Poverty passport: how Spanish cities segregate foreign population in poor neighborhoods

Country/area: Spain

Organisation: elDiario.es

Organisation size: Big

Publication date: 29 Jan 2020

Credit: Raúl Sánchez, Gabriela Sánchez, Icíar Gutiérrez, Pau Rodríguez, Emilio J. Salazar, Marta Barandela

Project description:

A data analysis that relates the average income with the percentage of foreign population in more than 35,000 census precincts throughout Spain. The research showed that the most important cities of the country cities segregate immigrants into their poorest neighborhoods. The investigation revealed that urban planning and immigration policies have brought racial discrimination in access to housing for millions of migrants in Spain.

Impact reached:

This project was one of the most read of the year in elDiario.es and also one of the one that made most people suscribe and pay for eldiario.es during the year, according to our statistics. Several NGOs that work with the migrant population in Spain shared the article, highlighting the excessive segregation of migrant population in Spain. After the publication a lot of inmigrants in Spain started to shared their own stories on how they were discriminated when they tried to rent or buy a house, there where thousands of stories shared on social media that showed racial discrimination to access housing. For example: one woman reported that a person did not want to show her a house to rent because of her accent over the phone.








Techniques/technologies used:

R, Rstudio an Excel for data compiling and data analysis. We cross-checked the national census foreign-born population databases with the median income in each census section to see if there was a correlation between higher income and higher foreign population. We used Mapbox, Javascript, and Flourish for mapping and data visualization. We created a map that allows the reader to change easily between the foreing population and income view. This way, the reader could see very clearly where both maps match.

What was the hardest part of this project?

Even this investigation had thousand of registers to be analyzed the most dificult part was to create a visualization that explains this phenomena in an easy format that allowed used to understand the main pattern of the story: the higher the income level, the lower the proportion of foreign population. Of all the options we looked at, we found the one that we thought was the clearest for any reader. A slider that allowed you to see where the poorest neighborhoods were in each city and also in which building blocks there was the most migrant population.

What can others learn from this project?

This project can inspire journalists from other countries to cross census foreign population data and income data to see if this to see if this pattern is repeated in other countries. Most of european governments announce big policies to accept migrants in their countries but analizing this data in more countries could show that this policies are not doing enough to integrate migrants into the society where on basic human right as housing is being blocked by racial discrimination. 

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