chapter one: approaches to methods winston jackson and norine verberg methods: doing social...

Chapter One:Approaches to Methods

Winston Jackson and Norine Verberg

Methods: Doing Social Research, 4e

© 2007 Pearson Education Canada 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 oppressed


Positivist Approach

August Comte (1798-1857) Social sciences use same method as natural

sciences to understand social regularities Emile Durkheim (1858-1917)

Social facts: “ways of acting, thinking, feeling, external to the individual”

Focus on patterns: the fact that males are four times more likely to commit suicide in each province is a social pattern.

He argues that such societal patterns cannot be explained by individual psychology


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


Positivism: Assumptions

1. All behaviour is naturally determined

2. Humans are part of natural world

3. Nature is orderly and regular

4. All objective phenomena are eventually knowable

5. Nothing is self-evident

6. Truth is relative

7. Knowledge comes from experience (through senses)


Positivism: Role of Values in Research

Should be value-free Put personal preferences aside Test alternative explanations


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

Common methods of data collection Experiments, surveys, secondary data analysis


Criticisms of Positivism

Value free goal is unattainable Bias influences many decisions Social biases 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 Criticisms influence the development of

interpretative and critical designs


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


Interpretative Approach: Assumptions

Reject the positivist notion that people are completely shaped by social factors

Assume that behaviour is influenced by the meanings people attach to events and actions

Develop meaning through intersubjectivity Schools: symbolic interactionism, ethnography,

and grounded theory


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


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)


Criticisms of the Interpretive Approach

Positivists reject the goals and assumptions of the interpretative approach. Argue that: Over-emphasis on subjectivity Replication problem Knowing more and more about less and less


Critical Approach

Karl Marx (1818-1883) placed importance on understanding that social relations were rooted in the struggle over control of the means of production (owners vs workers) Believed that class conflict would eventually

lead to equality Several conflict approaches: conflict

perspective, Marxism, feminism Have in common a belief that oppressive

relations are rooted in power struggles and that social change can bring about equality


Critical Approach: Assumptions

Essential conflict between interest groups Marx: owners/workers Feminists: men/women Anti-racist theorists: whites/visible minorities

Concern for social justice Belief in equality of opportunity/result Research should play a role in exposing

sources of inequality and promoting social justice


Role of Values: Critical Approach

Moral absolutes: some issues such as social justice, equality, not negotiable.

Research only judged to be valid if it leads to an improvement in condition of humanity.


Critical Approach: Research Designs

Focus: structural mechanisms that structure power relations among groups

Analysis of policies, law, or practices that legitimate the power of certain groups Marxism – use historical-comparative method to

illustrate how certain laws, policies, or practices gives capitalist more power than workers and citizens

Feminism– expose structural mechanisms used to oppress women (e.g., laws, policies, customs)

Use variety of methodologies (see chapter 7)


Criticisms of the Critical Approach

Absolute moral values deemed unscientific

Tendency to report desired outcomes only

Do not try to disprove critical assumptions


Some Important Distinctions

1. Quantitative versus qualitative research

2. Descriptive versus explanatory research

3. Pure versus applied research

4. Units of analysis: individuals/aggregations


Quantitative versus Qualitative

Quantitative Research Uses 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


Descriptive Versus Explanatory

Descriptive: emphasis on accurate count of dimensions

e.g., collect data in a way that allows one to describe the attributes of individuals, communities, or nations Census - description of entire population Sample - a small portion of the population who are

selected to represent the population

Explanatory: goal is to understand or to explain relationships.

e.g., why is it that females who select gender non-traditional careers come from higher socioeconomic backgrounds. Test alternative explanations


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


Units of Analysis

Individual level: data that describes the attitudes or characteristics of individuals More researchers employ individual level Explain variations in women’s length of

hospitalization following childbirth

Aggregation level: data that describes 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


Types of Variables

Dependent variables

Independent variables (also called the treatment variable in experimental design)

Control variablesIntervening variables

Conditional variables

Source of spuriousness variables

Confounding variables


Dependent Variable

The variable being “explained” The “effect” in the cause/effect relationship

Also called an “outcome” variable e.g., program of study, crime rate, recovery

rate, fatigue, political participation Indicated as the letter Y

X Y


Dependent variables

Alienation Academic

achievement Length of hospital stay Bereavement Class voting Occupational burnout Role strain/role conflict Marital satisfaction Quality of life Divorce

Fertility Life expectancy Status attainment Intergenerational

occupational mobility Maternal employment Occupational burnout Marital power Literacy Gender role orientation


Dependent variables (cont’d)

Divorce School dropout Fear of victimization Racial intolerance Health promoting behaviour Delinquency Economic conservatism Right- and left-wing

attitudes Income (gender gap)

Mortality (death) Morbidity (illness) Well-being/mental health Rape myth adherence Imprisonment rates Political participation Homophobia Authoritarianism Hypermasculinity/

machismo


Independent variable

The “cause” in a cause-effect relationship This variable is theorized as “influencing” the

dependent variable. e.g., gender, age, socioeconomic status

Indicated as the letter X in a formal statement:X Y

Thus, changes in the level of X, correspond with changes in the level of Y

Socioeconomic status influences preference for nontraditional program of study


Control variables

A control variables is a variable taken into account in exploring the relation between an independent variable and a dependent variable Control for the effects of other factors

Three types of control variables: Intervening Conditional Source of spuriousness


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 non-traditional program of study


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.


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 model, you note that you are

examining the relationship separately for the conditional variable

Males Females

X Y X Y


C. Source of Spuriousness Variable

A source of spuriousness variable (S/S) is a variable that is viewed as 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

…continued


Source of spuriousness (cont’d)

Example: when exploring the relationship between socioeconomic background and choice of non-traditional 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 her parents’ socioeconomic status as well as her own university program preferences

X / Y ↑ - S/S - ↑

chapter one: approaches to methods winston jackson and norine verberg methods: doing social...

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