1. Introduction
This paper tests two hypotheses about social resilience to climate-related disasters using data from ancient societies. The paper is in no way unique in using archaeological data to examine the societal impact of natural disasters or mechanisms of social resilience (e.g., Cooper and Sheets 2012; Fisher et al. 2009; Hegmon et al. 2008; Redman 2005), but it is unique in doing so using cross-cultural comparison of ancient societies throughout the world. A strength of cross-cultural comparison using archaeological data is that it allows one to test whether or not an assumed predictive condition actually precedes its assumed effects, that is, whether a society with the predictive condition empirically changes in the predicted manner over time (Peregrine 2001, 2004; Smith and Peregrine 2012). If a predictor of social resilience to climate-related disasters can be identified and applies to societies of varying scales and complexities throughout human history, then there is good reason to believe that it can be used to create interventions applicable today (see also Cooper and Sheets 2012; Hegmon et al. 2008; Redman 2012; Redman and Kinzig 2003; Van de Noort 2011).
Social resilience as the concept used here refers to the ability of a social system to absorb disturbances while retaining the same basic structures and abilities to respond to further disturbances (see Parry et al. 2007, p. 37; also Holling 1973, p. 17). There are numerous more specific definitions of resilience or processes involved in resilience (Davidson et al. 2016). In this paper the definition used is commonly called “resistance” or “adaptability,” which refers to the capacity of a social system to “successfully avoid crossing into an undesirable system regime, or succeed in crossing back to into a desirable one” following a disaster (Walker et al. 2004). This is opposed to “transformative resilience,” which refers to the capacity of a social system “to create a fundamentally new system” following a disaster (Walker et al. 2004). A social system with adaptive resilience will tend to return to a state of equilibrium following a disaster that is similar to that which existed before the disaster (but not identical to it, as a resilient system will change to reduce future risk; see Wisner and Kelman 2015), while a social system with transformative resilience will fundamentally change its predisaster social system in order to achieve a new equilibrium state.
It must be noted that scalar issues are important to these definitions of resilience, as change is always occurring in social systems. These two forms of resilience focus on what occurs at the system level: does the system change in order to maintain fundamental social structures or are those structures fundamentally transformed in order to allow the system to continue (Redman and Kinzig 2003)? An assumption made in this paper is that adaptive resilience is preferable to transformative resilience in social systems because adaptive resilience tends to retain existing social structures and relationships (Turner 2010). Thus, adaptive resilience is the focus of this paper.
In addition, this paper focuses on catastrophic climate-related disasters—those that are caused by climatic events and disrupt an entire sociopolitical system. Disasters caused by geological processes, human-derived environmental degradation, asteroid strikes, or the like (e.g., Gunn 2000; Jusseret et al. 2013; Sheets 2012; van der Leeuw et al. 2005) are not considered here as they are not examined in the literature on the adherence to social norms (societal tightness), one of the independent variables used in the analyses. In addition, only “catastrophic” events, defined by Lorenz and Dittmer (2016, p. 37) as “devastating events which encompass entire societies” are focused on, as opposed to less far-reaching “disasters” or localized “emergencies” (Lorenz and Dittmer 2016). In the modern world a catastrophic event would be something like Typhoon Haiyan, which hit the Philippines in November of 2013, devastating infrastructure throughout the Visayan Islands, choking the economy of the entire nation, and threatening the stability of the Aquino government (Salazar 2015). In the ancient world similar impacts might be seen among states, but in the smaller-scale chiefdoms and village societies included here, a catastrophic event might be far more localized, impacting only the area of chiefly control or individual villages and their immediate neighbors. This focus on catastrophic events is due to the limitations of the archaeological and paleoenvironmental records. These are important points to keep in mind when considering the paper’s results.
The remainder of the paper provides a review of literature pertinent to the hypotheses tested and a detailed description of the methods employed to test them. Two hypotheses about social resilience to catastrophic climate-related disasters are then tested; one focused on adherence to social norms, and the other focused on political strategies. The results suggest that polities in which political strategies encourage broad political participation are more resilient than those that require tight adherence to social norms.
2. Resilience, political strategies, and societal tightness
This section briefly defines and reviews the literature pertaining to the paper’s three key concepts: social resilience, corporate political strategies, and societal tightness (see Table 1). Two hypotheses concerning social resilience to catastrophic climate-related disasters based on these concepts are introduced.
Summary of key concepts employed in the paper.
There is a vast and growing literature on social resilience to disaster. The concept of resilience has its roots in ecology and the basic idea that the ability to withstand shocks should be seen through the lens of organisms operating within a complex adaptive system (e.g., Redman and Kinzig 2003; Meerow et al. 2016). The basic concepts of resilience were first developed in a seminal paper by C. S. Holling (1973), and in the ensuing 40 years Holling’s ideas have grown into an active but extremely diverse set of specific theories about resilience (Folke 2006). Two major themes have become the subject of increasing discussion in the literature on social resilience to climate-related disasters. The first is the importance of vulnerability—that the impact of a climate-related disaster is in part socially created because societies frequently build structures (both social and physical) that exacerbate the impact of disaster (e.g., Comfort et al. 2010; Tierney 2014; Wisner et al. 2004). The second is that more flexible social structures (again, both social and physical) are more resilient to climate-related disasters than more rigid social structures (e.g., Aldrich 2012; Holling et al. 2002; Kahn 2005; Paton 2006)—a perspective that is referred to as flexibility theory in this paper for ease of discussion. Both of these themes suggest that flexibility or freedom to adapt are the key to social resilience to climate-related disasters (Hegmon et al. 2008; Redman 2005; Redman and Kinzig 2003). This is particularly true for adaptive resilience (which, as discussed above, is the focus of this paper) for flexibility is one of the features that allows societies to adapt rather than transform.
In contrast, Gelfand and colleagues (Gelfand et al. 2011; Harrington and Gelfand 2014; Roos et al. 2015) have recently put forward the hypothesis that societies facing frequent natural disasters and hazards (climate-related disasters as well as conflict and epidemic disease) will tend to develop strong social norms and high levels of intolerance to deviance. They argue that strong social norms provide societies with opportunities for greater coordination to deal effectively with disasters (Gelfand et al. 2011, p. 1101). As Roos et al. (2015, p. 14) put it, “we expect societies evolve to have stronger norms for coordinating social interaction because they are necessary for survival” in the face of either natural disasters or manmade threats (such as invasion). The author refers to this perspective as “tightness theory” in this paper for ease of discussion. Gelfand and colleagues find strong support for what the author calls the tightness theory of social resilience in a study of 33 nations (Gelfand et al. 2011), of the 50 United States (Harrington and Gelfand 2014), and in evolutionary game theory (Roos et al. 2015). However, tightness theory has not been tested in small-scale societies or non-Westphalian states nor has it been examined in the context of catastrophic climate-related disasters.
While both flexibility theory and tightness theory focus on social adaptations to dynamic conditions, they put forward contrasting ideas about the social roots of adaptive resilience to climate-related disasters. Flexibility theory envisions broad political participation, open lines of communication, and fluid mechanisms of coordination as the key to resilience. Tightness theory envisions strong norms of behavior fostering well-coordinated responses as key.
Measuring societal tightness–looseness is relatively straightforward, as the concept is well-defined and already has clear and robust measures (see the supplemental material in Gelfand et al. 2011). In tight societies, social norms—the shared expectations for appropriate social beliefs and behaviors—are rigorously adhered to, and violations are punished. Tight societies tend to be more authoritarian and have greater constraints on civil liberties than loose societies. Citizens in tight societies also display more cautiousness and self-control than those in loose societies.
As in Gelfand et al. (2011; also Harrington and Gelfand 2014), the ideas of a societal tightness–looseness continuum has a long history in anthropology and psychology. It was first develop by anthropologist Pertti Pelto (1968) to demonstrate that differences in adherence to social norms was critical to understanding variation in human cultures. Pelto (1968) hypothesized that variation in local ecology, particularly in the realm of agricultural ecology, produced variation in adherence to social norms but did not formally test this idea. Gelfand and colleagues set out to test Pelto’s hypothesis and to determine if the concept applied to modern nation states, as Pelto had only examined small-scale “traditional” societies. They found that tighter nations are more common in locations that experience more climate-related natural disasters (Gelfand et al. 2011; Harrington and Gelfand 2014), suggesting that tightness might be a key aspect of social resilience (Roos et al. 2015).
Measuring flexibility in social structures is more difficult (Lebel et al. 2006). For this paper the continuum from more corporate- to more network-oriented polities (Blanton et al. 1996) is used to measure societal flexibility [in the remainder of this paper the term “exclusionary” is used in place of network, following Feinman (2012)]. The idea that political leaders employ specific strategies to maintain and legitimate authority along a continuum from more corporate ones to more exclusionary ones was developed through efforts to explain an archaeological puzzle: when looking at ancient polities of equivalent scale and complexity there is a marked difference in the visibility of political leaders. Some ancient polities, such as those of the Sumerian empire, have leaders that are clearly identified and often glorified, even to the extent of being considered divine. Others, even contemporary ones in regular contact, such as the Harappan empire of the Indus valley (which had important ties to the Sumerian empire) are “faceless,” having no clearly identified leaders.
Blanton et al. (1996) theorized that this puzzling difference stems from the strategies leaders employ and found broad regularities that break down into a continuum with two poles. One end of the continuum is characterized by exclusionary strategies in which leaders tightly control access to political participation and legitimize their authority through a cult of personality and ties to both local and foreign elites whose loyalty they sustain through control over esoteric goods and knowledge (see Helms 1979). The other end of the continuum is characterized by corporate strategies in which leaders encourage political participation and legitimize their authority through their generosity, often displayed in feasts, and an appeal to their being first among equals (see Leach 1954).
The corporate–exclusionary model has been widely employed in archaeology and has been developed along several lines including cultural evolutionary theory (e.g., Peregrine 2012) and collective action theory (Blanton and Fargher 2008; Feinman 2016). The model has also been applied to the contemporary world (e.g., Feinman 2010) and has obvious parallels to regime models (e.g., autocratic versus democratic) used widely in other areas of the social sciences (e.g., Marshall et al. 2016; also Blanton 1998), so its application to modern societies seems appropriate. It is important to note that the corporate–exclusionary model does not describe polity types but rather a continuum of political strategies that change over time as leaders respond to different challenges and opportunities.
The corporate–exclusionary model holds an explicitly top–down view of political processes, but in doing so does not deny that a complex dialectical relationship exists in all societies between rulers and citizens nor does it assume that the perception and reality of power are isomorphic (Feinman 2016). Rather, the corporate–exclusionary model posits that the way power is wielded by authority is what shapes both how power is perceived and the manner in which power can be coopted or resisted by citizens (Peregrine 2012). And while the citizens’ perception of their access to power is important, it is virtually impossible to “see” archaeologically (Fargher 2016). What we can see is the degree to which leaders allow or limit access to political decision-making, and that is the key variable employed here to measure social flexibility.
The link between participation in political decision-making and social flexibility is well-established in the disaster resilience literature through the concept of “participative capacity.” Participative capacity refers to the ability of local actors to influence decision-making (Lorenz and Dittmer 2016, p. 47–48). As Redman (2005, p. 72; also Redman and Kinzig 2003) put it, “management has to be flexible, working at scales that are compatible with the scales of critical ecosystem and social functions.” Because those scales range from local to societal, participation has to be equal at all those levels. A key element in participative capacity is control and flow of information. In more resilient social systems horizontal (i.e., between individuals operating on similar scales) information flow appears more important than vertical flow so that control of information at high levels in a hierarchical system may lead to less resilience (Redman and Kinzig 2003). Because key definitional elements of the corporate–exclusionary continuum focus on both these features—participation in decision-making and control over information and material flows—it would seem that the corporate–exclusionary continuum should be a good proxy measure for societal flexibility.
It should be noted that these hypothesis are rather specific. They focus only on catastrophic and climate-related disasters. They do not take into account potential differences in vulnerability among the societies that are tested nor disasters that are small scale or involve nonclimatic events. These are limitations, but they are necessary to match the manner in which the second hypothesis was tested in the literature on modern nations (Gelfand et al. 2011; Harrington and Gelfand 2014) and the available archaeological and paleoenvironmental records. On the other hand, the hypotheses themselves require evaluating whether preexisting social conditions impact resilience, which itself can be taken as a measure of vulnerability (Wisner et al. 2004).Hypothesis 1: Societies with more corporate political strategies are more resilient to catastrophic climate-related disasters.
Hypothesis 2: Societies with tighter adherence to social norms are more resilient to catastrophic climate-related disasters.
3. Methods
This section provides a detailed description of the sample, coding methods, and variables used in this study. The detail is necessary because these methods may be unfamiliar to readers who are not cross-cultural researchers and because the sample is unusual even for those who regularly conduct cross-cultural research.
a. Sample
The sample used here requires some preliminary explanation. Because this study is focused on social resilience to climate-related disasters, the sample is one based on climate-related disasters rather than disasters involving geological processes, human-induced environmental degradation, or the like. It is important to note before continuing that what is being termed a disaster in this study is what would be termed a catastrophe in the disaster resilience literature, that is, an event or series of events that lead to societalwide disruption rather than a smaller-scale disaster or emergency (Lorenz and Dittmer 2016). Within the archaeological context this may reflect a period of repeated climate-related disasters (e.g., sequential years of drought or flooding) and not just a single event. Not all societies have experienced catastrophic climate-related disasters, and not all of those have been the focus of archaeological research that could provide adequate data for examining adaptive social resilience, so the sample had to be selected based on specific criteria rather than on random sampling. Those criteria were 1) a specific region or site that has been the focus of extensive archaeological research; that 2) has been subjected to at least one catastrophic climate-related disaster that can be clearly identified in both the geological and archaeological record (and, again, what is visible in the archaeological and geological record is often a time period of repeated climate-related disasters rather than a single catastrophic event); and that 3) is spatially and culturally distinct from other cases in the sample in order to minimize the likelihood of autocorrelation (a formal analysis of autocorrelation effects could not be conducted here because the linguistic data normally used as a control is lacking for most archaeological cases).
To address the first sampling criterion preference was given to cases included in eHRAF Archaeology (http://ehrafarchaeology.yale.edu/ehrafa/), a repository of primary and secondary source documents that have been indexed for content to the paragraph level and thus provides rapid access to specific information in the repository documents. To address the second sampling criterion, only cases that have been discussed in the archaeological literature as having been subjected to one or more catastrophic climate-related disasters were considered (except for the Ontario Peninsula and northern Europe, which were chosen as a control cases for the analyses). And, to address the third sampling criterion, cases were sought from different culture areas of the world. Because the cases are from different culture areas and are spatially segregated, autocorrelation should be minimized (again, a formal test could not be conducted using a linguistic control, and a test employing location as a control is unnecessary as the cases are so distant from one another). In the end, 22 distinct catastrophic climate-related disasters impacting societies in nine regions were selected for coding (Fig. 1). Individual cases coded consisted of those archaeologically known societies inhabiting a specific region impacted by the disaster, with one case representing the time period within 100 years before the disaster and another representing the time period within 100 years after the disaster (only the period preceding the disaster is analyzed in this paper, as predictive conditions are the focus of this paper). The sample cases are listed in Table 2, which also lists the focal communities and time periods as typically defined in local chronologies (the time periods coded are within these local chronological periods) and the catastrophic climate-related disasters that impacted the cases.
Location of focal regions coded for social resilience to catastrophic climate-related disasters: 1) Ontario Peninsula, 2) American Bottom, 3) Gila River valley, 4) Petén, 5) Moche River valley, 6) Denmark, 7) upper Nile valley, 8) Khabur River valley, and 9) Indus River valley.
Citation: Weather, Climate, and Society 10, 1; 10.1175/WCAS-D-17-0052.1
List of cases coded with natural disasters, dates, and supporting sources; focal communities and general time periods; and associated eHRAF files. Focal communities include both the specific site and related sites in the area surrounding it. General time periods refer to periods in the local chronology, but coding was restricted to the 100-yr period prior to and 100-yr period following the listed disaster dates.
b. Coding process
Coding followed the general protocol used in most cross-cultural research (Ember and Ember 2009). Developing the codebook was done in an iterative fashion. All measures were pretested against sample cases, tested for reliability, and revised until reliable codes and a clear coding protocol were achieved. A total of 163 variables were coded, though only a small number of them are used in the analyses presented here. The final edition of the codebook, along with the coded data, is archived at the Human Relations Area Files (HRAF) Advanced Research Center (http://hrafarc.org/).
The coding process itself was done on electronic forms (also archived at the HRAF Advanced Research Center) by students who had been trained for the task but were unaware of the hypotheses to be tested (naïve coders in the terminology of cross-cultural research). Coders were kept unaware of the hypotheses so that they could not, consciously or unconsciously, bias their coding in the direction of the hypotheses. The author trained the coders by first explaining the concepts behind the code and defining key terms. Each coder then independently coded a case on a selected variable or set of variables and then met with the author to compare them. The coders frequently agreed, but where there were differences the author worked with the coders to refine their understanding of the concepts upon which the variable focused. Through this iterative process the coders developed a reliable protocol to ensure they were each coding the variables in the same way.
To further ensure accurate coding, each variable was independently coded by two coders who first read through documents in eHRAF Archaeology on a focal site or region and time period as specified for a given case, then copied passages relating to each variable in the codebook, and arrived at a preliminary code. The coders then met to identify disagreements in coding, and when disagreements were found, they read through each other’s collected passages to determine if they missed some information. Usually the coders came to an agreed code based on their combined reading and recording of the source materials. When they did not, the variable was coded as having missing or conflicting data (in rare instances the coders agreed on a resolved code to which one or both disagreed but that both agreed should not be coded as missing or conflicting).
It is important to note that coders were only to use data for the focal region during the focal time period, which was the 100-yr period before or the 100-yr period following a given climate-related disaster. There were rare occasions where data were not available within that narrow range, and in those cases the focal time period was expanded to include the time periods typically used within a local archaeological chronology. Similarly, focal regions did not always have sufficient data to code all the variables, and the rare cases when additional data were required coders were allowed to look at nearby sites with better data on the variable being coded. The assumption is that these expansions of focal dates and regions added random error to the coded data rather than any systematic bias, as each coder decided individually when to look beyond the focal region and time period, so they were not systematically altering a case’s parameters.
c. Variables
Two independent variables were derived from the raw coded data. The first is the looseness–tightness index, which measures the degree to which a society has strongly enforced social norms (Gelfand et al. 2011; Harrington and Gelfand 2014). The index used here was constructed in consultation with Gelfand and is calculated as the average standardized scores on the six variables listed in Table 3. The first two variables are intended to be proxy measures for the potential number of social norms present in a given society. The remaining four variables are intended as direct material indicators of the degree to which there appears to be adherence to social norms. It is expected that societies with lower scores on this index tend to have fewer strongly enforced norms and greater tolerance for violations of them. Societies with higher scores are expected to have more strongly enforced norms and less tolerance for violations of them.
Looseness–tightness index codes. Community integration and community ceremonials were coded following the coding details in Murdock and Wilson (1972); for the other variables unstandardized implies that the range of variation extends far beyond a basic set of forms or types; moderately unstandardized implies that while most items follow a basic set of forms or types, they are also routinely altered or personalized to create a relatively large range of variation within those basic forms or types; moderately standardized implies that basic forms or types are generally followed, albeit with variation caused by individual manufacture or preference; standardized implies strong adherence to basic forms or types with relatively little variation.
The second independent variable is the corporate–exclusionary index, which measures the degree to which the political agents control access to political authority (Blanton et al. 1996; also see Blanton 1998; Fargher 2016). The index was constructed as the average standardized scores on the five variables listed in Table 4 and is described in more detail by Peregrine (2008, 2012) and Peregrine and Ember (2016). In brief, the index measures the degree to which political agents encourage or discourage political participation and interaction with external polities. In more corporate societies, which score lower on the scale, agents encourage members of the society to participate in political activities, share authority broadly, and allow greater interaction with outsiders. The opposite is true in more exclusionary societies, where agents control access to political authority, share it only among a small group of peers, and prevent most members of society from interacting with outsiders. The index measure for the corporate–exclusionary continuum employed here has been used to code archaeological data in several previous research projects that have produced statistically robust results (Peregrine 2008, 2012, 2017; Peregrine and Ember 2016).
Corporate–exclusionary index codes. These variables were coded following coding details given in Peregrine (2012).
The indexes comprising the two independent variables are statistically robust. The looseness–tightness index has an alpha of 0.863 (six items), and all the variables that compose it correlate to a single factor explaining 61% of the variance. The corporate–exclusionary index has an alpha of 0.978 (five items), and all the variables that compose it correlate to a single factor explaining 92% of the variance. It is interesting to note that the two indexes correlate (r = 0.844, p < 0.000), although not entirely surprising. One of the features of more exclusionary political strategies is control over prestige objects and symbols of power. This control would translate, in the material record at least, into the appearance of greater adherence to social norms. However, the indexes separate into two factors with little overlap following varimax rotation, suggesting that they do tap into somewhat different societal properties.
The dependent variables reflect the social impact of a specific catastrophic climate-related disaster on seven areas: population, health and nutrition, conflict, household organization, village organization, regional organization, and communal ritual, all coded on a three-point none–some–much scale. These were coded based on the change observed in related variables coded for the time period before the climate-related disaster versus those for the time period following. Greater stability in the dependent variables is assumed to indicate adaptive resilience, following the definition presented earlier. It should be noted that these variables were originally coded on a five-point scale from significant decrease to significant increase, thus identifying the direction of change rather than simply whether or not change occurred. The variables were recoded into the three-point scale used here because 1) a number of the relationships turned out to be curvilinear, and recoding solved this issue, and 2) since the hypotheses are related to stability and not the direction of change, the recoding did not impact the hypothesis tests, and indeed may be more appropriate than the original coding.
As discussed above, climate-related disasters were coded as reflecting either individual events or periods of repeated disasters resulting in catastrophic impact. Despite considerable work in reconstructing paleoclimate and paleoenvironment (e.g., Coats et al. 2015; Cook et al. 2016; Rein et al. 2005; Stahle et al. 2016), there remains much work to be done to link specific events with the archaeological record (but see, e.g., Douglas et al. 2015; Hegmon et al. 2008; Macklin et al. 2013; Medina-Elizalde and Rohling 2012; Munoz et al. 2015; Sandweiss et al. 2009; Weiss 2000). For this reason it was from the archaeological literature that many of the climate-related disasters were identified. These disasters are commonly discussed in the framework of settlement interruption or destruction or of large-scale community and regional reorganization. Thus, the variables chosen to describe the impact of climate-related disasters map onto what are often the archaeologically identifiable features of such disasters.
One might be appropriately concerned that identifying climate-related disasters in this way would create a self-fulfilling prophecy—that climate-related disasters cause changes in social organization that are, in themselves, the things that lead archaeologists to identify climate-related disasters—but that concern is not wholly warranted. Each case where a climate-related disaster was suggested in the archaeological literature was independently verified through geological markers in order to be included in the sample, so these are “true” disasters, pointed at through the archaeological record but geologically confirmed. That these disasters impacted the coded archaeological cases in an obvious way is not a serious problem for this study, as the focus here is on social resilience as indicated by variation in change and the degree to which that variation can be predicted by the independent variables.
4. Results and discussion
Two hypotheses were tested using the data produced through the methodology described above. Hypothesis 1 was that societies with more inclusive and participatory political structures are more resilient when facing climate-related disasters than are societies in which leaders tightly control access to political authority. Table 5 presents the results of Pearson’s one-tailed correlations between the corporate–exclusionary index and the seven dependent variables. One-tailed correlations are employed because the hypothesized relationships are directional. There appears to be modest support for hypothesis 1. All but one of the correlations are in the expected direction, and conflict, regional organization, and communal ritual appear to be significantly more stable if a society has a more corporate political system preceding a climate-related disaster. This would suggest that having a more corporately oriented political organization tends to minimize conflict following a disaster and to preserve core structures of both regional organization and the public rituals that bond groups into social units.
Pearson’s r correlations between independent and dependent variables.
Hypothesis 2 was that societies with tighter adherence to social norms are more resilient to climate-related disasters than are societies with looser adherence to social norms. Table 5 also presents the results of Pearson’s one-tailed correlations between the looseness–tightness index and the seven dependent variables. The results of Pearson’s correlations in Table 5 indicate minimal support for hypothesis 2. Only one correlation is statistically significant, and it is in the direction opposite to that hypothesized. Indeed, all but one of the correlations are in the direction opposite to that hypothesized. One thus must reject hypothesis 2 and conclude that adherence to social norms does not appear to provide meaningful resilience to climate-related disasters.
These results suggest that societies with more inclusive political structures tend to be more resilient to catastrophic climate-related disasters in terms of internal conflict, regional organization, and community ritual. These results support the basic tenants of flexibility theory (e.g., Lebel et al. 2006; Norris et al. 2008). On the other hand, the results do not offer much support for tightness theory, at least as applied to catastrophic climate-related disasters. This is somewhat surprising, as tightness theory has been empirically supported through studies of 33 nations and of all 50 of the United States (Gelfand et al. 2011; Harrington and Gelfand 2014). There are, however, a number of reasonable explanations for these differing results. First, this study and the two conducted by Gelfand and colleagues are on different scales; this study examines a much longer time scale and a much wider range of societal forms. As pointed out by Davidson et al. (2016), strategies of resilience may differ between domains of impact (i.e., urban or community versus socioecological), and Lorenz and Dittmer (2016) argue that different scales of impact (i.e., societal wide versus community) may also require different strategies of resilience. It may also be that tightness provides more social resiliency in Westphalian nation-states but does not do so in smaller-scale societies and archaic states.
A second explanation for why this study and those by Gelfand and colleagues come to different conclusions is because this study focuses on catastrophic climate-related disasters rather than the more episodic ones used in the tightness studies. Gelfand and colleagues focus on climate-related disasters of much smaller scales than the ones considered here. The disasters they consider are such things as floods, tornadoes, droughts, and the like, which might impact individual communities or regions within a society but do not have societalwide impact (see Harrington and Gelfand 2014, p. 7992; also Lorenz and Dittmer 2016, p. 37). So, what may be reflected in these results is that flexibility provides greater social resiliency to catastrophic climate-related disasters while tightness provides greater resiliency to smaller-scale disasters. This itself is an interesting finding and warrants further investigation. While the archaeological and paleoenvironmental record may preclude systematic testing of the relationship between the corporate–exclusionary index and smaller episodic disasters and emergencies, the tightness–looseness index can be examined in relation to recent catastrophic climate-related disasters to determine if the results of this study are replicated in modern nation-states.
In any case, the conclusion that societies with more inclusive political structures are more socially resilient to catastrophic climate-related disasters must be received cautiously for at least two reasons: First, the sample size is small, and given the limitations created by the sampling criteria, it is entirely possible that the sample represents an atypical segment of the range of variation in societies that have experienced catastrophic climate-related disasters. Second, despite our best efforts to create a strict protocol, the concepts coded do not always have unambiguous archaeological indicators, and thus the variables coded were, of necessity, coarse-grained. With these problems one would assume the resulting data would contain considerable random error. Being random, however, this error is unlikely to have created a false relationship between two variables (type II error) but rather make it more difficult to find true relationships (type I error). Thus, one would expect that finding support for hypothesis 1 would be difficult given the coarseness of the data. But support was found for some of the variables, and for that reason the coarseness of the data may not have been as serious a problem as anticipated (although it may have prevented the identification of relationships in the other variables), or the relationships are so strong that the random error inherent in these coarse data did not mask them (cf. Loken and Gelman 2017).
While there are obvious problems in the methods and data employed here, the potential of cross-cultural research using the archaeological record far outweighs those problems, for in cross-cultural research we have a powerful method through which archaeology can be made obviously relevant for understanding, and perhaps addressing, contemporary social problems (Hegmon et al. 2008; Sheets 2012). Because diachronic comparative archaeology allows one to test causality across a range of cases, one can reasonably assume that the results are generalizable to many historical and cultural contexts. Not only does this provide a powerful test for the various theories about social resilience, but it also provides an excellent foundation for policy decisions, as results are likely not restricted to a particular time or place but reflect more general patterns of human behavior, patterns that can be employed as the basis for both evaluating general hypotheses and for developing practical interventions. The archaeological record has not ordinarily been examined in such a way that it will produce such generalizable conclusions to support both basic research and policy development (but see Cooper and Sheets 2012; Fisher et al. 2009; Hegmon et al. 2008; Van de Noort 2011). Beyond adding to our understanding of social resilience, my hope is that this project may lead others to explore historical questions with policy implications in a manner that produces generalizable results.
5. Political participation and social resilience
Two hypotheses concerning social resilience to catastrophic climate-related disasters were tested in this paper. Social resilience was defined as adaptive, in which existing social structures and relationships are able to absorb the disaster’s shock and to alter in ways that will prevent future shocks from destroying existing social structures and relationships. Support was found for the hypothesis that societies in which leaders encourage broad political participation are more resilient than those whose leaders suppress political participation. No support was found for the hypothesis that societies with tighter adherence to social norms are more resilient than those with looser adherence.
Humans have faced catastrophic climate-related disasters many times, and because of climate change it is likely that we will face such disasters within the time scale of this study (100 years). The results of this study suggest that to become more socially resilient to the catastrophic climate-related disasters we can anticipate developing through climate change, societies should promote policies that encourage citizens to actively participate in governance and decision-making (Lebel et al. 2006). Such policies would appear to provide greater flexibility in decision-making, the ability to communicate information and responses at appropriate scales, and perhaps to provide the entire response system with a broader range of knowledge to guide decisions (also see Brugger and Crimmins 2015; Dilling et al. 2015; Heijmans 2004; Norris et al. 2008, p. 142–144). This flexibility appears to have fostered social resilience in ancient societies at a variety of scales and in a variety of socioecological contexts, and thus there appears to be no a priori reason to assume that this would not be true for contemporary societies. Policies that increase political participation and communication across all social scales should be promoted by those seeking to foster a world more resilient to the catastrophic climate-related disasters expected in the next century. What might such a polity look like in practice?
A modern polity with leaders who employ corporate political strategies would promote a collective ideology (Peregrine 2017; see also Fargher 2016; Feinman 2016; Thaker et al. 2016). Such an ideology might look something like the Trump administration’s “America First” policies or the more widespread nativism movements occurring around the developed world. But nationalist or nativist rhetoric can itself lead to conflict, so promoting these would not be a desired way to promote collectivism. More appropriate would be appeals to common goals rather than to common backgrounds, languages, or cultures. Promoting common goals provides the opportunity for all members of the polity, whether native or not, to participate in a collective effort. Such efforts are often seen in the wake of climate-related disasters, as citizens from across a polity come together to aid survivors. These efforts can persist through social service organizations such as churches, shelters, food pantries, and the like. Promoting a collective ideology would promote membership in these types of organizations and provide incentives for those who join them.
Leaders who employ corporate political strategies would also work to provide opportunities for political participation to all members of the polity (Peregrine 2017; see also Fargher 2016). True democracies do this through the process of voting and the opportunity for any citizen to run for office, though in practice there are always limits to participation in this way (Arnstein 1969). More important might be open discussion forums in which all members of the polity can have input into decision-making. This, too, is a feature common to many democracies. Less common are opportunities for government agencies to open their doors and educate the public about their purpose, operations, and needs. Providing two-way information channels at appropriate levels (i.e., local government agencies to local citizens) would allow government agents to participate with citizens and encourage participation and understanding across the government–citizen divide. Leaders promoting political participation would promote such dialogues and create formal mechanisms through which such dialogues would build a partnership between citizens and government, or even pave the way toward citizen control (Arias et al. 2016; Arnstein 1969; Brugger and Crimmins 2015; Brunner 2014; Delica-Willison and Willison 2004).
Interestingly, this corporate polity would look much like the one envisioned by current scholars and practitioners of disaster response and management. In the wake of Hurricane Katrina, these scholars and practitioners began rethinking the established “command and control” approach to disaster response (e.g., Handmer and Dovers 2007; see also Baker 2016) in favor of one that gives more weight to local actors, initiatives, and organizations, particularly those that encourage local engagement in decision-making (Cretney 2016; Ferguson et al. 2016; Norris et al. 2008). As Cretney (2016, p. 37) puts it, this approach encourages “relationships between community organizations and higher-level governance institutions that allow for communities to take some level of ownership and control” over disaster response. The findings presented here support this approach to disaster response. Similarly, current literature on the sociocultural aspects of disaster resilience suggests that “social capital” in the form of such things as community empowerment, collaboration, and appreciation of diversity are important facets of social resilience (Gil-Rivas and Kilmer 2016; Kasdan 2016; Thaker et al. 2016; Wisner and Kelman 2015; Yoon et al. 2016). While not directly tied to corporate political strategies, these concepts are related. As Gil-Rivas and Kilmer (2016, p. 1323) explain, in order to build resilience, “participation in decision-making and planning processes is critical…community members (both leaders and residents) need to have meaningful involvement.” Such involvement is at the core of societies with more corporately oriented political strategies. Thus, this study serves as an empirical confirmation of the potential efficacy of current approaches to disaster response policy and practice in minimizing the impact of the catastrophic climate-related disasters we can anticipate climate change will produce in the next century.
Acknowledgments
Research presented here was conducted as part of the Natural Hazards and Cultural Transformations project funded by the National Science Foundation (Award SMA-1416651) and supported through the HRAF Advanced Research Center (hrafARC) at Yale University. The author wishes to thank the hard-working students who coded the data used here: Joseph Bazydlo, Megan Davidson, and Kristina Verhasselt. The author also wishes to thank Carol R. Ember, Michele Gelfand, Eric Jones, and Ann Kinzig for their comments and criticisms on earlier drafts of this paper. The author must further thank the three reviewers and the editor of Weather, Climate, and Society, who provided among the most insightful and pragmatic comments the author has ever received. As always, any flaws or errors the reader might find remain solely my own.
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