounds with the aim to see how the individuals interact individually, then the unit of analysis is individual  Unit of analysis: things we examine in order to create summary description  Sometimes units of analysis are clearly stated. Sometimes, they can be identified from the description of the sampling methods or the research design - Individuals  Typical unit of analysis  Usually, researchers describe and explain social groups by aggregating and analyzing the description of individuals - Groups  Usually interested to know about characteristics that belong to a group. E.g: if want to study criminals by studying members of a criminal gang, the UoA is individual but if want to distinguish between small gang and big gang in different cities, the UoA is group - Organizations: corporations or church, universities, supermarkets etc - Social artifact:  Any product of social beings or their behavior. E.g: books, poems, paintings, automobiles, buildings, songs, pottery , jokes, student excuses for missing exams and scientific discoveries  Social interactions are also considered social artifact. e.g: friendship choices, court cases, traffic accidents, divorce fistfights, ship launching, airline hijackings, race riots and student demonstration. - Faulty Reasoning about UoA: The Ecological Fallacy (Group imposes on Individual)  Ecological refers to groups or sets or systems: something larger than individuals  It’s about a false assumption about an individual that is drawn from an observation on the masses  To correct this fallacy, should conduct at individual and group level. Then only conclusions can be made  This kind of fallacy usually occurs when there isn’t enough data available. The possible data that can be made is correlation BUT NOT causation - Faulty Reasoning about UoA: The Individualistic Fallacy (Indivi. Imposes on Group)  A fact that you observe based on an individual doesn’t invalidate generalizations and probabilistic statement. E.g: Your friend gets rich without a formal education. This exceptional factor doesn’t mean that it is always true that you don’t have to get education in order to be rich The Time Dimension - Cross-sectional Studies  Exploratory and descriptive studies are often cross-sectional  Involves studying a sample/population/phenomenon concerning one point in time  Cross section: a study done by studying a larger group at a period of time  Problem: the data will most likely be relevant at that period of time and not to others  Imagine taking a ‘still photo’  this is how cross sectional works - Longitudinal Studies  Permits observations of the same phenomena over an extended period of time  Basically, if you want to see the changes over time, longitudinal is the best one  Methodology: study a group in a very long period of time or use records or artifacts to study change over time - Three Types of Longitudinal Studies: 1) Trend Studies: examines changes within a population over time. Observe trend  Example: compares Canada censuses over time, shifts in the makeup of the national population 2) Cohort Studies : when researchers examine specific subpopulations or cohorts as they change over time  Example: age group  studying the economic attitudes of the cohort born during the Great Depression 3) Panel Study: studies the same set of people each time  this allows us to study the precise patterns of persistence and change in intentions - Comparison of the Three Types of Longitudinal Studies  Demonstration: Example: Attitudes toward abortion  Cohort: might follow shifts in attitudes among the WWII generation  Trend: shifts in attitudes of the general Canadian population by using polling data collected on a regular basis  Panel: Subset of population and study those specific person over time. Problem: some of the respondents may not partic
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