1. CORE CONCEPTS
in Sociology
John Bradford, Ph.D.

2. I. RESEARCH METHODS

3. Three types of Studies
• There are 3 different types of studies that
correspond to 3 different sorts of dependent
variables (Y), or objects of investigation…
1. Case study (what causes an event or condition)
– Often we aren’t interested in Y itself as a fact or event,
but changes in Y across time (longitudinal study) or
differences in Y across space (cross-sectional study).
2. Cross-sectional study (comparison across space)
3. Longitudinal study (comparison across time)

4. Feedback
Two types of Feedback:
1. Positive (reinforcing, amplifying):
Initial changes become amplified or
magnified over time; patterns are
reinforced.
– Examples: exponential population
growth; nuclear explosion; ‘rich getting
richer’, etc.
2. Negative (counteracting,
balancing):
Initial changes are counteracted or
balanced out, so that conditions remain
relatively stable.
– Examples: homeostasis; a thermostat;
“what goes up, must come down”, etc.
Births
+
Population
+
Force of
Gravity
-
Jump up
+
Positive Feedback
Negative Feedback

5. Positive vs. Negative Association
of Variables
• Positive association
i. as values of X go up, values of Y go up. ↑↑
ii. as X goes down, Y goes down. ↓↓
• Negative association
– as X goes up (down), Y goes down (up) ↓↑ or ↑↓.

6. Positive vs. Negative Association
of Variables
• Notes:
i. “Positive” and “Negative” associations are averages!
Examples that don’t fit the general pattern will
always exist.
ii. ‘Associations’ refer to relationships between 2 or
more variables, not a single variable in itself.
iii. Example: height and weight are positively associated
(on average)

7. Independent (X) vs. Dependent (Y)
Variables
• Independent variable (X) = the ‘cause.’ Variable that influences.
• Dependent variable (Y) = the ‘effect.’ Variable that is influenced by
the cause; it is dependent on the cause.
• INCA: the INdependent variable is the CAuse.

8. Independent (X) vs. Dependent (Y)
Variables
• Examples:
– Gender (X) is thought to influence occupation (Y)
– Religious affiliation (Y) is thought to be influenced by income.
– Educational attainment (X) is thought to influence income (Y).
– Age (X) is thought to influence attitudes towards using
computers (Y)
– Income (Y) is thought to be influenced by race (X)

9. Sampling
1. A Sample is a portion of the larger
population that you will study to make
inferences about the larger population.
2. General rule: the more diverse a population
is, the larger the sample needs to be!
3. Samples should be random (equally
probable). Randomness means that every
element in the population has the same
probability of being in the sample.

10. Experiments
• An experiment involves manipulating the
independent variable (X) and observing the effect on
the dependent variable (Y)
• Experiments are the only means by which we can
explore causal relationships; only way we can know
for sure if changes to X cause changes in Y.
• Experimenter needs two dependent variable (Y)
groups of Y:
1. Experimental group- receives ‘treatment’ of independent
variable (X)
2. Control group- does not receive treatment; is left alone.

11. Experiments
• Imagine a scientist testing the
effect that some drug, X, has on
growth of rats, Y.
• To see how the drug effects rat
growth, the experimenter will
compare growth in two groups
of rats: Y₁ , the group of rats
that gets the drug (X) and a
group of rates Y₂ that will not.
• Y₁ is the experimental group,
and Y₂ is the control group.

12. Experiments
• One assumes separation or isolation
between the setting where X is
applied and the control, where X isn’t
applied.
• It is important that rats which receive
the drug and rats which do not be
alike in all relevant characteristics and
conditions, so that any observed
differences between rats which
receive the drug (the experimental
group) and those that do not (the
control group) can be attributed only
to the drug (X), and not to something
else.

13. Experiments
• Random Assignment to condition-
is the process whereby all
participants have an equal chance
of taking part in any condition of
the experiment.
• The purpose is to ensure that any
potentially relevant differences
between the experimental and
control groups are distributed
evenly and therefore won’t affect
the outcome (i.e. will cancel each
other out)

14. Experiments
• A counter-factual refers to something
that did not happen, but could have or
would have occurred.
• We use the ‘control group’ to make a
counterfactual argument, which says that:
“in the absence of X, this is how Y₁ would
have behaved.” We assume that Y₁ would
have behaved like Y₂, the control.
• Why? Because they are alike in all
relevant characteristics so any difference
we observe must be a result of the
independent variable, X.

15. Experiments
5 Rules for Doing True Experiments
1. Have at least two groups (control and experiment)
2. Randomly assign people to groups
3. Treat the experimental group by manipulating the
independent variable
4. Observe the effect of the treatment on the dependent
variable in the experimental group
5. Compare the dependent variable differences (the
outcome of treatment) in the experimental and
control groups

16. II. FOUR FAMOUS SOCIAL
PSYCHOLOGY EXPERIMENTS

17. Stanley Milgram and Obedience
• One of the most famous
experiments of the 20th century.
• What explains the Holocaust? Are
Germans just inherently more
obedient than other people?
• The Milgram experiment measured
the willingness to obey an
authority figure who instructed
them to perform acts that
conflicted with their personal
conscience.

18. Stanley Milgram and Obedience
Experiment:
• Three roles:
– an experimenter (man in white lab coat);
– a volunteer (the ‘teacher’);
– and the shockee (the ‘learner’). All are
actors except the volunteer.
• Responding to a newspaper ad, a volunteer
was told he would be participating in an
experiment testing the effects of negative
reinforcement (punishment) on learning.
The volunteer was told that a ‘teacher’
(giving electric shocks) and ‘learner’
(receiving electric shocks) were to be picked
at random.

19. Stanley Milgram and Obedience
Experiment:
• In reality, the experiment was to see how
much electroshock the teacher would give as
punishment, when told it was part of an
experiment. Everyone but the ‘teacher’ was
acting and knew the true purpose of the
experiment. No electric shocks were actually
administered, but the volunteer believed he
was administering them.
• The ‘learner’ would go into another room and
a tape recording was played of scripted
answers. For each wrong answer, the teacher
was supposed to give a shock to the learner,
with the voltage increasing in 15-volt
increments for each wrong answer.

20. Stanley Milgram and Obedience
Findings:
• BASELINE STUDY (most famous):
65% of volunteers ‘go all the way’
and are willing to shock the subject
to death!
• Milgram also studied 20-40
variants of this experiment with
different results:

21. Stanley Milgram and Obedience
Findings:
• Experiment #3: The Shockee is placed
in the same room so that the volunteer
can see him; obedience drops to 40%.
• Experiment #4: The volunteer must
physically restrain the shockee;
obedience drops to 30%.
• Experiment #14 : If experimenter is
not a scientist in a white lab coat, then
obedience drops to 20%.
• Experiment #17: Volunteer and two
other participants (both actors); if
other actors refuse to continue the
experiment, obedience drops to 10%

22. Stanley Milgram and Obedience
Findings:
• Experiment #15: *If there are two
other experimenters in white lab
coats (both actors) who disagree
about what to do, then obedience
drops to ZERO!
• As soon as participants are told
that they “have no choice”,
obedience drops to ZERO!
• These results were confirmed in
2006.

23. Stanley Milgram and Obedience
QUESTION: What does all this mean?
Why did so many people go along
with the experiment, if they only did
so long as they were NOT ordered
to do so?

24. Stanley Milgram and Obedience
• This study does NOT show that
people ‘obey orders’!
• They are participating because they
believe they are promoting the
‘greater good’, a noble cause:
science.
• They are shocking innocent
strangers not because they believe
they have to, but because they
believe they ought to.

25. Zimbardo’s Stanford Prison
Experiments
Experiment:
• 70 volunteers selected;
• by flip of coin, half are chosen
as guards, other half as
prisoners
• Participants make up their own
rules; not pre-determined
• Each participant was paid $15 a
day

26. Zimbardo’s Stanford Prison
Experiments
• Findings:
• Experiment ended after 6 days!
• Could no longer distinguish reality (the
experiment) from the roles they
adopted as prisoners and guards
• “There were dramatic changes in
virtually every aspect of their behavior,
thinking and feeling…. We were
horrified because we saw some boys
(guards) treat others as if they were
despicable animals, taking pleasure in
cruelty, while other boys (prisoners)
became servile, dehumanized robots….”
(141)

27. Zimbardo’s Stanford Prison
Experiments
• Findings:
• About 1/3 of guards became
‘corrupted by the power of their
roles’ (142)
• “*T+he mere act of assigning
labels to people and putting them
into a situation where those
labels acquire validity and
meaning is sufficient to elicit
pathological behavior”
(Zimbardo, pg. 143)

28. ‘On Being Sane in Insane Places’
• Can we always distinguish
‘normal’ from ‘abnormal’
people? The ‘sane’ from the
‘insane’?
• How objective are these labels?
1. Are ‘insane’ behaviors caused
by innate characteristics of
these individuals or are they
elicited from external
environments?
2. Do observers see the ‘same’
behavior differently in different
circumstances? Scene from One Flew
Over the Cuckoo’s Nest
(1975)

29. ‘On Being Sane in Insane Places’
• Rosenhan undertakes groundbreaking study:
will sane people (‘pseudo-patients’) be
recognized as sane by hospital staff in a
psychiatric ward?
• Experiment
– 8 sane people admitted into 12 hospitals; 3
women, 5 men
– Initially complained of ‘hearing voices’ of an
‘existential nature’:
– Symptoms chosen because there were zero
reports of ‘existential psychoses in the literature’
– After being admitted, pseudo-patients behaved
normally
– Length of stay ranges from 7 to 52 days, average
of 19 days
D. L. Rosenhan

30. ‘On Being Sane in Insane Places’
• Findings: The normal are not
detectably sane!
– Pseudo-patients were never detected
• Other patients (but not doctors and staff)
sometimes detected that they were not
insane.
– Each was discharged with a diagnosis
of schizophrenia “in remission”
– Normal behaviors were often
interpreted as abnormal because of the
diagnosis!
D. L. Rosenhan

31. Labels and Perception
Label
(diagnosis)
Perception
of
behavior
• “Once a person is
designated abnormal, all
of his other behaviors and
characteristics are
colored by that label”
(280).
1. Observers perceive
normal behavior as crazy;
our expectations thus
reinforce our initial
impressions
2. Patients can even begin
to see themselves as
‘crazy’, and thus act crazy
(self-fulfilling prophecy)

32. Asch’s Conformity Experiments
• Question: Which of the lines
on the second card (A, B, or C)
is the same length as the line
on the first card?
• “That we have found the
tendency to conformity in our
society so strong that
reasonably intelligent and
well-meaning young people
are willing to call White Black
is a matter of concern. It
raises questions about out
ways of education and about
the values that guide out
conduct” (95)
Solomon Asch
(1907 – 1996)

33. III. SOCIOLOGICAL CONCEPTS

34. What is Sociology?
• Definition #1: Sociology is the scientific study of
interactions and relations among human beings (p.
3).
– Socius (Latin) = ‘associate’; logy (Greek) = ‘study’
• Definition #2: Sociology explains the intended and
unintended consequences of human influence.

35. What is Sociology?
• Sociology studies the PATTERNS that people
generate as they interact, influence, and relate to
one another.
• In short:
THINK PATTERNS, NOT PEOPLE!
(at least not individual people)

36. What is an explanation?
• An Explanation of anything is always:
1. An answer some Why-question, and
2. A comparison (or contrast)
– “Why is the sky blue and not orange?”
– “Why does social inequality exist, instead of not
existing?”
• Often this comparison is not stated explicitly
– {NOTE: In English we can express this contrast in a variety of
ways. For example: Why A rather than B? Why A, as opposed to
B? Why A instead of, or in contrast to B? }

37. What is an explanation?
Additional Vocabulary:
• Explanandum (Latin) = the object of
explanation; whatever it is you are trying to
explain
• Explanans (Latin) = the explanation; the thing
that explains the explanandum.

38. What is an explanation?
• Example: “Why is it 85 degrees?”
• Explanandum = 85 degrees.
• Possible Explanations:
a) “Because we use the Fahrenheit scale instead of
Celsius.”
b) “Because of our approximate distance from the
sun.”
c) “Because it is summer time.”
d) “Because the air conditioner is not working.”

39. What is an explanation?
• The explanandum is really not an object at all,
but a comparison!
• Example: “Why is it 85 degrees?”
• Each explanation (explanans) of ‘85 degrees’
addresses a different explanandum:
a) 85 degrees (Fahrenheit, rather than Celsius)
b) 85 degrees (on earth, as opposed to another planet
or without the sun)
c) 85 degrees (in summer, in comparison to
temperatures in other seasons)
d) 85 degrees (inside, instead of 72 in most buildings)

40. What is an explanation?
• Why-Question: “Why do you rob banks?”
• Willie Sutton: “Because that’s where the
money is!”

41. What is an explanation?
• Intended Explanandum: The priest meant by his
question: ‘Why do you rob banks {vs not rob banks}?’
• Reinterpreted Explanandum: ‘Why do you rob banks
{vs. rob some other place}?

42. What is an explanation?
• Question: “Why do ducks fly south for the
winter? “
• Answer: “Because its too far to walk.”
– Intended explanandum: Why do ducks fly south for
the winter {vs not migrate south for the winter}?
– Reinterpreted explanandum: Why do ducks fly {vs
walk} south for the winter?

43. What is an explanation?
• Detective asks the suspect:
“Why did the man die?”
• Suspect answers: “Well, he
had to go sometime!”
– Intended explanandum: Why
did the victim die now {vs. die
at some other time}?
– Reinterpreted explanandum:
Why did the victim die at all
{vs. live forever}?

44. What is an explanation?
• Making different comparisons has led
to scientific revolutions...
• Physics:
– pre-Newtonian: Why does an object
{move/not move}?
– Newton: Why does an object have a
{given acceleration/ some other
acceleration}?
• Biology:
– Aristotle: Why does {this species/ some
other species} exist?
– Darwin: Why did this species
{survive/become extinct}?

45. What is an explanation?
• In a nutshell, “Thinking without
comparison is unthinkable.” (Swanson
1971: 145).

46. The Sociological Imagination
• Sociology attempts to explain facts about
groups of people, and then to relate these
social facts to our individual lives.
• The study of how our lives are influenced by
our larger historical and social circumstances
is called the sociological imagination.

47. The Sociological Imagination
“Neither the life of an individual
nor the history of a society can
be understood without
understanding both.”
C. Wright Mills
(1916-1962)

48. The Sociological Imagination
• To understand one side, you have to understand the
other.
• The ability to understand history and its relation to
biography is called the sociological imagination by C.
Wright Mills.
Man/Woman Society
Biography History
Self World
Personal “Troubles of
milieu”
Public “Issues of
social structure”

49. “Men make their own history,
but they do not make it as they
please; they do not make it
under self-selected
circumstances, but under
circumstances existing already,
given and transmitted from the
past. The tradition of all dead
generations weighs like a
nightmare on the brains of the
living.”
Karl Marx
(1818-1883)

50. What is Social REALITY?
• Thomas theorem: "If people define
situations as real, they are real in their
consequences“
• To understand human inter-actions and
relations, sociologists have to
understand both reality, and perceived
reality.
W. I. Thomas
1863 - 1947

51. • Social relations are often real
because we act AS IF they are real.
The social world concerns not only
the material world, but the
meanings we ascribe to the
material objects, meanings which
are themselves non-physical and
non-material.
Examples:
1. Nations
2. Money

52. Self-fulfilling and Self-negating
prophecies
• Robert K. Merton also coined the terms
– ‘self-fulfilling prophecy’ and
– ‘role model’
• A self-fulfilling prophecy is something that
becomes true because it is believed to be
true.
– Example: bank run, placebos, psychic
predictions, etc…
• A self-negating prophecy is a belief that
causes its own falsehood. Explanation: it is
something that, once believed to be true or
expected to happen, cannot happen (or
becomes less likely to happen).
Robert K. Merton
(1910 – 2003)

53. The Power of Expectations
• Pygmalion Effect (aka
Rosenthal effect): the
greater the expectation
placed upon people, the
better they perform.
– According to legend, Pygmalion
was the king of Cyprus who fell
in love with a beautiful woman
(Galatea) he sculpted out of
ivory.

54. The Power of Expectations
• In the 1960s Robert Rosenthal
and Lenore Jacobson
hypothesized that teacher
expectations influenced
children’s performance.
• Study: they randomly assigned 1
out of 5 children to the
‘spurter/bloomer’ group, but
told teachers these students
were selected to the group
based on test performances that
indicated future success.
• Findings: the kids who were
expected to ‘spurt’ made larger
improvements than nonspurters.

55. Cascades and ‘Tipping’ points
• Social Cascades = TIPPING = a domino effect or
chain reaction.
– Occurs when a small event triggers a large event or when
the actions of a few trigger the actions of many.
– Basic idea: small or few  large and many
• What explains this? We are always paying attention
to and being influenced by the behavior of other
people.

56. Cascades and ‘Tipping’ points
• Diversity + Connectedness = ‘Tipping’
– Example: There are 100 people in the mall and you
see a few of them running! How many of them
have to be running out of the mall before you run
out of the mall also?
• Assume you have no understanding of why they are
running!
Crowded mall

57. Cascades and ‘Tipping’ points
• Diversity and Connectedness lead to ‘Tipping’
• Consider two scenarios:
– Scenario 1: Homogeneity. Everyone has the same threshold, or
tipping point. Everyone will run out of the mall if they see 20 other
people run out of the mall. What happens? NOTHING! No one will
leave unless 20 other people leave!
– Scenario 2: Heterogeneity (Diversity). Everyone is numbered from 1
to 100; their number is also the number of people they need to see
running before they also run: their threshold. What happens? First
person leaves, then the second, then the third, etc. This generates a
chain reaction, aka a CASCADE!
Person 0
Begins to run
Person 1 runs
only if 1 other
person runs
Person 2 runs
only if 2 other
people run
3 4 5 6

58. Cascades and ‘Tipping’ points
• Mark Granovetter devised this threshold model
initially to describe RIOTS:
– one person will definitely riot; another will riot only if
one other person riots; a third will riot only if two
others riot; etc….
– We are much more likely to riot ourselves if we see
others rioting.

59. Cascades and ‘Tipping’ points
• The threshold model explains:
1. Why social changes can be
abrupt, discontinuous, and
sudden.
2. Why they are so unpredictable.
– One person in a chain can either
cause or prevent a collective
chain reaction, or social cascade.
• Other examples: clapping, birth
rates, dancing at parties…