1. Cultural Consensus Analysis
Bill Dressler & Kathy Oths
Society for Psychological Anthropology
2017

2. Basic Outline of (very brief) Workshop
Review basics of the model
Quick overview of techniques
Studying variation
Cultural consonance

3. Steps in Studying Cultural Models
Determine cultural domain to be studied
Identify salient elements of the domain
Free lists Open-ended interviews
Explore the structure of the domain
Pile sorts, ratings, rankings Narrative analysis
Test for Cultural Consensus
Explore distribution of cultural knowledge and content of shared understanding

4. Point to remember…. Cultural consensus analysis is not the beginning
Rather, it is the culmination of ethnographic work, usually supplemented by various forms of structured ethnographic techniques
CCA then enables you to:
Verify that knowledge is shared within a domain
Explore and better understand the configuration of the cultural model(s)

5. Review of the Basics of the Model

6. The Cultural Consensus Model
(Romney, Weller and Batchelder 1986)
Responses of
Individuals
Determine R’s
relative degree of
shared knowledge R1 R2 R3 R4 R5 R6 . Rn
Degree of
sharing of
knowledge
Calculate a consensus set
of responses, weighted by
pattern of knowledge
sharing

7. 2-dimensional array of food similarities/differences: 2010 - 2014

11. Meals

12. Health

13. Individual representation = [cultural model] + [personal model]
What are the features
that distinguish among
the elements of the model?
Is there a shared
understanding of these
features?

14. Adriane .83 Greg Pure personal biography:
Adriane – individual experiences
with food
.83
Greg – individual experiences
Adriane
.83
Greg
Why?
Shared cultural model:
Adriane
.83
Greg
knowledge1
Cultural Model
of Food
knowledge2
Individual correlation = knowledge1 x knowledge 2

15. Patterns of agreement: Meals
Ratio indicates overall
consensus, if > 3.0
Cultural competence coefficients
indicate how well your answers
reflect group-level answers
Average cultural competence
indicates the strength of the
cultural consensus

18. Cultural model of how to construct a meal
Kim
Robin
Adriane
Bryanna
Kelso
Diedre
Alec
Heidi
Joshua
Greg
.95
.98
.93
.98
Cultural model of how
to construct a meal
.93
.92
.90
.76
.78
.89

19. Consensus ratings
of foods

20. Consensus ratings = a ‘cultural best estimate’ How would a reasonably culturally competent member of this social group rate or classify these foods?

21. Fitting attributes to the array
How do we know if people are using features to define semantic structures?
Correlate the features with the distance between the points in the map of the pile sort
If the correlation is high (> .75), then probably people were using those features to sort the terms

22. ? Food Meal Health Southern TEA 4.00 1.76 MASHP 2.00 2.64 3.86 STEAK
1.00
2.71
3.47
BURGERS
1.77
3.31
SANWICH
2.76
2.66
HOTDOG
1.49
2.38
CORN
3.48
3.84
CATFISH
3.06
3.76
CHEESE
3.56
APPLE
5.00
3.93
2.58 FF
1.21
2.94
COOKIE
3.00
1.06
2.69
FCHICK
1.31
3.97
RICE
3.16
3.08
WING
2.78
BEER
1.51
3.25
ICREAM
1.17
2.85
ORANGE
1.80
SALAD
2.63
PIE
1.27
3.88
SHRIMP
3.58
3.23
GRITS
MNCHEES
1.85
3.67
BEANS
3.68
3.63
PEAS
3.79
3.32
BBQ
1.87
3.90
PIZZA
1.65
2.06
BANANA
3.82
2.03
OKRA
3.78
3.87
TOMATO
3.46

23. Fitting the attributes
Meal correlation = .91
Health correlation = .91
Southern correlation = .20

24. 2-dimensional array of food similarities/differences: 2010 + 2011
Where does it
go on my plate?
Is it healthy?

25. Quick Overview of Techniques

26. Doing Cultural Consensus Analysis
In Anthropac
The formal process model
The informal data model
In a standard statistical package: SPSS
Formal process model (MTTIW)
Informal data model

27. Studying Variation

28. Classic Brazilian Food
Feijão/Feijoada
Rice
Churrasco
Cerveja (beer)
Macarão (pasta)
Hearts of palm
Pintado (catfish)
Doces (sweets)
Sucos/vitaminas
Almoço (lunch)
Launches
Salgadinhos/picados
Comida mineiro
Comida baiano
Comida carioca
Comida gaúcho

29. The Prestige Value of Food in Urban Brazil (Oths, Carolo, & dos Santos 2003)
Sample
Eigenvalue ratio
Mean (± sd)
Total sample
1.8:1
.40 (± .35)
Upper-middle class
10:1
.69 (± .06)
Middle class
Single factor
.54 (± .04)
Lower middle class
.81 (± .03)
Lower class
.50 (± .28)

30. Testing variation with separate model estimates within groups (Oths, Carolo, & dos Santos 2003)

31. Cultural Modeling - The Domain of Family Life
“Violence/addiction”
“Lack of education”
Importance for having
a family
“Family organization”
“Affective climate”

32. Distribution of Cultural Competence in Family Life – urban Brazil
Eigenvalue ratio = 8.49

33. Recommended cut-off points for the S. D
Recommended cut-off points for the S.D. of cultural competence (Hruschka and Maupin 2013)

35. Relationship of years in Nairobi and cultural competence in the cultural model of HIV+ management (Copeland 2011)

36. Cultural competence in family life and psychological distress in urban Brazil (n = 52)
Step 1
Step 2
Step 3
Age
-.073
-.033
.035
Sex
-.163
-.161
-.056
Socioeconomic status
-.343*
-.288*
-.252*
Cultural competence
in family life -
-.282*
-.197*
Cultural consonance
-.461*
Multiple R
.378*
.467*
.635*

37. Residual Agreement Concept introduced by Boster in 1986
Refers to agreement among respondents beyond an overall cultural consensus
“Multicentric domain”
Defined by Caulkins and Hyatt
Multicentric domains have multiple centers of agreement:
Subcultural domains, in which there are two or more centers of agreement that are different but not oppositional
Contested domains, in which some individuals take a perspective opposite to that expressed by others in the same population

38. Boster’s (1986) original approach
Works from the agreement matrix
Run consensus analysis and then generate the predicted agreement
Subtract the predicted agreement matrix from the observed agreement matrix to generate a residual agreement matrix
Use QAP (quadratic assignment procedure) to test for correlation of the observed and residual agreement matrices
If matrices are correlated, then there is residual agreement not exhausted by the consensus

39. Boster’s original approach (cont.)
This can be thought of as an “omnibus” test of residual agreement
Just tells you it’s there
Not what it is
Utility of this test may not be great, especially if there is always going to be some kind of residual agreement—a reasonable assumption

40. Norbert Ross & Doug Medin
In essence, they use the same approach as Boster to test for residual agreement
They calculate residual matrices within groups and compare them
Then, they identify which items from the consensus analysis differ between groups
This actually confounds overall cultural consensus with whatever differences exist

41. Hruschka, et al. (2008)
First, they confirm that there is an overall cultural consensus
Second, using three different techniques, they demonstrate that there are different patterns of response within groups
Third, they compare cultural answer keys calculated within groups
Does not account for overall cultural consensus

42. Boster and Johnson (1989) Use the second factor
This captures agreement left over after the overall consensus has been accounted for
Plotting respondents by cultural competence coefficients and second factor loadings—or “residual agreement coefficients”—shows the shape of divergence from the overall consensus

43. Distribution of cases by cultural competence and residual agreement
Eigenvalue ratio = 6.7
Mean competence = 0.70
s.d. = 0.11
(Second Factor)
(First Factor)

44. Distribution of cases by cultural competence and residual agreement
Blue = 2001
Red = 2011
p < .001 for residual agreement

45. Residual agreement (Dressler et al. 2015)
Shared deviation
from consensus
within subgroup1
OVERALL
CULTURAL
CONSENSUS
“Residual agreement”
Shared deviation
from consensus
within subgroup2

46. Calculating deviation from the overall cultural consensus
Dev1 = individual rating of item 1 – consensus rating of item 1 Dev2 = individual rating of item 2 – consensus rating of item 2 ….. DevN = individual rating of item N – consensus rating of item N
Deviations averaged
over individuals in
subgroup1
Deviations averaged
over individuals in
subgroup2

47. compute d1 = ls1 - 3. 07. compute d2 = ls2 - 3. 23
compute d1 = ls compute d2 = ls compute d3 = ls compute d4 = ls compute d5 = ls compute d6 = ls compute d7 = ls compute d8 = ls compute d9 = ls compute d10 = ls compute d11 = ls compute d12 = ls compute d13 = ls compute d14 = ls compute d15 = ls compute d16 = ls
compute d17 = ls compute d18 = ls compute d19 = ls compute d20 = ls compute d21 = ls compute d22 = ls compute d23 = ls compute d24 = ls compute d25 = ls compute d26 = ls compute d27 = ls compute d28 = ls compute d29 = ls compute d30 = ls compute d31 = ls compute d32 = ls

48. Results of the analysis of residual agreement
Items rated more
important in 2011
<
Items rated more
important in 2001
>

49. Respondents in 2011 rated as more important than the overall
consensus items associated
with information technologies,
especially cell phones and
internet access
Respondents in 2001 rated as
consensus items associated with
traditional Brazilian sociality,
especially spending time in
venues associated with social
interaction
Items rated more
important in 2011
Items rated more
important in 2001

51. Cultural Consonance

52. Cultural consonance is the degree to which individuals approximate, in their own beliefs and behaviors, the prototypes for belief and behavior encoded in shared cultural models
Cultural models Cultural consonance Health outcomes

53. Less important
More important

54. Calculating Cultural Consonance in Lifestyle
Responses of Respondent 10042 No
Yes 1
Total =
9/18=

56. Pile sort - 2001 Pile sort - 2011 ‘’Organization’ ‘Violence’
‘Education’
Pile sort
‘A good family’
‘’Organization’
‘Affect’
‘Violence’
‘Education’
‘A good family’
’Organization’
Pile sort
‘Affect’

58. Constructing and scaling survey items to measure cultural consonance in family life
Each of core concepts
from cultural domain
18 Likert-response
items gauging the
respondent’s appraisal
of her own family
Group discussion of possible
survey research items
within research staff
Scale scores = sum of responses
weighted by the importance of
the concept from cultural
consensus analysis

59. Cronbach’s alpha = .87

61. Description of Brazilian families
using free listing and focus groups
Exploration of dimensions
of meaning using pile sorts and focus groups
Confirmation of consensus
around principal dimension
of value
A straight line from natural speech acts to measurement = emic validity
Development of scale of
cultural consonance based
on consensus meaning
of terms

62. Cultural consonance in life goals

63. The End