‘A bundle of belongings is not the only thing a refugee brings to their new country.’
The world is witnessing numerous crises, which have caused upwards of 25.9 million people to take refuge in other countries. Facing an imminent threat of violence and persecution, these refugees find a new lifeline in other countries. The countries accepting these refugees, have a mammoth task at hand and face various implications due to the influx of immigrants.
The US has played an instrumental role in light of these crises by providing refuge to around 22,500 people in 2018 itself. It is imperative for these refugees to find employment, in order to settle in and get accustomed to the new country. In an attempt to aid the chances of employment a refugee has, Stanford’s Immigration Policy Lab has come up with a Placement Algorithm designed to increase the chances of a refugee receiving employment.
The algorithm analyzes the statistical data on refugee demographics, local market conditions, individual preferences and outcomes to generate predictions that recommend an ideal location for the refugees. It also considers factors such as age, English proficiency and the size of the immigrant community in the refugee’s country. As of now, the US only allocates refugees to different areas depending on the capacity of the places to recieve them. It is believed that the algorithm which follows a model, map and match methodology, will be able to drastically affect the employment rate of refugees. The algorithm uses past data on the refugees, implements mathematical equations and eventually comes up with a location that might be apt for the refugee.
While it has not been implemented in real life, traditional methods of checking algorithms such as trials based on cases of refugee families show a promising response. The response increased the employment rate of refugees in the US from around 25% to a staggering 50%, for the median refugee.
A process wherein past statistics are used to decide where a refugee can have a higher chance of employment, the algorithm still does not take into account many other factors that could influence the rate of employment such as the social factor, as there are no past statistics present in this field of study. The fact that there are several factors that result in the well-being of refugees makes the work for the developers tougher, and they are still devising a plan to tackle these problems.
The researcher’s are already in the process of collaborating with the government to develop the algorithm, by considering more mathematical equations that could improve the results achieved. Until tried out in real life,one cannot say whether it will be successful or not, although considering the optimism around the research, one can hope that mathematics could help solve the dilemma that millions of refugees face world-wide.
Citations:
https://www.unhcr.org/figures-at-a-glance.html
https://airbel.rescue.org/projects/placement-algorithm/
https://cis.org/Rush/Refugee-Resettlement-Admissions-FY-2018
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