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Dual inheritance theory (DIT), also known as gene–culture coevolution or biocultural evolution, was developed in the 1960s through early 1980s to explain how human behavior is a product of two different and interacting evolutionary processes: genetic evolution and cultural evolution. Genes and culture continually interact in a feedback loop:
changes in genes can lead to changes in culture which can then
influence genetic selection, and vice versa. One of the theory's central
claims is that culture evolves partly through a Darwinian selection
process, which dual inheritance theorists often describe by analogy to
genetic evolution.
'Culture', in this context, is defined as 'socially learned
behavior', and 'social learning' is defined as copying behaviors
observed in others or acquiring behaviors through being taught by
others. Most of the modelling done in the field relies on the first
dynamic (copying), though it can be extended to teaching. Social learning,
at its simplest, involves blind copying of behaviors from a model
(someone observed behaving), though it is also understood to have many
potential biases,
including success bias (copying from those who are perceived to be
better off), status bias (copying from those with higher status),
homophily (copying from those most like ourselves), conformist bias
(disproportionately picking up behaviors that more people are
performing), etc. Understanding social learning is a system of pattern
replication, and understanding that there are different rates of
survival for different socially learned cultural variants, this sets up,
by definition, an evolutionary structure: cultural evolution.
Because genetic evolution is relatively well understood, most of
DIT examines cultural evolution and the interactions between cultural
evolution and genetic evolution.
Theoretical basis
DIT holds that genetic and cultural evolution interacted in the evolution of Homo sapiens.
DIT recognizes that the natural selection of genotypes is an important
component of the evolution of human behavior and that cultural traits
can be constrained by genetic imperatives. However, DIT also recognizes
that genetic evolution has endowed the human species with a parallel
evolutionary process of cultural evolution. DIT makes three main claims:
Culture capacities are adaptations
The
human capacity to store and transmit culture arose from genetically
evolved psychological mechanisms. This implies that at some point
during the evolution of the human species a type of social learning leading to cumulative cultural evolution was evolutionarily advantageous.
Culture evolves
Social
learning processes give rise to cultural evolution. Cultural traits
are transmitted differently from genetic traits and, therefore, result
in different population-level effects on behavioral variation.
Genes and culture co-evolve
Cultural
traits alter the social and physical environments under which genetic
selection operates. For example, the cultural adoptions of agriculture
and dairying have, in humans, caused genetic selection for the traits to
digest starch and lactose, respectively. As another example, it is likely that once culture became adaptive,
genetic selection caused a refinement of the cognitive architecture that
stores and transmits cultural information. This refinement may have
further influenced the way culture is stored and the biases that govern
its transmission.
DIT also predicts that, under certain situations, cultural
evolution may select for traits that are genetically maladaptive. An
example of this is the demographic transition,
which describes the fall of birth rates within industrialized
societies. Dual inheritance theorists hypothesize that the demographic
transition may be a result of a prestige bias, where individuals that
forgo reproduction to gain more influence in industrial societies are
more likely to be chosen as cultural models.
View of culture
People have defined the word "culture" to describe a large set of different phenomena. A definition that sums up what is meant by "culture" in DIT is:
Culture is socially learned information stored in individuals' brains that is capable of affecting behavior.
This view of culture emphasizes population thinking by focusing on
the process by which culture is generated and maintained. It also views
culture as a dynamic property of individuals, as opposed to a view of
culture as a superorganic entity to which individuals must conform. This view's main advantage is that it connects individual-level processes to population-level outcomes.
Genetic influence on cultural evolution
Genes affect cultural evolution via psychological predispositions on cultural learning.
Genes encode much of the information needed to form the human brain.
Genes constrain the brain's structure and, hence, the ability of the
brain to acquire and store culture. Genes may also endow individuals
with certain types of transmission bias (described below).
Cultural influences on genetic evolution
Culture can profoundly influence gene frequencies in a population.
Lactase persistence
One of the best known examples is the prevalence of the genotype
for adult lactose absorption in human populations, such as Northern
Europeans and some African societies, with a long history of raising
cattle for milk. Until around 7,500 years ago, lactase production stopped shortly after weaning, and in societies which did not develop dairying, such as East Asians and Amerindians, this is still true today.
In areas with lactase persistence, it is believed that by domesticating
animals, a source of milk became available while an adult and thus
strong selection for lactase persistence could occur; in a Scandinavian population, the estimated selection coefficient was 0.09-0.19. This implies that the cultural practice of raising cattle first for meat and later for milk led to selection for genetic traits for lactose digestion.
Recently, analysis of natural selection on the human genome suggests
that civilization has accelerated genetic change in humans over the past
10,000 years.
Food processing
Culture has driven changes to the human digestive systems making
many digestive organs, such as teeth or stomach, smaller than expected
for primates of a similar size, and has been attributed to one of the reasons why humans have such large brains compared to other great apes.
This is due to food processing. Early examples of food processing
include pounding, marinating and most notably cooking. Pounding meat
breaks down the muscle fibres, hence taking away some of the job from
the mouth, teeth and jaw.
Marinating emulates the action of the stomach with high acid levels.
Cooking partially breaks down food making it more easily digestible.
Food enters the body effectively partly digested, and as such food
processing reduces the work that the digestive system has to do. This
means that there is selection for smaller digestive organs as the tissue
is energetically expensive, those with smaller digestive organs can process their food but at a lower energetic cost than those with larger organs.
Cooking is notable because the energy available from food increases
when cooked and this also means less time is spent looking for food.
Humans living on cooked diets spend only a fraction of their day
chewing compared to other extant primates living on raw diets. American
girls and boys spent on average 7 to 8 percent of their day chewing
respectively (1.68 to 1.92 hours per day), compared to chimpanzees, who
spend more than 6 hours a day chewing.
This frees up time which can be used for hunting. A raw diet means
hunting is constrained since time spent hunting is time not spent eating
and chewing plant material, but cooking reduces the time required to
get the day's energy requirements, allowing for more subsistence
activities. Digestibility of cooked carbohydrates is approximately on average 30% higher than digestibility of non-cooked carbohydrates.
This increased energy intake, more free time and savings made on tissue
used in the digestive system allowed for the selection of genes for
larger brain size.
Despite its benefits, brain tissue requires a large amount of
calories, hence a main constraint in selection for larger brains is
calorie intake. A greater calorie intake can support greater quantities
of brain tissue. This is argued to explain why human brains can be much
larger than other apes, since humans are the only ape to engage in food
processing. The cooking of food has influenced genes to the extent that, research suggests, humans cannot live without cooking.
A study on 513 individuals consuming long-term raw diets found that as
the percentage of their diet which was made up of raw food and/or the
length they had been on a diet of raw food increased, their BMI
decreased. This is despite access to many non-thermal processing, like grinding, pounding or heating to 48 °C. (118 °F).
With approximately 86 billion neurons in the human brain and 60–70 kg
body mass, an exclusively raw diet close to that of what extant primates
have would be not viable as, when modelled, it is argued that it would
require an infeasible level of more than nine hours of feeding every
day. However, this is contested, with alternative modelling showing enough calories could be obtained within 5–6 hours per day.
Some scientists and anthropologists point to evidence that brain size
in the Homo lineage started to increase well before the advent of
cooking due to increased consumption of meat and that basic food processing (slicing) accounts for the size reduction in organs related to chewing.
Cornélio et al. argues that improving cooperative abilities and a
varying of diet to more meat and seeds improved foraging and hunting
efficiency. It is this that allowed for the brain expansion, independent
of cooking which they argue came much later, a consequence from the
complex cognition that developed.
Yet this is still an example of a cultural shift in diet and the
resulting genetic evolution. Further criticism comes from the
controversy of the archaeological evidence available. Some claim there
is a lack of evidence of fire control when brain sizes first started
expanding. Wrangham argues that anatomical evidence around the time of the origin of Homo erectus (1.8 million years ago), indicates that the control of fire and hence cooking occurred.
At this time, the largest reductions in tooth size in the entirety of
human evolution occurred, indicating that softer foods became prevalent
in the diet. Also at this time was a narrowing of the pelvis indicating a
smaller gut and also there is evidence that there was a loss of the
ability to climb which Wrangham argues indicates the control of fire,
since sleeping on the ground needs fire to ward off predators.
The proposed increases in brain size from food processing will have led
to a greater mental capacity for further cultural innovation in food
processing which will have increased digestive efficiency further
providing more energy for further gains in brain size. This positive feedback loop is argued to have led to the rapid brain size increases seen in the Homo lineage.
Mechanisms of cultural evolution
In
DIT, the evolution and maintenance of cultures is described by five
major mechanisms: natural selection of cultural variants, random
variation, cultural drift, guided variation and transmission bias.
Natural selection
Differences
between cultural phenomena result in differential rates of their
spread; similarly, cultural differences among individuals can lead to
differential survival and reproduction rates of individuals. The
patterns of this selective process depend on transmission biases and can
result in behavior that is more adaptive to a given environment.
Random variation
Random
variation arises from errors in the learning, display or recall of
cultural information, and is roughly analogous to the process of mutation in genetic evolution.
Cultural drift
Cultural drift is a process roughly analogous to genetic drift in evolutionary biology.
In cultural drift, the frequency of cultural traits in a population
may be subject to random fluctuations due to chance variations in which
traits are observed and transmitted (sometimes called "sampling error").
These fluctuations might cause cultural variants to disappear from a
population. This effect should be especially strong in small
populations.
A model by Hahn and Bentley shows that cultural drift gives a
reasonably good approximation to changes in the popularity of American
baby names. Drift processes have also been suggested to explain changes in archaeological pottery and technology patent applications.
Changes in the songs of song birds are also thought to arise from
drift processes, where distinct dialects in different groups occur due
to errors in songbird singing and acquisition by successive generations. Cultural drift is also observed in an early computer model of cultural evolution.
Guided variation
Cultural
traits may be gained in a population through the process of individual
learning. Once an individual learns a novel trait, it can be
transmitted to other members of the population. The process of guided
variation depends on an adaptive standard that determines what cultural
variants are learned.
Biased transmission
Understanding
the different ways that culture traits can be transmitted between
individuals has been an important part of DIT research since the 1970s. Transmission biases occur when some cultural variants are favored over others during the process of cultural transmission. Boyd and Richerson (1985)
defined and analytically modeled a number of possible transmission
biases. The list of biases has been refined over the years, especially
by Henrich and McElreath.
Content bias
Content biases result from situations where some aspect of a cultural variant's content makes them more likely to be adopted.
Content biases can result from genetic preferences, preferences
determined by existing cultural traits, or a combination of the two.
For example, food preferences can result from genetic preferences for
sugary or fatty foods and socially-learned eating practices and taboos. Content biases are sometimes called "direct biases."
Context bias
Context
biases result from individuals using clues about the social structure
of their population to determine what cultural variants to adopt. This
determination is made without reference to the content of the variant.
There are two major categories of context biases: model-based biases,
and frequency-dependent biases.
Model-based biases
Model-based
biases result when an individual is biased to choose a particular
"cultural model" to imitate. There are four major categories of
model-based biases: prestige bias, skill bias, success bias, and
similarity bias. A "prestige bias" results when individuals are more likely to imitate cultural models that are seen as having more prestige.
A measure of prestige could be the amount of deference shown to a
potential cultural model by other individuals. A "skill bias" results
when individuals can directly observe different cultural models
performing a learned skill and are more likely to imitate cultural
models that perform better at the specific skill. A "success bias"
results from individuals preferentially imitating cultural models that
they determine are most generally successful (as opposed to successful
at a specific skill as in the skill bias.) A "similarity bias" results
when individuals are more likely to imitate cultural models that are
perceived as being similar to the individual based on specific traits.
Frequency-dependent biases
Frequency-dependent
biases result when an individual is biased to choose particular
cultural variants based on their perceived frequency in the population.
The most explored frequency-dependent bias is the "conformity bias."
Conformity biases result when individuals attempt to copy the mean or
the mode cultural variant in the population. Another possible frequency
dependent bias is the "rarity bias." The rarity bias results when
individuals preferentially choose cultural variants that are less common
in the population. The rarity bias is also sometimes called a
"nonconformist" or "anti-conformist" bias.
Social learning and cumulative cultural evolution
In
DIT, the evolution of culture is dependent on the evolution of social
learning. Analytic models show that social learning becomes
evolutionarily beneficial when the environment changes with enough
frequency that genetic inheritance can not track the changes, but not
fast enough that individual learning is more efficient.
For environments that have very little variability, social learning is
not needed since genes can adapt fast enough to the changes that occur,
and innate behaviour is able to deal with the constant environment.
In fast changing environments cultural learning would not be useful
because what the previous generation knew is now outdated and will
provide no benefit in the changed environment, and hence individual
learning is more beneficial. It is only in the moderately changing
environment where cultural learning becomes useful since each generation
shares a mostly similar environment but genes have insufficient time to
change to changes in the environment.
While other species have social learning, and thus some level of
culture, only humans, some birds and chimpanzees are known to have
cumulative culture.
Boyd and Richerson argue that the evolution of cumulative culture
depends on observational learning and is uncommon in other species
because it is ineffective when it is rare in a population. They propose
that the environmental changes occurring in the Pleistocene may have provided the right environmental conditions. Michael Tomasello argues that cumulative cultural evolution results from a ratchet effect that began when humans developed the cognitive architecture to understand others as mental agents.
Furthermore, Tomasello proposed in the 80s that there are some
disparities between the observational learning mechanisms found in
humans and great apes - which go some way to explain the observable
difference between great ape traditions and human types of culture (see Emulation (observational learning)).
Cultural group selection
Although group selection is commonly thought to be nonexistent or unimportant in genetic evolution,
DIT predicts that, due to the nature of cultural inheritance, it may be
an important force in cultural evolution. Group selection occurs in
cultural evolution because conformist biases make it difficult for novel
cultural traits to spread through a population (see above section on
transmission biases). Conformist bias also helps maintain variation
between groups. These two properties, rare in genetic transmission, are
necessary for group selection to operate. Based on an earlier model by Cavalli-Sforza and Feldman, Boyd and Richerson show that conformist biases are almost inevitable when traits spread through social learning,
implying that group selection is common in cultural evolution.
Analysis of small groups in New Guinea imply that cultural group
selection might be a good explanation for slowly changing aspects of
social structure, but not for rapidly changing fads. The ability of cultural evolution to maintain intergroup diversity is what allows for the study of cultural phylogenetics.
Historical development
In 1876, Friedrich Engels wrote a manuscript titled The Part Played by Labour in the Transition from Ape to Man, accredited as a founding document of DIT;
“The approach to gene-culture coevolution first developed by Engels and
developed later on by anthropologists…” is described by Stephen Jay Gould as “…the best nineteenth-century case for gene-culture coevolution.” The idea that human cultures undergo a similar evolutionary process as genetic evolution also goes back to Darwin. In the 1960s, Donald T. Campbell published some of the first theoretical work that adapted principles of evolutionary theory to the evolution of cultures. In 1976, two developments in cultural evolutionary theory set the stage for DIT. In that year Richard Dawkins's The Selfish Gene
introduced ideas of cultural evolution to a popular audience. Although
one of the best-selling science books of all time, because of its lack
of mathematical rigor, it had little effect on the development of DIT.
Also in 1976, geneticists Marcus Feldman and Luigi Luca Cavalli-Sforza published the first dynamic models of gene–culture coevolution.
These models were to form the basis for subsequent work on DIT,
heralded by the publication of three seminal books in the 1980s.
The first was Charles Lumsden and E.O. Wilson's Genes, Mind and Culture.
This book outlined a series of mathematical models of how genetic
evolution might favor the selection of cultural traits and how cultural
traits might, in turn, affect the speed of genetic evolution. While it
was the first book published describing how genes and culture might
coevolve, it had relatively little effect on the further development of
DIT. Some critics felt that their models depended too heavily on genetic mechanisms at the expense of cultural mechanisms. Controversy surrounding Wilson's sociobiological theories may also have decreased the lasting effect of this book.
The second 1981 book was Cavalli-Sforza and Feldman's Cultural Transmission and Evolution: A Quantitative Approach. Borrowing heavily from population genetics and epidemiology, this book built a mathematical theory concerning the spread of cultural traits. It describes the evolutionary implications of vertical transmission,
passing cultural traits from parents to offspring; oblique
transmission, passing cultural traits from any member of an older
generation to a younger generation; and horizontal transmission, passing traits between members of the same population.
The next significant DIT publication was Robert Boyd and Peter Richerson's 1985 Culture and the Evolutionary Process.
This book presents the now-standard mathematical models of the
evolution of social learning under different environmental conditions,
the population effects of social learning, various forces of selection
on cultural learning rules, different forms of biased transmission and
their population-level effects, and conflicts between cultural and
genetic evolution. The book's conclusion also outlined areas for future
research that are still relevant today.
Current and future research
In
their 1985 book, Boyd and Richerson outlined an agenda for future DIT
research. This agenda, outlined below, called for the development of
both theoretical models and empirical research. DIT has since built a
rich tradition of theoretical models over the past two decades. However, there has not been a comparable level of empirical work.
In a 2006 interview Harvard biologist E. O. Wilson expressed disappointment at the little attention afforded to DIT:
"...for some reason I haven't fully
fathomed, this most promising frontier of scientific research has
attracted very few people and very little effort."
Kevin Laland and Gillian Ruth Brown attribute this lack of attention to DIT's heavy reliance on formal modeling.
"In many ways the most complex and
potentially rewarding of all approaches, [DIT], with its multiple
processes and cerebral onslaught of sigmas and deltas, may appear too
abstract to all but the most enthusiastic reader. Until such a time as
the theoretical hieroglyphics can be translated into a respectable
empirical science most observers will remain immune to its message."
Economist Herbert Gintis disagrees with this critique, citing empirical work as well as more recent work using techniques from behavioral economics.
These behavioral economic techniques have been adapted to test
predictions of cultural evolutionary models in laboratory settings as well as studying differences in cooperation in fifteen small-scale societies in the field.
Since one of the goals of DIT is to explain the distribution of human cultural traits, ethnographic and ethnologic
techniques may also be useful for testing hypothesis stemming from DIT.
Although findings from traditional ethnologic studies have been used to
buttress DIT arguments, thus far there have been little ethnographic fieldwork designed to explicitly test these hypotheses.
Herb Gintis has named DIT one of the two major conceptual
theories with potential for unifying the behavioral sciences, including
economics, biology, anthropology, sociology, psychology and political
science. Because it addresses both the genetic and cultural components
of human inheritance, Gintis sees DIT models as providing the best
explanations for the ultimate cause of human behavior and the best
paradigm for integrating those disciplines with evolutionary theory.
In a review of competing evolutionary perspectives on human behavior,
Laland and Brown see DIT as the best candidate for uniting the other
evolutionary perspectives under one theoretical umbrella.
Relation to other fields
Sociology and cultural anthropology
Two major topics of study in both sociology and cultural anthropology
are human cultures and cultural variation.
However, Dual Inheritance theorists charge that both disciplines too
often treat culture as a static superorganic entity that dictates human
behavior.[95][96]
Cultures are defined by a suite of common traits shared by a large
group of people. DIT theorists argue that this doesn't sufficiently
explain variation in cultural traits at the individual level. By
contrast, DIT models human culture at the individual level and views
culture as the result of a dynamic evolutionary process at the
population level.
Human sociobiology and evolutionary psychology
Evolutionary
psychologists study the evolved architecture of the human mind. They
see it as composed of many different programs that process information,
each with assumptions and procedures that were specialized by natural
selection to solve a different adaptive problem faced by our
hunter-gatherer ancestors (e.g., choosing mates, hunting, avoiding
predators, cooperating, using aggression).
These evolved programs contain content-rich assumptions about how the
world and other people work. When ideas are passed from mind to mind,
they are changed by these evolved inference systems (much like messages
get changed in a game of telephone). But the changes are not usually
random. Evolved programs add and subtract information, reshaping the
ideas in ways that make them more "intuitive", more memorable, and more
attention-grabbing. In other words, "memes" (ideas) are not precisely
like genes. Genes are normally copied faithfully as they are replicated,
but ideas normally are not. It's not just that ideas mutate every once
in a while, like genes do. Ideas are transformed every time they are
passed from mind to mind, because the sender's message is being
interpreted by evolved inference systems in the receiver.
It is useful for some applications to note, however, that there are
ways to pass ideas which are more resilient and involve substantially
less mutation, such as by mass distribution of printed media.
There is no necessary contradiction between evolutionary
psychology and DIT, but evolutionary psychologists argue that the
psychology implicit in many DIT models is too simple; evolved programs
have a rich inferential structure not captured by the idea of a "content
bias". They also argue that some of the phenomena DIT models attribute
to cultural evolution are cases of "evoked culture"—situations in which
different evolved programs are activated in different places, in
response to cues in the environment.
Sociobiologists
try to understand how maximizing genetic fitness, in either the modern
era or past environments, can explain human behavior. When faced with a
trait that seems maladaptive, some sociobiologists try to determine how
the trait actually increases genetic fitness (maybe through kin
selection or by speculating about early evolutionary environments).
Dual inheritance theorists, in contrast, will consider a variety of
genetic and cultural processes in addition to natural selection on
genes.
Human behavioral ecology
Human behavioral ecology
(HBE) and DIT have a similar relationship to what ecology and
evolutionary biology have in the biological sciences. HBE is more
concerned about ecological process and DIT more focused on historical
process.
One difference is that human behavioral ecologists often assume that
culture is a system that produces the most adaptive outcome in a given
environment. This implies that similar behavioral traditions should be
found in similar environments. However, this is not always the case. A
study of African cultures showed that cultural history was a better
predictor of cultural traits than local ecological conditions.
Memetics
Memetics, which comes from the meme idea described in Dawkins's The Selfish Gene,
is similar to DIT in that it treats culture as an evolutionary process
that is distinct from genetic transmission. However, there are some
philosophical differences between memetics and DIT.
One difference is that memetics' focus is on the selection potential
of discrete replicators (memes), where DIT allows for transmission of
both non-replicators and non-discrete cultural variants. DIT does not
assume that replicators are necessary for cumulative adaptive evolution.
DIT also more strongly emphasizes the role of genetic inheritance in
shaping the capacity for cultural evolution. But perhaps the biggest
difference is a difference in academic lineage. Memetics
as a label is more influential in popular culture than in academia.
Critics of memetics argue that it is lacking in empirical support or is
conceptually ill-founded, and question whether there is hope for the
memetic research program succeeding. Proponents point out that many
cultural traits are discrete, and that many existing models of cultural
inheritance assume discrete cultural units, and hence involve memes.
Shortcomings and criticisms
Psychologist Liane Gabora has criticised DIT.
She argues that use of the term ‘dual inheritance’ to refer to not just
traits that are transmitted by way of a self-assembly code (as in
genetic evolution) but also traits that are not transmitted by
way of a self-assembly code (as in cultural evolution) is misleading,
because this second use does not capture the algorithmic structure that
makes an inheritance system require a particular kind of mathematical
framework.
Other criticisms of the effort to frame culture in Darwinian terms have been leveled by Richard Lewontin, Niles Eldredge, and Stuart Kauffman.
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