Family-to-family child migration network of informal adoption in China

Informal adoption, where children are adopted without official registration, is a significant yet understudied social phenomenon in China. Unlike formal adoptions, informal adoptions lack legal protection and monitoring, leaving children vulnerable to abuse and exploitation. The ambiguous nature of informal adoption frequently confounds it with child abandonment and trafficking, hindering research efforts. This lack of clarity has resulted in inconsistent legal judgments and limited understanding of the actual processes and patterns involved. This study aims to address this gap by leveraging data from a large-scale public welfare website, 'Baby Coming Back Home,' to analyze the geographic and sociological characteristics of informal adoption in China. The researchers seek to understand how societal forces and government policies have influenced the temporal and spatial distribution of informal adoption, offering valuable insights for improving child welfare and rights protection. A key objective is to clarify the distinction between informal adoption and illegal activities like child trafficking. Understanding this distinction is crucial for effective policy interventions and for safeguarding the rights of vulnerable children.

Existing research on informal adoption in China is limited and often conflates it with child trafficking. Some studies use questionnaires to explore the practice in specific regions or among particular groups, while others employ census data or legal documents to analyze irregular child migration. However, a comprehensive, large-scale analysis of informal adoption patterns and networks remains lacking. Previous research highlights the influence of factors like China's one-child policy, economic hardship, and son preference on the phenomenon. This study builds upon this existing work by utilizing a novel data source – a public welfare website – to offer a more extensive and nuanced understanding of informal adoption in China and its intricate network structures.

The researchers employed web crawling techniques to gather data from the 'Baby Coming Back Home' website, a Chinese commonwealth forum dedicated to reuniting families separated by adoption or other circumstances. The keywords "Bao Yang" (informally adopted in) and "Song Yang" (informally adopted out) were used to identify relevant data points. Initially, 16,041 data points were collected spanning from 1924 to November 26, 2018. Data points not meeting the study's definition of informal adoption (including legal adoptions, suspected trafficking cases, missing children, and abandonment) were excluded, leaving 15,685 cases for analysis. The geographical scope included the entire territory of China. Administrative division data from the Chinese Academy of Sciences' Resources and Environment Data Cloud Platform was utilized as a supplemental base map. ArcGIS was used for spatial visualization, while UCINET and Gephi were employed for social network analysis. Key metrics included the Gini-Hirschman coefficient (Eqs. 1 and 2), measuring the geographic concentration of informal adoptions, and social network analysis indicators to explore network properties, treating provinces as nodes and migration paths as weighted directed edges. The analysis focused on understanding the temporal evolution, spatial distribution, migration patterns, and information flow networks associated with informal adoption.

The study revealed a complex interplay of factors influencing informal adoption in China. The temporal analysis divided the period from 1924 to 2018 into five stages, each reflecting specific socio-political and economic conditions. Stages I and II (1924-1978) were characterized by high rates of informal adoption driven by extreme poverty, famine, and less stringent birth control measures. Stage III (1979-1992), marked by the strict implementation of the one-child policy, saw a significant increase in informal adoptions, heavily influenced by the strong son preference. Stage IV (1993-2012) showed a decrease in adoptions, potentially due to improved living standards and reduced economic pressure. Stage V (2013-2018) reflects the impact of the two-child policy and increasing gender equality awareness, leading to a further decline in informal adoptions. The spatial analysis showed a clear concentration of informal adoptions in densely populated provinces and major cities. Henan, Hebei, and Shandong were identified as key target provinces for in-adoption. Provinces in the western region of China exhibited high rates of out-adoption. Major cities acted as hubs for both the supply and demand sides of the informal adoption network. The analysis found that the provinces with high in-adoption rates were mostly concentrated in the eastern coastal areas of China. Provinces with a large number of adoptions (normalized in-adoption number >0.50) were Henan, Hebei, Shandong, Fujian, Jiangsu and Guangdong. Chongqing, Shanghai, and Beijing emerged as key intermediary cities in the information flow network, reflecting their roles as regional economic centers and transportation hubs. The network analysis revealed that the overall informal adoption pattern resembled an “inverted T” shape, with children being transferred from central China toward the coastal regions.

This study's findings provide crucial insights into the complex dynamics of informal adoption in China. The temporal analysis highlights the significant impact of government policies and economic conditions on adoption rates. The strong correlation between the implementation of the one-child policy and a rise in informal adoptions emphasizes the unintended consequences of population control measures. The spatial analysis underscores the importance of geographical location and urban centers in shaping the adoption network. The identification of key source and target provinces provides a basis for targeted interventions aimed at protecting vulnerable children. The study's distinction between informal adoption and child trafficking, based on the gender of children involved and the age at adoption, offers a critical refinement in understanding these interconnected issues. The identification of key cities in the information flow network offers valuable targets for preventative and intervention strategies.

This research offers the first comprehensive analysis of informal adoption in China using data from a large-scale public welfare website. The findings provide detailed insights into the spatio-temporal evolution and network structure of this complex social phenomenon. The study’s analysis highlights the influence of socio-economic factors, government policies, and geographical location on informal adoption. The identification of key cities and provinces involved in the adoption network can inform the development of targeted interventions to protect children’s rights and prevent exploitation. Future research should explore the life trajectories of informally adopted children, further investigate the differences between informal adoption and child trafficking, and consider the impact of evolving family planning policies on the prevalence of informal adoptions.

The study acknowledges several limitations. The data utilized are self-reported and may contain inaccuracies or biases. The reliance on a single website might not capture the full scope of informal adoptions in China, as many families may be reluctant to share such sensitive information publicly. The study's focus on a specific timeframe and geographical region might limit the generalizability of the findings. Future research should consider using multiple data sources and methodologies to address these limitations and broaden understanding of informal adoption in China.