jac_methods_Ch01
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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
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
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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
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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
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Positivism: Assumptions
i.
ii.
iii.
iv.
v.
vi.
vii.
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
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Positivism: Role of Values in Research
Should be value-free
Put personal preferences aside
Test alternative explanations
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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
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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
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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
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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
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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
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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)
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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
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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
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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
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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.
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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)
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Criticisms of the Critical Approach
Absolute moral values deemed unscientific
Tendency to report desired outcomes only
Do not try to disprove critical assumptions
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Some Important Distinctions
1. Quantitative versus qualitative research
2. Descriptive versus explanatory research
3. Pure versus applied research
4. Units of analysis: individuals/aggregations
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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
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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 nontraditional careers come from higher socioeconomic
backgrounds
Test alternative explanations
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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
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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
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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
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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 nontraditional programs
Dependent variable: program of study
Indicated as the letter Y:
XY
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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:
XY
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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
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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 nontraditional careers “intervenes” to explain why
those of higher SES are more likely to choose
nontraditional program of study
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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
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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
XY
Females
XY
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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
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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
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