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iii
Preface
The RAND Corporation seeks to improve policy through research and analysis. Within
RAND, the Center for Qualitative and Mixed Methods acts primarily as an internal forum for
dissemination of mixed methods. Mixed methods are a set of techniques used to process both
qualitative and quantitative data. One approach to mixed methods is to begin a research process
with highly qualitative data—such as documents produced by people in the course of their lives
or notes from ethnographic interviews—and then process these data into fully quantitative
statistical analyses.
We recognized that, within policy and academic research, dealing theoretically and
empirically with culture (i.e., socially learned information that influences beliefs and behaviors)
is one of the primary motivations to engaging in a qualitative-to-quantitative research process.
As with much academic social science, some policy research is conducted within the framework
of utility maximization (i.e., the notion that actors are agents who optimize some function for
outcomes that result from their behaviors). Taking the concept of culture seriously, however,
means that researchers must consider that individuals do not have perfect information when they
optimize utility. Both the outcomes and the range of behaviors to achieve them often are learned
by observing other individuals, and the variable distribution of this socially learned information
is what we recognize as
culture
. Culture thus becomes a crucial part of the information context in
which utility is maximized.
Integrating culture within social science in general requires mixed methods because culture
comes to the researcher in a qualitative form but must be quantified for research paradigms that
involve formal tests of theory. The authors of this manual come from different traditions within
anthropology, including cognitive, evolutionary, and biocultural approaches, and we have
worked in a variety of applied research roles. We discovered that we each had independently
encountered many of the concepts and methods in this manual and found them useful in
providing a formal approach to dealing with culture. Currently, these concepts and methods are
scattered among various articles from disconnected traditions within anthropology and related
areas of social science. Thus, we felt
A Manual for Cultural Analysis
was needed.
RAND Ventures
The RAND Corporation is a research organization that develops solutions to public policy
challenges to help make communities throughout the world safer and more secure, healthier and
more prosperous. RAND is nonprofit, nonpartisan, and committed to the public interest. RAND
Ventures is a vehicle for investing in policy solutions. Philanthropic contributions support our
ability to take the long view, tackle tough and often-controversial topics, and share our findings
iv
in innovative and compelling ways. RAND’s research findings and recommendations are based
on data and evidence, and therefore do not necessarily reflect the policy preferences or interests
of its clients, donors, or supporters. Funding for this venture was provided by gifts from RAND
supporters and income from operations.
v
Contents
Preface .. iii
Figures and Tables ........ vii
Summary ......... viii
Acknowledgments ......... ix
Abbreviations ..... x
1.Introduction: The Need for an Operational Concept of Culture ........... 1
2.What We Know About How Culture Operates and Why ......... 4
Culture as an Adaptive Buffer . 4
Learning Mechanisms . 5
Social Learning Strategies ....... 8
Emergent Higher-Order Patterns from Social Learning .......... 11
Summary ...... 19
3.Methods to Understand Culture: Cultural Consensus Analysis .......... 21
Other Potential Solutions for When the Cultural Constructs Are Not Known a Priori . 25
Empirical Examples of Cultural Consensus Analysis . 30
Cultural Consensus Analysis, Qualitative Methods, and Statistical Methods .. 41
4.Using Cultural Measurements in Statistical Models with Other Variables ..... 43
Modeling Cultural Measures Together with Attribute Data .... 43
Modeling Cultural Measures on Networks ..... 45
Network Science Statistical Techniques ........ 46
5.Dealing with Cultural Data-Point Nonindependence—Galton’s Problem ...... 54
How Nonindependence Affects Models......... 56
Policy-Relevant Applications of Modeling Nonindependence 58
Methods to Correct for Nonindependence ..... 59
Constructing the Expected Autocorrelation Matrix
w
. 61
6.Conclusion.... 67
References ........ 69 。。。。。。