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Chapter 1 Approaches to Methods

Chapter 1 Approaches to Methods. Winston Jackson and Norine Verberg Methods: Doing Social Research, 4e. Key Methodological Approaches. The positivist approach Research is a tool for uncovering general laws of cause and effect in social behaviour The interpretive approach

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Chapter 1 Approaches to Methods

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  1. Chapter 1Approaches to Methods Winston Jackson and Norine Verberg Methods: Doing Social Research, 4e

  2. Key Methodological Approaches The positivist approach • Research is a tool for uncovering general laws of cause and effect in social behaviour The interpretive approach • Research is a tool for understanding the reality experienced by people The critical approach • Research is a tool that should be used to improve the conditions of the oppression © 2007 Pearson Education Canada

  3. Positivist Approach • Auguste Comte (1798-1857) • Use natural science model to study social regularities • Emile Durkheim (1858-1917) • Social facts: “ways of acting, thinking, feeling, external to the individual” • Focus on patterns • e.g., the “fact” that males are four times more likely to commit suicide is a social pattern • Social facts cannot be explained by individual psychology © 2007 Pearson Education Canada

  4. Characteristics of Positivist Approach • Predominantly quantitative • “Number crunchers” • Advocate an “objective” approach • Remove individual opinion/bias • Emphasis on having reliable knowledge of social relations; can make predictions • Based on consistent empirical results © 2007 Pearson Education Canada

  5. Positivism: Assumptions • All behaviour is naturally determined • Humans are part of the natural world • Nature is orderly and regular • All objective phenomena are eventually knowable • Nothing is self-evident • Truth is relative • Knowledge comes from experience © 2007 Pearson Education Canada

  6. Positivism: Role of Values in Research • Should be value-free • Put personal preferences aside • Test alternative explanations © 2007 Pearson Education Canada

  7. Positivism: Research Designs • Quantitative methods of data collection • Social variables assigned numbers • Illustrate social patterns using statistical terms • E.g., average income, fertility rate, divorce rate • Predict the relationship among variables • Females more likely to be a nurse than males; males more likely be engage in high risk behaviour • Common methods of data collection • Experiments, surveys, secondary data analysis © 2007 Pearson Education Canada

  8. Criticisms of Positivism • Value-free goal is unattainable • Bias can enter research (e.g., racism, sexism) • Conservative bias in social research • research supports the status quo • Subjective element missed – how people experience and shape the social world © 2007 Pearson Education Canada

  9. Interpretive Approach • Max Weber (1864-1920) placed importance on people’s understanding of their actions • To understand social patterns requires empathetic or interpretative understanding —Verstehen • Key figures: Mead, Goffman, Becker, Glaser and Strauss • Emphasis on how people make sense of their lives and how their sense of self develops in interaction with others © 2007 Pearson Education Canada

  10. Interpretative Approach: Assumptions • Reject the positivist notion that people are completely shaped by social factors • Assumes behaviour is influenced by the meanings people attach to events and actions • Schools: symbolic interactionism, ethnography, and grounded theory © 2007 Pearson Education Canada

  11. Interpretative Approach: Role of Values • Values should be relative • What constitutes appropriate or inappropriate behaviour depends upon socialization and may shift over time and across cultures and societies • Researchers should try to understand and explain the values of cultural actors • No place for judging behaviour and people’s beliefs © 2007 Pearson Education Canada

  12. Interpretive Approach: Research Designs • Data collection and data analysis are cyclical, connected activities (see Chapter 6) • Typical methods of data collection • Participant observation • In-depth interviews • Focus groups • Typical methods of data analysis • Ethnographic analysis • Grounded theory (constant comparison method) © 2007 Pearson Education Canada

  13. Criticisms of the Interpretive Approach • Positivists reject the goals and assumptions of the interpretative approach • Over-emphasis on subjectivity • Replication problem • Knowing more and more about less and less © 2007 Pearson Education Canada

  14. Critical Approach • Karl Marx (1818-1883): social relations are rooted in the struggle between owners and workers • Advocated equality • Conflict schools: conflict perspective, critical theory, Marxism, feminism • Share a belief that oppressive relations are rooted in power struggles and that social change can bring about equality © 2007 Pearson Education Canada

  15. Critical Approach: Assumptions • Powerful groups attempt to enhance their interests at the expense of less powerful groups • Emphasis on conflicting interests • e.g., Marxism: owner/worker relations • e.g., Feminism: male/female relations • Research should expose oppressive relations and promote empowerment of oppressed groups © 2007 Pearson Education Canada

  16. Critical Approach: Role of Values • Moral absolutes: some issues such as social justice or equality are not negotiable. • Research only judged to be valid if it leads to an improvement in condition of humanity. © 2007 Pearson Education Canada

  17. Critical Approach: Research Methods • Use a broad range of methods • Historical method • Comparative method • Secondary analysis of existing data • Emphasize macrovariables (i.e., properties of societies) © 2007 Pearson Education Canada

  18. Criticisms of the Critical Approach • Absolute moral values deemed unscientific • Tendency to report desired outcomes only • Do not try to disprove critical assumptions © 2007 Pearson Education Canada

  19. Some Important Distinctions • Quantitative versus qualitative research • Descriptive versus explanatory research • Pure versus applied research • Units of analysis: individuals/aggregations © 2007 Pearson Education Canada

  20. Quantitative Versus Qualitative Quantitative Research • Use numbers, statistics, emphasis on measurement, precision, prediction Qualitative Research • Emphasis on verbal descriptions • Reflect the world as seen by the participant • Focus on the “lived experience” of participant • Use word-for-word quotations when reporting findings • Typically employs small samples © 2007 Pearson Education Canada

  21. Descriptive Versus Explanatory Descriptive: goal is to describe some aspect of society • Census - description of entire population • Sample - a small portion of the population who are selected to represent the population • E.g., what are the differences between females enrolled in traditional vs. nontraditional programs Explanatory: goal is to explain relationships • E.g., why is it that females who select gender non-traditional careers come from higher socioeconomic backgrounds • Test alternative explanations © 2007 Pearson Education Canada

  22. Pure Versus Applied Research Pure Research: tries to produce an understanding of patterns of social behavior Applied Research: tries to solve a problem or bring about certain changes in society © 2007 Pearson Education Canada

  23. Units of Analysis Individual level: data that describe the attitudes or characteristics of individuals • More researchers employ individual level • E.g., explain variations in women’s length of hospitalization following childbirth Aggregate level: data that describe a characteristics of a group, community, or nation • Implies a grouping beyond the individual level • E.g., compare hospitals on average length of hospital stay for women following childbirth © 2007 Pearson Education Canada

  24. Types of Variables • Dependent variables • Independent variables (also called the treatment variable in experimental design) • Control variables • Intervening variables • Conditional variables • Source of spuriousness variables • Confounding variables © 2007 Pearson Education Canada

  25. Dependent Variable • The variable being “explained” • The “effect” in the cause/effect relationship • E.g., a study examining factors explaining why females choose gender-traditional versus non-traditional programs • Dependent variable: program of study • Indicated as the letter Y: X  Y © 2007 Pearson Education Canada

  26. Independent Variable • The “cause” in a cause-effect relationship • E.g., gender, age, socioeconomic status • Possible factors influencing preference for gender nontraditional program of study: • Urban/rural home community • Types of games/activities preferred in childhood • Parents’ socioeconomic status • Indicated as the letter X in a formal statement: X  Y © 2007 Pearson Education Canada

  27. Control Variables • A control variable is a variable taken into account when exploring the relation between an independent variable and a dependent variable • Goal: Control for the effects of other factors • Three types of control variables: • Intervening • Conditional • Source of spuriousness © 2007 Pearson Education Canada

  28. A. Intervening Variable • An intervening variable links an independent variable (X) to a dependent variable (Y) • Thus, a change in X causes a change in I, which in turn causes a change in Y. > X  > I  > Y • Example: Exposure to women who have non-traditional careers “intervenes” to explain why those of higher SES are more likely to choose nontraditional program of study © 2007 Pearson Education Canada

  29. B. Conditional Variable • A conditional variable is a variable that accounts for a change in the relationship between an independent (X) and dependent (Y) variable when general conditions change • Example: Investigate the relationship between socioeconomic status and attitudes toward capital punishment: • Want to find out if the pattern between X and Y is fundamentally altered (or is entirely different) for each gender © 2007 Pearson Education Canada

  30. Conditional Variable (cont’d) • Would test for males and females: do males and females have similar attitudes or are attitudes conditional upon one’s gender • Hence, gender would be the conditional variable • To graph a conditional variable model, present the relationships separately for the conditional variable Males Females X  Y X  Y © 2007 Pearson Education Canada

  31. C. Source of Spuriousness Variable • A source of spuriousness variable (S/S) is a variable that is viewed as having a possible influence on both the independent (X) and dependent (Y) variable, in such as way that it accounts for the relationship between them. • Called a confounding variable in experimental research — found to be systematically influencing the experiment’s outcome © 2007 Pearson Education Canada

  32. Source of Spuriousness (cont’d) • Example: When exploring the relationship between socioeconomic background and choice of nontraditional program by female students, consider the possibility that rural/urban background is the source of spuriousness. • Does coming from a urban vs. rural background influence parents’ socioeconomic status as well as university program preferences © 2007 Pearson Education Canada

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