Sampling Migrants from their Social Networks: The Demography and Social Organization of Chinese Migrants in Dar es Salaam, Tanzania.

Journal Article (Journal Article)

The streams of Chinese migration to Africa are growing in tandem with rising Chinese investments and trade flows in and to the African continent. In spite of the high profile of this phenomenon in the media, there are few rich and broad descriptions of Chinese communities in Africa. Reasons for this include the rarity of official statistics on foreign-born populations in African censuses, the absence of predefined sampling frames required to draw representative samples with conventional survey methods and difficulties to reach certain segments of this population. Here, we use a novel network-based approach, Network Sampling with Memory, which overcomes the challenges of sampling 'hidden' populations in the absence of a sampling frame, to recruit a sample of recent Chinese immigrants in Dar es Salaam, Tanzania and collect information on the demographic characteristics, migration histories and social ties of members of this sample. These data reveal a heterogeneous Chinese community composed of "state-led" migrants who come to Africa to work on projects undertaken by large Chinese state-owned enterprises and "independent" migrants who come on their own accord to engage in various types of business ventures. They offer a rich description of the demographic profile and social organization of this community, highlight key differences between the two categories of migrants and map the structure of the social ties linking them. We highlight needs for future research on inter-group differences in individual motivations for migration, economic activities, migration outcomes, expectations about future residence in Africa, social integration and relations with local communities.

Full Text

Duke Authors

Cited Authors

  • Merli, MG; Verdery, A; Mouw, T; Li, J

Published Date

  • July 2016

Published In

Volume / Issue

  • 4 / 2

Start / End Page

  • 182 - 214

PubMed ID

  • 27746912

Pubmed Central ID

  • PMC5061575

Electronic International Standard Serial Number (EISSN)

  • 2049-5846

International Standard Serial Number (ISSN)

  • 2049-5838

Digital Object Identifier (DOI)

  • 10.1093/migration/mnw004


  • eng