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Theorizing Cross-Cultural Migrations: The Case of Eurasia since 1500

Published online by Cambridge University Press:  25 July 2017

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Abstract

In this article we plead for a less state-centered definition of migration that allows us to understand better the relationship between cross-cultural migrations and social change and social development in the long run. Therefore, we developed a method that enables us to systematically compare CCMRs (cross-cultural migrations per capita) through time and space. This CCMR method puts issues of state policies and citizenship in a much broader social context. We conclude that the presentist approach to migration in the social sciences is highly myopic, as it privileges migrations crossing state borders over internal moves, and favors migrants who have the intention to settle for good. In itself this is a legitimate choice, especially if the core explanandum is the way migrants’ long-term settlement process in another (modern) state evolves. In the more empirical parts of this article however we have concentrated on the effects of Eurasian societies since 1500 that have received migrants. Sending societies and individual migrants and nonmigrants in sending and receiving societies have been largely left out. Finally, and paradoxically, integration and assimilation in the long run leads to diminishing opportunities of social development by cross-cultural experiences, because one could argue that due to globalizing migrations cultures converge further and thus cultural boundaries (as is already the case in migration to cities within culturally homogenous nation-states in the twentieth century) become less salient or disappear entirely. Logically speaking, this is also an implication of the model, presently to be developed further.

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Copyright © Social Science History Association, 2017 
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FIGURE 1. CCMR method for a given territory and period.

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FIGURE 2. Formula to calculate CCMRs. Pi (p) denotes the probability of a person living in period p and geographical unit i migrating during their lifetime. Miperm, Mimult, and Miseas denote permanent (to cities and to rural areas), multiannual (labor migration), and seasonal cross-community, often long-distance, movements inside unit I, respectively. Miimm is the number of immigrants to unit i from outside and Miemi the number of emigrants from unit i to elsewhere. The notation Σp indicates that these migration numbers are summed over period p. Ni (p) is the average population in geographical unit i in period p. To compensate for overcounting in the migration numbers, the expression needs to be corrected by the second factor, in which Ei (p) denotes the average life expectancy in period p and Lp is the length of the period. Note that in this article we ignore the second term because we estimate Lp = 50 years ≈ Ei (p).

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FIGURE 3. CCMRs for Europe (excluding European Russia), 1501–1900.

Source: Lucassen et al. 2014: table 170.
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FIGURE 4. Migration rates, limited to urbanization and emigration in Europe (excluding European Russia), 1501–1900.

Source: Lucassen et al. 2014: table 170.
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FIGURE 5. CCMRs for Europe (excluding European Russia), 1801–2000.

Source: Lucassen et al. 2014: table 170.
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FIGURE 6. CCMRs for Europe (excluding European Russia), without TMA, 1801–2000.

Source: Lucassen et al. 2014: tables 170 and 172.
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FIGURE 7. Total net CCMRs per category for Europe without Russia, excluding migrations to cities within nation-states in the twentieth century and excluding soldiers and sailors, 1801–2000 (%).

Source: Lucassen et al. 2014: table 168.
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TABLE 1. Main stream theories aimed at explaining social change in cities

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TABLE 2. Attributing “weights” for the positive effects to the four CCMs at the collective, societal, level

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FIGURE 8. Schematic representation of the relationship between CCM and social change.

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FIGURE 9. CCMRs in Europe (without Russia), Russia, China, and Japan, 1601–1800.

Source: Lucassen and Lucassen 2014a: 31.
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FIGURE 10. CCMRs in Europe (without Russia), Russia, China, and Japan, 1801–2000.

Source: Lucassen and Lucassen 2014a: 33 and 394. European rates have been adjusted following Lucassen et al. 2014: table 170.
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FIGURE 11. Weighted CCMRs for Europe, China, and Japan 1600–2000.