Modern demography seeks to characterize populations or subgroups of populations based upon statistical commonalities or differences between them. Clearly, some of these may be largely cultural (e.g., age of marriage, total fertility, socioeconomic status) or largely biological (e.g., resistance to particular strains of malaria, skin cancer risk, mean height), while others may be almost entirely cultural (e.g., knowledge of contraceptive technology) or almost entirely biological (e.g., presence or absence of particular inheritable genes). The disentanglement of biology and culture in group characteristics has proved to be complex.
While human societies are always conditioned by demographic characteristics, thinkers such as Malthus or, later, Boserup have made sweeping claims for the fundamental role of population growth as the key independent variable. Malthus, famously, argued that population inevitably grew quickly to exhaust resources regardless of the rate of growth in the latter, due to the superior power of a geometric series compared to an arithmetic one. This flawed perspective was unfortunately used as the basis for population policies biased against the poor and aimed at protecting social surpluses for the upper classes. Many have long found this claim unconvincing both in its mathematical formulation as well as in its biological, sociological, and technological naïveté. Scientific claims mixed with an uncritical stance toward the power structure unfortunately characterized demographic writing long after Malthus.
Demographers, with few exceptions, have tended to be atheoretical or uncritical, from a social science perspective, and to decontextualize variables such as mortality rates and fertility rates or even to devise demographic models purportedly applicable to many times and places. By contrast, anthropologists and historians argued throughout the 20th century for the need to recognize the complexity of the interactions between demographic, epidemiological, cultural, political, and environmental factors.
Perhaps the most influential demographic model, that of the demographic transition (introduced in 1929 but tailored to address U.S. policy objectives in 1945), is a case in point. This model uses fertility rates and mortality rates as dependent variables, differentially impacted by a variety of other factors, to explain the major demographic growth displayed by many societies since the advent of modern public health as well as the recent arrival at very low population growth levels by, for example, Germany or Japan. The demographic transition models the change from high fertility rates and high mortality rates (close to static population levels) to high fertility rates plus lower mortality rates due to public health measures (leading to longer average life spans and rapid population growth). It then charts a period of increasing prosperity and state social security policies motivating smaller household sizes, leading to another equilibrium (again roughly static population) at lower fertility and mortality rates.
The model seems to fit the trajectory followed by many modernizing countries but falls considerably short, even at the statistical level, of a universal model for industrial societies, as the significant differences between German and U.S. demographic trends in the 20th century would suggest. What it most particularly lacks is any critical reflection on the necessity or current or future desirability of conformity to such a model. Barely below the surface of the model is the Malthusian assumption that U.S. concerns about a third-world population explosion are beyond criticism and that public health, economic liberalization, democracy, and family planning efforts will have their primary justification in slowing population growth in the poorer regions of the world. Predictably, despite the historical evidence that changing economic conditions caused demographic changes in Europe, the focus for poorer countries was placed on family planning. The forced sterilization campaigns in India from the 1950s to the 1990s were linked to this policy yet supported by the Indian government. The parallels between this view and the more overtly racist views of many demographers earlier in the 20th century largely obviate the differences.
In the latter part of the 20th century, demographers moved away from the highly criticized transition theory to attempt to incorporate culture. With the exception of institutional demography, which focused on the influence of historical social institutions (family systems, community organization, patriarchy, and so on) on demographic variables such as fertility, demographers nevertheless continued to be largely Eurocentric, ahistorical, and apolitical building, on diffusion theory, a branch of modernization theory, to predict the spread of European technology for fertility control to supposedly less enlightened areas.
Demographic models by nondemographers have had different agendas. The problem of explaining historical increases in agricultural production (per unit area) led Boserup to argue that technical progress in agriculture was historically motivated by demographic pressure. Boserup proposed a universalistic model in which increasing population pressure led humans to gradually ratchet up the intensity of agriculture (equated with frequency of land use) from slash-and-burn through gradual stages to annual production, characterized at each stage by lower returns to labor (primarily due to soil exhaustion or the extra labor needed to maintain fertility). The model proposed that these diminishing returns to labor were acceptable only because higher returns per unit area were achievable and were necessitated by demographic pressure. Thus, demographic necessity was the mother of technological invention and individual maximization the driving force. Few believe matters are this simple. The ancient custom of flood recession agriculture, where nature annually renews fertility, followed a different trajectory, more easily fitting political economy models than demographic or individual maximizing ones. When irrigated agriculture obtained long-term multiplier impacts from infrastructure, this also necessitated complex political change enabling choices between long, and short-term benefits, not simple individual responses to population pressure.
If Boserup made politics a mere response to demography, Carneiro suggested that population pressure was the proximate cause of state formation. In his model, states occur where populations are circumscribed by ecology such that their eventual concentration leads to conflict, which, in turn, necessitates some form of higher organization. Provided that productivity is high, such as along navigable river systems, population growth brings ever-greater population pressure and ever-greater need for political resolution of conflict, and eventually this leads to state creation. Carneiro incorporated the idea that agricultural technology itself is relative and so levels of demographic pressure leading to conflict are themselves dependent on the capacities of the technology, as applied to the natural resources, to support population growth. While Carneiro proposed this model as a general theory of state formation, subsequent archaeological work has not sustained its specific premise that population pressure preceded the development of hierarchy, nor its general claim for the foundational role for population circumscription and demographic pressure in state formation.
A contextualized historical demography brings specialized techniques that social scientists in many fields rely on to understand both human and animal populations. Ratios of males to females and age distributions can often be reconstructed and used to chart major economic and social change. Even tabulating household composition solely in terms of age and gender tells us a great deal about any society. If we add to this study of disease, nutrition, and DNA (human, animal, and microbe), also discernable from skeletal material, a vast array of insights into social structure, kinship, and migration of past societies can be gleaned from the most basic demographic materials.
Societies differ enormously in terms of the availability of ancillary materials of demographic importance, and these may vary from evidence of dwelling spaces, refuse heaps, or potshards all the way to several hundred years worth of birth and death records for each parish in a country (as in France). Surface surveys focusing on potshards in the Fertile Crescent (Mesopotamia) have provided one of the simplest reasonably reliable methods for estimating local population trends. Brinkman notes that although surface surveys are less than perfect, they provide one of the few ways to survey large geographic areas, and they exhibit enough internal consistency to support significant demographic arguments. Thus, they suggest that between 2100 BC and 625 BC, the population of lower Mesopotamia declined dramatically and did so differentially with an approximate 75% decline in the northern sector and a 25% decline in the southern regions. The same data also suggest that between 2700 BC and 625 BC a much larger percentage of the total population in lower Mesopotamia came to live in small towns and villages. These conclusions, and the associated details of regional patterns of habitation, obviously have many broad implications for an understanding of the period even if by themselves they raise more questions than they answer.
Anthropologists attempting to reconstruct historic or ancient population patterns have used demographic tools with their own research agenda without attempting a full scale rethinking of demography’s assumptions or history. Recent attempts to reconstruct the peopling of the new world exemplify research driven by the assumption that in key respects, the indigenous inhabitants of the Americas resemble populations at similar technological levels elsewhere. In an attempt to gain precision on where these peoples came from, how (mainly but not entirely across Beringia, a land bridge existing in particular periods), and when (9-13,000 BC or substantially earlier), scholars have focused on genetic markers that distinguish particular subpopulations. This first step leads directly to a consideration of the many factors that may have influenced the fertility and mortality of each subpopulation.
The actual genetic analysis is heavily weighted toward the use of statistics gleaned from geographically based studies of modern populations in the Americas or Siberia to extrapolate to degrees of historical proximity. Little serious effort has been done to model the implications of culture specific marriage patterns in the Americas or to apply such models to past demographic analysis even though statistically significant parallel or cross-cousin marriage would impact the rates of change in genetic markers carried in male or female lines.
The Atlantic slave trade and the conquest of the New World, with its huge significance in increased mortality, brought major transformations to the Americas that in some sense obscure the dynamics of indigenous demographics. Both processes have thus directly tied research into ancient demographics in the New World to similar research in the historic period beginning with the conquest. The scarcity of pre-contact skeletal remains has meant that modern populations with indigenous ancestries need to be used as proxies. This raises many issues, since most Native Americans have their own origin stories, do not subscribe to an Asian origin, and view the enterprise as potentially weakening remaining rights to land.
While demographers and physical anthropologists now regularly use sophisticated statistical and biological techniques to study health, disease, migration, and nutrition among different populations, many social scientists still view the field with lenses colored by a perception of the field’s history of apolitical or even overtly racist research. The modern preoccupation of private insurance companies with eliminating risk has raised a modern concern about the potential misuse of demographic statistics. This touches on the more general issue of human subjects protection within academia and the very real difficulties and risks, including legal risks to researchers, associated with collecting large databases of DNA even for the most worthy of causes. It may become increasingly difficult to do demographic research. If this leads to critical reflection and debate on research agendas, it may have a positive outcome, while if demographic research is simply stifled, much of great value will be lost.
References:
- Crawford, M. H. (1998). The origins of Native Americans. Evidence from anthropological genetics. Cambridge: Cambridge University Press.
- Greenhalgh, S. (1996). The social construction of population science: An intellectual, institutional, and political history of twentieth-century demography. Comparative Studies in Society and History, 38(1), 26-66.
- McNicoll, G. (1994). Institutional analysis of fertility. In K. Lindahl-Kiessing & H. Lundberg (Eds.), Population, economic development, and the environment (pp. 199-230). Oxford: Oxford University Press.
- Salzano, F. M., & Bortolini, M. C. (2002). The evolution and genetics of Latin American populations. Cambridge: Cambridge University Press.
