Proposed SNA: Social Network Analysis as a means of impeding networks of exploitation among Tajikistani labor migrants

Introduction/Background:
I spent the last summer working for American Councils on International Education in Dushanbe, Tajikistan, as director of the Persian Critical Language Scholarship program. While working there I also conducted research on language policy in Tajikistan as it relates to labor migration.

Labor migration is an extremely important topic for Tajikistan. The country has always been the poorest in Central Asia, but the Tajikistan Civil War from 1992 to 1997 further crippled the economy and its lingering effects have continued to hamper growth and economic opportunity for Tajikistani citizens. This encourages many Tajikistanis to seek employment abroad and it is estimated that 90% of Tajikistani migrant workers find employment in Russia. Migrants choose Russia because of its visa-free regime for Tajikistani citizens (non-employment seeking visits are permitted up to 90 days), the shared history between the two countries as members of the Soviet Union, and the presence of migrant networks and communities that have existed since the time of the USSR.

Since the fall of the Soviet Union, however, knowledge of the Russian language has become less widespread in Tajikistan. Many Russian speakers left during the civil war and the education system is so impoverished that it has proved capable neither of providing necessary materials nor of implementing pedagogy to teach Russian effectively in the country’s schools. This lack of Russian language competency is a big disadvantage to the newest generation of labor migrants. It complicates their efforts to find employment in Russia and makes it more difficult for them to understand their rights and responsibilities under Russian law. This exposes them to exploitation by Russian employers and their intermediaries.

In previous social network studies, researchers (Phillips and Massey 2000)(Waldinger and Litcher 2003) have shown how social networks have been able to help migrants in the moving process and in finding jobs. Most studies performed have highlighted these positive “social capital” aspects of migrant social networks. In her paper entitled “Networks of Exploitation: Immigrant Labor and the Restructuring of the Los Angeles Janitorial Industry”, however, Dr. Cynthia Cranford showed how existing social networks could lead to negative consequences for immigrants. Her research with janitors showed that immigrants were usually exploited by intermediaries (often the same ethnic group as the workers they exploited) who were in turn put under extreme stress and pressure by an American company to provide cheap labor. Cranford found that workers with strong ties to supervisors (family member or close friend) experienced less exploitation while those with weak ties (heard about the job from a neighbor or distant relative) were more likely to be exploited.

I would like to design an SNA that would trace networks of exploitation among Tajik workers in the construction industry.

Goal: Identify exploitative avenues to finding work in Russia so that Tajik migrants can be steered towards safer alternatives. 

Questions and Methodology: Tajik migrant workers in the construction industry in Moscow, Russia would be asked who the most influential person (people) have been in helping them to find their current job in Moscow. They would also need to be asked a series of questions about their employment experience to determine if it has been exploitative. The exploitative or non-exploitative nature of the job will be recorded and added to the attribute file along with information such as their gender, age, a self-assessment of their knowledge of Russian, the region of Tajikistan they hail from, etc.

The hope is that a network would emerge of both positive and negative (exploitative) sources of information regarding employment for Tajik workers in Moscow. This information could then be communicated to newer waves of migrants as they plan their entry to Russia.