In
this post I explore several branches of social science theory that support the
social reactor model of settlement scaling. This is a continuation of my prior post, which explored the basis for comparing urban and village settlement
systems. Like that post, this one is exploratory in nature, and I would really
welcome feedback on these ideas. This post is a bit more academic and detailed
than most in this blog, for which I apologize. Here is an outline of the
scheme.
1. Theories of population growth and its effects
- Large-scale social consequences of population size
- Scalar stress
- Dual inheritance theory
2. Community theory
- Social interaction generates communities
- Social interaction generates successful communities
- Communities can accomplish goals
3. Urban economics
Yes,
I realize this is a motley collection of themes—some are well-worked out
theories or theoretical approaches, one is a discipline, and others are
specific research topics or claims. But as Ralph Waldo Emerson said, “A foolish
consistency is the hobgoblin of little minds.” I am not any kind of
theoretician, and I’m afraid this is the best I can do for now. Don’t like this
scheme? Then help me out; send me comments and critiques.
1. Theories of population growth and its effects
The
first group of theories focus on the role of population growth—and population
size—on society and behavior. This is a long-standing research theme in the
social sciences. I divide this area into three categories.
A. Large-scale social consequences of population size
Social
scientists have recognized the large-scale social consequence of increasing
group size for more than a century. The great sociologist Georg Simmel noted in
1898: “Every quantitative extension of a group requires certain qualitative
modifications and adjustments” (Simmel 1898:834).”
The growth of larger social groups, and the association between group size and
socio-political complexity, have been major themes in the literature on
cultural evolution in anthropology. Quantitative analysis directed at this
theme was common in anthropology in the 1950s and 1960s (Carneiro 1962; Naroll 1956), and this work even included some
early settlement scaling analyses (Cook and
Heizer 1965)!
A
popular topic of research on population change in the 1960s and 1970s was the
role of “population pressure” in generating various social changes (Cohen 1977; Spooner 1972). The resulting
consensus held that simplistic models positing population increase as the sole
cause of political change were inadequate; for example, Carneiro’s (1970) model of population growth causing
warfare, which in turn caused the rise of states, is rarely invoked now, except
as a foil or a historical note. But narrower models, focused on economic and
environmental variables—such as Netting’s (1993)
model of population pressure causing agricultural intensification in
smallholder farming—have fared better with time, even appearing in best-selling
popular science books (e.g., M.E. Smith 2016a)
(well, I hope I do sell a few copies......).
The
two relationships mentioned above—(1) group size has increased over time in
many areas of the world; and (2) group size is strongly predictive of
sociopolitical complexity—might be considered “stylized facts” in archaeology.
That is, they are well-documented relationships whose explanation has been the
subject of dispute. I am intrigued by the concept of stylized facts in
economics, and I’ll probably blog about this on Publishing Archaeology soon.
But the relevant conclusion here is that group size is important, and—in some
circumstances—has causal effects on social and economic life. This is similar
to the claims of the social reactor model, although the cultural evolutionary
models tend to gloss over specific social interactions within set places in their
pursuit of more general results. If this discussion does not seem sufficiently
“theoretical,” then I’ll invoke the “demographic-structural theory” of Jack
Goldstone (1991, 2002), further
elaborated by Turchin and Nefedov (2009).
This is a productive political-economy approach in economic history and
historical sociology that melds population increase theory with structural
models of power relations.
B. Scalar stress
Archaeologist
Gregory Johnson (1982) coined the term
“scalar stress” to refer to social stress or difficulties created by increases
in the size of a social group. His focus was on the size of the decision-making
group, and he analyzed the development of hierarchies of social decision making
as group size increases. Research on scalar stress focuses on the negative
aspects of larger social groups. The best-known archaeological example is Roland
Fletcher’s (1995) model of thresholds in
settlement size and density, caused by scalar stress. This kind of analysis of
archaeological site size continues today (Alberti
2014).
There
is a large literature in social psychology on the role of population density in
generating psychological stress (Evans 2001;
Spruill 2010), and research on the “urban health penalty”—the negative
health consequences of living in dense cities (Vlahov
and Galea 2002; Vlahov et al. 2004)—follows a similar tack. In fact, if
we step back a bit, there is a major historical line of research in sociology
on the negative effects of growing city size. This is too big a topic to get
involved in here (and I don’t know if very well......), but one element that
remains a topic of discussion after many decades is “social disorganization
theory,” concerning the negative social consequences of urban life,
particularly in large cities (Kornhauser 1978;
Kubrin and Weitzer 2003; Sampson 2004).
Scalar
stress and social disorganization theory are relevant to settlement scaling in
that they emphasize the negative consequences of life in large cities. Urban
scaling of contemporary cities shows that superlinear scaling is not only about
positive economic outputs; crime, poverty, and disease rates also exhibit
superlinear scaling (thanks to Deborah Strumsky for her nice lecture today at
ASU, reminding us about superlinear scaling of disease levels). Social
interactions in the built environment have both positive and negative
consequences.
C. Dual inheritance theory
Dual
inheritance theory is about how human genes and culture evolve separately, yet
inter-relatedly; they co-evolve. Starting with Boyd and Richerson (1985), this is now a major line of research in
anthropology and biology (Henrich 2015;
Richerson and Christiansen 2013). What does it have to do with scaling?
A major focus in dual inheritance theory is the mechanisms of cultural
transmission. How do people learn from others? How do new traits arise and
spread through a population? What are the roles of skill, teaching, prestige,
and conformity in the spread of knowledge? Many of these traits depend on
population size.
This
research is relevant to settlement scaling in its analysis of how the size of
social groups relates to technology and other cultural adaptations. No single
person in any social group has all of the knowledge needed to survive or to
reproduce the group’s culture. Successful cultures require the combined
knowledge and skills of many members. Larger groups have a greater diversity of
tools and concepts (Henrich 2015), and if
a group gets too small, it can lose effective technological adaptations
rapidly, as in ancient Tasmania (Henrich 2004).
Unfortunately,
the dual inheritance scholars have not thought much about how their models relate
to settlements and urbanism; their models lack a spatial dimension. If
technological diversity depends on group size, then perhaps larger settlements
have distinctive technological attributes compared to smaller settlements. But
the emphasis on learning and cultural transmission of dual inheritance research
does relate to the social interaction basis of the social reactor model.
2. Community theory
By
“community theory” I mean work from a political-economy perspective that
studies communities as sites of social interaction. This perspective diverges
from a common approach to communities in archaeology, in which the emphasis is
on idealist and social constructionist models that claim communities are
generated by shared meanings in people’s heads. For some discussion of these
differences, see two posts on Publishing Archaeology: here,
and here. I sometimes wish I worked in a discipline that didn’t have so
much silliness and ridiculousness taken seriously as theory.
The
three sections that follow are not distinct theoretical approaches; they are
major claims of the political-economy approach to communities. This approach—particularly
these three claims—is broadly supportive of the social reactor model of
settlements.
A. Social interaction generates communities (“connection,
not affection”)
The
dominant view in the social sciences views communities as generated from
processes of social interaction. This goes back to Emile Durkheim at least. Sociologist
Steven Brint (2001) shows different
definitions of community in a nice tree diagram:
Notice that neighborhood
groups and other social communities (lower left) are based on activities and
frequent interactions. Here is how economists Sam Bowles and Herbert Gintis (Bowles and Gintis: F420) define community:
“By
community we mean a group of people who interact directly, frequently and in
multi-faceted ways. People who work together are usually communities in this
sense, as are some neighbourhoods, groups of friends, professional and business
networks, gangs, and sports leagues. The list suggests that connection,
not affection, is the defining characteristic of a community. Whether
one is born into a community or one entered by choice, there are normally
significant costs to moving from one to another.” (p.F420)
Most
definitions of community in the social sciences are based on three factors:
social interaction, spatial locality, and some kind of common ties (Hillery 1955; Jabareen and Carmon 2010). My
definition of neighborhood—intended to be useful for archaeologists—is quite
similar (M.E. Smith 2010). Again, see my
prior blog posts for a critique of the social constructionist views of
community in archaeology (here, and here), or see my paper on quality of life (M.E. Smith 2016b).
B. Social interaction generates successful communities
Social
interaction is emphasized in a number of normative theories of successful
communities. Anthropologists and archaeologists, take note: planning and other
social scientists use the term “normative” in a very different way than it is
used in anthropology and archaeology. Normative in these other fields means
theory with an evaluative dimension; for example, theory about what makes for “good
city design” (Lynch 1981) is called
normative theory. I discuss this briefly in Smith (2011).
How
to use urban design to promote social interactions is a major component of
normative planning theory. Social interactions—with friends, neighbors, and
other residents—are seen as one of the prime indicators of successful cities
and towns. Social interaction—particularly in reference to neighborhood
physical facilities like parks, playgrounds, and pedestrian-friendly streets—is
a key dimension of social cohesion in cities (R.A.
Smith 1975). Urban planners give considerable attention to designing
neighborhoods and streets that promote interactions (Kısar Koramaz 2014). Stable neighborhoods facilitate social
interaction, which promotes social cohesion or integration (Brower 2011).
Here
are some passages from Robert Putnam and Lewis Feldstein, in their book on social
capital and successful communities in the U.S. today:
“Again
and again, we find that one key to creating social capital is to build in
redundancy of contact. … Common spaces for commonplace encounters are prerequisites
for common conversations and common debate ... Urban planning, architecture,
and technology can each fosters redundancy and multistrandedness by creating opportunities
for encounters that knit together existing ties. Because local arrays of built
space and communications technology act as ‘background structural factors’ in
most of our cases, their true importance is not always manifest.” (Putnam and Feldstein 2003:291)
C. Communities can accomplish goals
Communities
are important not just as places where people live, but also because they can accomplish
tasks and get things done. The great social scientist Charles Tilly (one of my intellectual
heroes) asked, “Do communities act?” (Tilly
1973). He was discussing the ways in which communities in early modern
France applied resources toward common goals. This line of analysis has
continued in several branches of the social sciences. Bowles and Gintis, for example,
note that communities can solve problems that are difficult for markets or
states to solve. See their typology, based on the differing types of social
relations that characterize the three kinds of institution:
Bowles
and Gintis (2002:F422-F423) state:
“communities
solve problems that might otherwise appear as classic market failures or state
failures: namely, insufficient provision of local public goods such as
neighborhood amenities, the absence of insurance and other risk-sharing
opportunities even when these would be mutually beneficial, exclusion of the
poor from credit markets, and excessive and ineffective monitoring of work
effort. Communities can sometimes do what governments and markets fail to do
because their members, but not outsiders, have crucial information about other
members’ behaviours, capacities, and needs. Members use this information to
uphold norms.”
The
ability of communities to act—effectively and with positive outcomes—is at the
heart of the work of Elinor Ostrom (1990, 2005).
One of her basic arguments parallels precisely the argument of Bowles and
Gintis: local communities can manage common-pool resources more successfully
and sustainably than either states (government ownership) or markets
(privatization). Here is her basic model:
Notice
the role of face-to-face communication on the left side. Basic social
interactions within a community promotes trust, reputation and reciprocity.
The
upshot of this perspective on communities is that social interactions in a
specific spatial locale have a variety of positive effects for residents. These
effects are felt on both the individual and the group levels. To these basic
findings of social science research, the social reactor model of settlement
scaling adds two things: (1) social interactions in a given built environment
have an even wider range of specific outcomes than social-science research
might suggest; and (2) they exhibit a surprising level quantitative regularity.
3. Urban economics
I’ve
just about run out of steam here. I guess that’s a convenient excuse to avoiding
talking about a discipline I know little about. So let me just cite an article
that not only has a fantastic title—“Buzz”—but also provides an excellent
introduction to the role of face-to-face interaction in cities (Storper and Venables 2004). And I will close
with two brief quotes from urban economist Edward Glaeser’s excellent book, The Triumph of Cities (Glaeser 2011):
“The
central theme of this book is that cities magnify humanity’s strengths. Our
social species’ greatest talent is the ability to learn from each other, and we
learn more deeply and thoroughly when we’re face-to-face.” (p.250)
“Cities
enable the collaboration that makes humanity shine most brightly. Because
humans learn so much from other humans, we learn more when there are more
people around us.” (p. 247)
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Nice post, Mike. What are your thoughts on how to measure social vectors for wholly prehistoric contexts? Archaeologists have been good at quantifying tangible urban infrastructure, but social interactions seem like the more important variable in defining urban life. Something approaching GDP/income could perhaps be calculating using certain artifact types or labor estimates for various tasks, and we could maybe get at the potential for large assemblies of people through architecture. But I don't see prehistorians picking up traces of crime, or successfully quantifying many of the artistic/aesthetic culture that make cities exciting places today. Maybe I'm not thinking creatively enough, though.
ReplyDeleteDavid - Yes, the measurement of social outcomes is a methodological issue to think about. So far, our group has measured these things:
ReplyDelete- area vs. population (where population is estimated from house counts), finding the same density gradient as found in modern cities. Our medieval paper on this is just about ready for re-submission after revisions. And my student Rudy Cesaretti has a bunch of ethnographic cases with the same patterns, in his MA paper.
- house size as a measure of wealth, using aggregate house area for a settlement as a measure of total wealth. This shows superlinear scaling for some North American tribal-level archaeological cases (paper by Scott Ortman, in press), and for an Andean case as well (paper by a bunch of us, just about ready to submit).
- plaza area as a measure of something. Plaza area shows superlinear scaling with population in New Mexico pueblos, but it shows a strange (but regular) sub-linear relationship with population in two samples of Mesoamerican cities. That paper is still in the writing stage.
- infrastructure. There don't seem to be ancient cases where we can quantify infrastructure in a big enough sample to look at scaling, although Scott has a post-doc working on Roman cities who may find the information.
- volume of monumental architecture would be an obvious variable to look at, but its hard to know how to characterize it. Is this a wealth-related social output, or is it a kind of infrastructure? Or with a good sample, perhaps the scaling results could help answer that question.
Hello! Love your Blog! I am starting out and would love any pointers you could offer!:) Thanks anyway!:) http://merelyanarm.blogspot.com/
ReplyDeleteA Quality blog from your side about Settlement Scaling and Social Science Theory. Thank you for sharing it with us. It includes excellent stuff and the source that you have taken is very good so thank you once again for sharing it with us.
ReplyDelete