When Water Becomes Thicker Than Blood

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However, across the world, we observe important distinctions in how societies arrange familial relations. These differences have important ramifications. As a result of different family characteristics, children are brought up within varying gendered, class-based, or age-based hierarchies in the setting of their natal home. But how can we measure these differences in family organization? And what factors can we discern to offer a tentative explanation for where these differences come from? In this article, we introduce a new global dataset on historical family characteristics at the level of the ethnic group.

The original formulation of New Institutional Economics argues that the way that transaction costs and property rights are arranged is crucial to growth and development North, In this model, secure property rights and low transaction costs will lead to the efficient allocation of resources through investment in physical and human capital. However, New Institutional Economics has also spawned an interest in informal institutions which were long excluded from standard economic analysis. One element of this is the attempt to incorporate culture into economic models Guiso et al.

Cultural variation is challenging to capture empirically in large part due to its multifaceted nature. As such, it had largely disappeared from economic models as an explanatory variable in the middle decades of the 20th century. In much of the economics literature, topics of culture and the institutional determinants of development are tackled at the national level. One of our two aims in this article is therefore to introduce a global, geo-referenced dataset of societal characteristics with a focus on family organization.

Our second objective is to explore how the global distribution of family organization, specifically the existence of FCOWA, relates to a set of geographical variables: ruggedness, elevation, distance to coast, and distance to the centers of the Neolithic Revolution.

We hope that this will contribute to further understanding of why certain features of family organization occur in one place but not in another, and by doing so also give insight into the wider determinants and consequences of cultural differences. Here, we are interested in one particular element of culture, that of family organization and in particular how family organization impinges upon or empowers women. Why focus on women and family organization? For a start, the family is the key nexus of socialization. This means that family organization and gender roles are particularly likely to be passed on from one generation to the next.

Moreover, family life and the household are central to many societies and cultures, which means that they are likely to have effects well beyond the realm of the family. This has even been argued to mean that what children learn about authority and equality within their families can be seen reflected at the level of the polity Aristotle, ; Todd, , p. An important element of such power relations within familial arrangements is that of men versus women.

Blood Isn’t Always Thicker Than Water

The position of women is integrally entwined with culture. In defining a gender system, Karen Mason writes the following:. A set of beliefs and norms, common practices, and associated sanctions through which the meaning of being male and female and the rights and obligations of males and females of different ages and social statuses are defined. Gender systems typically encompass both a division of labor and stratification of the genders.

These gender systems may thus be influenced by norms and values which, in turn, are historically determined. However, an important question remains: Why do certain family organization arrangements occur in one region but not another? Important for our purposes is the distinction between functionalist, developmental explanations on one hand, and a number of slow-moving, persistent explanations on the other.


The former view basically argues that family systems change as societies develop, become wealthier, and change demographically e. Although we will also try to include developmental explanations in our analyses, our main focus is on explanations that have an important role in the persistence of family organization.

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We are particularly interested in geographical explanations. This limits our set of explanatory variables to geographical variables that go back centuries or even millennia. Several ideas have been put forward as to the deep causes of the distribution of female-friendly family arrangements. A number of scholars have identified the agricultural system of a given region as one of the underlying determinants of family organization. Goody argues that societies practicing hoe agriculture tend to transmit property land to members of the same gender in a descent group, whereas societies practicing plow agriculture transmit to descendants of both sexes.

This, in turn, affects other outcomes such as the prevalence of dowries or control of premarital sex. Others have argued that plow agriculture is detrimental to the position of women Alesina et al. Fauve-Chamoux indicates that stem families are associated with pastoral, mountainous regions. Many of these approaches boil down to geography as a fundamental explanation for societal developments related to family and women.

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In this article, we take a first exploratory look at a number of geographical characteristics which are suggested by the literature to have an effect on family systems particularly as they pertain to the position of women. These characteristics are distance to coast, ruggedness, elevation, and distance to the nearest center of the Neolithic Revolution.

Water is Thicker Than Blood

In the next section, we discuss briefly the motivation for the inclusion of each variable. The rest of the article proceeds by sketching the method of matching the family characteristics to locations and the measurement of the geographic variables. The final section concludes.

We use distance to the coast on the basis of the qualitative literature. The underlying idea is that the position of women is better in coastal areas where men are often away at sea for long periods of time as fishermen or sailors. Distance to the nearest center of the Neolithic Revolution is used as a proxy for the timing of the Neolithic Revolution.

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The argument for the effect on gender relations runs as follows; as societies shifted from a nomadic existence to one of settled agriculture more rigid hierarchies emerged between classes, generations, and men and women. Evidence for this claim has been presented by Hansen et al.

The suggestion is that societal organization prior to the Neolithic Revolution for instance, in hunter—gatherer groups was relatively female friendly, with goddess worship and associated fertility ritual paramount. This idea has received some recent support from work done on hunter—gatherer groups in the Congo and the Philippines Dyble et al.

They demonstrate that in these modern day hunter—gatherer groups, equality between the sexes is the norm, with men participating in child care and unanimous decision making the norm. Engels argued that the subordinate position of women follows as a direct result of the rise of alienable property rights which together with monogamy underpin modern civilization.

Two more variables that we explore are ruggedness and elevation. Both of which represent, to some extent, an inhospitable environment which could result in societies being isolated from larger cultural developments. Transportation in such regions is more difficult, making them hard to access. In a way, these are therefore used as measures of a later advent of such events as the introduction of agriculture or the incorporation into states Scott, However, the effect of these variables could cut both ways as isolation from wider societal security networks could force people to rely more heavily on family connections and drive the formation of joint families.

In addition, ruggedness and elevation could leave regions beyond the influence of state authority and wider societal developments. In the Ethnographic Atlas , Murdock brought together as many ethnographies as possible in such a way as to make cross-cultural comparison possible. To this end, he created more than variables which were coded from the various monographs, manuscripts, and articles consulted to allow researchers to examine how societies compared with one another in a consistent manner.

The two sources were combined by matching the ethnic groups coded in Murdock with a list of names of ethnic groups listed in the ANM Bolt, , The unmatched percentage can be attributed to changing naming practices as well as the ethnographies covering a different set of societies than covered in the ANM. Figure 1 shows which societies from Murdock we were able to match to the ANM. It highlights three important lacunas. Australia and the western part of Latin America are also frequently unmatched. Besides these specific regions with low matching rates, missing societies are fairly evenly spread across the continents.

An important exception, however, is Africa, for which coverage is very good. From this dataset, we create a composite variable to measure FCOWA this measure is described in more detail in Carmichael and Rijpma, in press. We look at a number of variables from the Ethnographic Atlas. Of course, we were also dependent on the data available in the Ethnographic Atlas. First of all, we look at descent systems as patrilineal descent could deny women status, power, and claims on inheritance. We also look at whether women have access to property, specifically inheritance rules and property transfers at marriage.

We consider patrilocal residence arrangements after marriage, arguing that the absence of nearby kin could remove the support network of the spouse in the new marriage. We look at a preference for cousin marriage to capture whether women have a choice in their marriage partner which would again mean a stronger bargaining position ideally, we would use a direct measure such as the practice of arranged marriages, but this is not in the Ethnographic Atlas.

Members of a family tend to have different power positions. Again, we use an indirect measure to capture this: The hierarchies present in complex extended households. Our final measure is the presence of kin networks or clans.

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Their expected effect is ambivalent: They could either provide support and resources, or they could constrain the decision-making freedom. This measure has been constructed through polychoric factor analysis, a dimensionality reduction technique. It tries to find a latent variable that accounts for the variation and correlation among the multiple variables. The resulting index is a linear combination of the eight variables, using weights that ensure that the index explains as much of the variation in the eight variables as possible.


Blood is thicker than water – and blood plasma is, too

More details about the procedure can be found in the Appendix and in Carmichael and Rijpma in press. Besides geographical coverage, it is also important to be aware of other limitations of the Ethnographic Atlas. In cases where there was a mismatch, the issue could frequently be traced to the choices made in coding the ethnographies.

Some nuances in the original material could easily be lost. Likewise, it was also found that substantial variation could exist within the ethnic groups described. This was especially likely for ethnic groups that were spread across a large geographical area or were observed during times of great social change.


In the analyses below, we will try to control for them indirectly. Finally, there is the issue of time. Most observations were made between and with the median in Because geography will largely be constant over time, the heterogeneity in time of observation should not cause a discrepancy between our outcome and explanations. However, it is important to remember that some societies are observed much later than others and, accordingly, some will have been influenced by global trends in family practices. In our analysis below, we try to correct for this by including a variable for the moment of observation.