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A tool for helping newcomers to Canada identify suitable communities to settle


A research project was undertaken under the aegis of Canada government and Stanford University’s Immigration Policy lab to develop a tool that might help skilled immigrants identify the Canadian community in which they are most likely to flourish and achieve economic success. The Immigration, Refugees and Citizenship Canada is planning to launch a pilot program for testing a matching algorithm that can recommend the new immigrants where to settle in Canada.
A report on the pilot project, which was quoted by the Star says, “An immigrant’s initial arrival location plays a key role in shaping their economic success. Yet immigrants currently lack access to personalized information that would help them identify optimal destinations.”
“Instead, they often rely on availability heuristics, which can lead to the selection of suboptimal landing locations, lower earnings, elevated out-migration rates and concentration in the most well-known locations,” added the study completed last summer after two years of number crunching and sophisticated modelling.
The pilot project, named as GeoMatch project, is expected to help researchers observe whether such tools can create real benefits to the economic immigrants to Canada. It would also help researchers better understand the factors that are behind the economic success of immigrants.
.Currently, most of the immigrants to Canada prefer to settle in cities. By doing so, they might be missing on opportunities flourish economically, according to the researchers. That is why the research project is aiming to help newcomers with an option for evidence-based decision making.
The project also aims to leverage technology and data for the benefit of newcomers and communities. It applies the comprehensive historical datasets of Canada regarding the background characteristics of immigrants, their economic outcomes and geographic locations to produce suggestions on where the skilled immigrant might start a new life. The technology also applies machine learning methods to find out how the backgrounds, qualifications and skillsets of immigrants were related to their taxable earnings in different cities. The research also considered factors such population and unemployment in different locations.
These models are then employed to predict how newcomers with similar profiles would perform across possible destinations and how successfully they can become financially. Then the locations are ranked on the basis of the unique profile of the person.
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