Matriz de consistencia

What do we know: What does Sociology bring to the table for studying the human dimensions of global climate change?

In considering the potential contribution of sociology to the study of global climate change, I start with the fact that the discipline is fundamentally concerned with people in context. Our theory, data, and tools are well suited to questions about how people respond to their local environments. And, indeed, climate change will be felt locally. The phenomenon is global, but its consequences spatially heterogeneous, and ultimately interact with characteristics of local environments in affecting the people who live there (CCSP 2008).

There is a long tradition within sociology of examining a variety of outcomes at the individual and household level within a larger context such as a neighborhood or community (Entwisle 2007; Mayer and Jencks 1989; Sampson et al. 2002) that might be readily adapted to the study of climate change impacts. In developed countries such as the United States, research has focused primarily on the effects of neighborhood poverty, racial composition, and turnover. Given appropriate measurement, it is straightforward to include measures of the biophysical environment within the general multilevel framework.

According to the latest IPCC assessment, the prevalence and severity of heat waves, cold snaps, drought, and storm-induced flooding are among the possible consequences of global climate change. Their consequences for the health and wellbeing of individuals depend on other characteristics of the natural and social environment as well as local adaptation and mitigation strategies. A recent review of multilevel studies of health showed a neglect of the biophysical environment, including features related to or potentially consequent from climate change (Entwisle 2007). An exception is a study by Browning et al. (2006), who used a multilevel approach to study heat-related mortality in the 1995 Chicago heat wave.

To incorporate features of the biophysical environment into the general multilevel framework, sociologists need to develop an understanding of local contexts as places, i.e., local sociospatial environments. A consequence of relying so heavily on survey and census data to characterize contexts is that these local environments are somehow disembodied, not rooted. To understand the consequences of climate change, or indeed to incorporate a more complete understanding of the biophysical environment more generally, requires us to “put people in place.” Most research examining the effects of local context on an individual outcome utilize social survey data. It is straightforward to geocode the locations of survey respondents and then incorporate information about the biophysical and spatial environment within a GIS. It is important to note that there are deductive disclosure risks associated with releasing the locations of survey participants, even just their zip code or county of residence (Van Wey et al. 2005).

What do we need to know: What are the major sociological research questions?

To make progress, sociologists need to broaden their conceptualization to include all dimensions of the local

context, including dimensions of the natural environment. We need to consider that risks associated with the natural environment are multiple and complex, and further, that features of social context may combine with climate-related impacts to magnify, or mitigate, those impacts. If heat-related mortality is higher in poor neighborhoods with less

commercial activity (and fewer air conditioned establishments where the elderly can find refuge), we need to also consider the possibility that the heat index is probably also higher in these places, and air pollution worse. Multilevel studies that consider multiple aspects of the local environment, even multiple dimensions of the social environment, are quite rare (Entwisle 2007). We need to think of local contexts as “places,” socially interconnected and spatially situated. We also need to consider processes embedded in contexts at multiple levels.

Climate change as reflected in changes in the environmental conditions present in specific places will undoubtedly have many outcomes. I would like to draw attention to migration. Migration is both a response to environmental change and also, by determining patterns of settlement, a factor affecting exposure to place-specific risks of climate change. Environmental factors may act as “push factors,” contributing to a decision to move out of a particular area. They may also serve as “pull factors,” shaping the desirability of particular locales as potential destinations.

If people move as a consequence of climate change, the impact will be felt locally, but elsewhere as well. For instance, international migration into the U.S. may be stimulated directly and indirectly by climate variability and change elsewhere. Environmental refugees illustrate a direct impact, but indirect impacts are likely to be even more important. Given the size and persistence of migration streams from Mexico and other parts of Central and South America, for instance, it is important to consider the possibility that climate variability and change in these regions may further increase immigration pressures. A global perspective on climate variability and change is necessary even if ultimately, the concern is with impacts within the borders of the U.S. This is true not only with respect to issues of human settlement, but also with respect to health and welfare. Climate variability and change are global phenomena and impacts outside of the U.S. may have direct consequences for social systems within the U.S.

Migration is a micro behavior with potential consequences at a macro level. When people move from place to place, they change the local context in which they are themselves embedded as a kind of a swap. These moves have consequences for neighborhoods as well, both the origin as well as the destination. Schelling (1972), Bruch and Mare (2006), and Macy and van de Rijt (2006) have studied this process from the perspective of residential segregation. Unless replaced by households similar to them, the racial/ethnic composition of a neighborhood changes as households move out. There may also be consequences for other characteristics of places such as poverty. Neighborhood turnover may exacerbate the negative consequences of climate change.

One of the “truisms” about migration is that it is selective. Migrants are positively selected from places of origin. Those leaving particular areas are generally better off than those staying. So long as those places of origin have positive qualities, those leaving will be replaced by other in-migrants. If those places of origin are undesirable as potential destinations for other migrants, however, they will become increasingly disadvantaged as out-migration continues. Climate change will have a deleterious effect on some places, and may serve to advantage others (CCSP 2008). Depending on response, social inequality may increase as a result of dynamic feedbacks in the system related to the selectivity of migration. Across multiple social and spatial scales, marginal populations may be particularly likely to be affected by climatic events, partly because of their attachment to marginal environments.

At the global level, projected impacts of climate warming show countries that are already at significant

disadvantage globally are the most likely to suffer from flooding associated with sea rise. Bangladesh is one example. At a regional level, when Hurricane Katrina struck the southern coast of the U.S., already marginalized populations were disproportionately affected. In New Orleans, the lower ninth ward was devastated and recovery has been extremely slow. The contrast with Bourbon Street is stark. In the examples just given, the joint distribution of the population with respect to environmental vulnerability and economic and social disadvantage is an important part of the story. The poor are relegated to more vulnerable locations, which in turn expose them to greater risks, which in turn make it

difficult to accumulate the resources to improve economically, and so on. Those who are better off are less vulnerable to begin with, and if disaster should strike, are in a better position to respond, and possibly move on.

Disasters large and small have the potential to exacerbate inequalities at multiple levels. Little is known about such dynamics, partly because they are not well suited to standard analytic approaches. The feedbacks undermine the assumptions of multiple regression, especially that the disturbance is unrelated to the included predictor variables. The usual “fixes,” for example the use of instrumental variables, do not work because of the interconnectedness of the system. Instead, sociologists are turning to microsimulation approaches such as agent-based modeling.

With these approaches, it is possible to examine the macro consequences of micro behavior, including residential mobility and migration, and the integration of micro and macro processes more generally. Through the use of “what-if” scenarios, it is possible to consider dynamic responses to climate change, including change that has not yet happened, but might happen, or may never happen. Agent-based models can link people and place by being made spatially explicit. In geography, for example, spatially explicit agent-based models have been developed to describe land use change in a variety of settings (Parker et al. 2008). Sociologists are just beginning to develop spatially explicit models, and this is an area rich with potential. Spatially explicit models of the dynamics of social inequality in the face of locally experienced climate change are a natural focus for sociologists.

References

Browning, C.R., D. Wallace, S.L. Feinberg, and K. A. Cagney. 2006. “Neighborhood Social Processes, Physical Conditions, and Disaster-Related Mortality: The Case of the 1995 Chicago Heat Wave.” American Sociological Review 71: 661-678.

Bruch, E. and R.D. Mare. 2006. “Neighborhood Choice and Neighborhood Change.” American Journal of Sociology

1121:667-709.

CCSP (Climate Change Science Program). 2008. Analyses of the effects of global change on human health and welfare and human systems. A Report by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research. [Gamble, J.L. (ed.), K.L. Ebi, F.G. Sussman, T.J. Wilbanks, (Authors)]. U.S. Environmental Protection Agency, Washington, DC.

Entwisle, B. 2007. “Putting People Into Place.” Demography 44(4):687-703.

Macy, M.W. and A. van de Rijt. 2006. “Ethnic Preferences and Residential Segregation: Theoretical Explorations Beyond Detroit.” Journal of Mathematical Sociology 30:275-288.

Mayer, S.E. and C. Jencks. 1989. “Growing Up in Poor Neighborhoods: How Much Does It Matter?” Science

243:1441-1445.

Parker, D.C., B. Entwisle, R.R. Rindfuss, L.K. VanWey, S.M. Manson, E. Moran, L. An, P. Deadman, T.P. Evans, M. Linderman, M.M. Rizi, and G. Malanson. 2008. “Case studies, cross-site comparisons, and the challenge of generalization: Comparing agent-based models of land-use change in frontier regions” Accepted for publication in Journal of Land Use Science.

Sampson, R.J., J.D. Morenoff, and T. Gannon-Rowley. 2002. “Assessing ‘Neighborhood Effects:’ Social Processes and New Directions in Research.” Annual Review of Sociology 28:443-478.

Schelling, T. 1972. “A Process of Residential Segregation: Neighborhood Tipping”, Pp 157-184 in Anthony Pascal (ed.) Racial Discrimination in Economic Life. Lexington, MA: Lexington Books.

VanWey, L.K., R.R. Rindfuss, M.P. Gutmann, B. Entwisle, and D. Balk. 2005. “Confidentiality and Spatially Explicit Data: Concerns and Challenges.” Proceedings of the National Academy of Sciences 102(43):15337-42.