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New scientific system to assess imbalances among city neighborhoods

Developed by UC3M researchers


A team of researchers from Universidad Carlos III de Madrid (UC3M), in collaboration with the Madrid City Council, has developed an instrument which analyzes the socioeconomic needs of the areas of a city and makes a ranking of the most vulnerable neighborhoods.

Nuevo sistema científico para evaluar los desequilibrios entre los barrios de una ciudad

To develop this new system, the researchers applied the analytic hierarchy process (AHP) to the realm of public decision-making—in this case, to the allocation of the Territorial Rebalancing Fund (initialed FRT in Spanish). “This innovative strategy in the sphere of public policy offers considerable advantages to the public decision-maker, one of which is the possibility of taking a wide range of opinions into account for the decision that is ultimately adopted,” say the UC3M researchers, who are from the fields of both Political Science and Computer Engineering. “The application of this methodology to such a sensitive issue allows the final decision on the allocation of the funds to be viewed as an objective result that is legitimate and valid,” they note.

The model designed for the Madrid City Council makes it possible to produce a final ranking of neighborhoods (and, as such, of districts) based on the needs identified in each of them. For the ranking, a number of relevant social and economic indicators were assessed, such as employment rates, dependency ratios, educational level, life expectancy, the condition of  infrastructure, gross income per capita, etc. “If, thanks to this system, we identify a neighborhood that has a special situation of vulnerability or rate of development lower than the rest of the city for reasons related to unemployment or education, it will appear high in the ranking and offer us a line of public action to correct that imbalance,” explained Roberto Losada Maestre, one of the researchers, from the UC3M Department of Social Sciences.

The research project, called “Diseño de nueva metodología de determinación del grado de desequilibrio de distritos y barrios y sus necesidades de reequilibrio y obtención de nuevo indicador sintético destinado a mejorar la dotación del Fondo de Reequilibrio Territorial (Design of new methodology to determine the degree of imbalance of districts and neighborhoods and their needs for rebalancing and creation of a new synthetic indicator destined to improving the endowment of the Territorial Rebalancing Fund),  has revealed which of Madrid’s neighborhoods are the most disadvantaged. This vulnerability index orders the 128 neighborhoods from highest to lowest by their rebalancing needs. In the upper echelon of the ranking are neighborhoods such as San Diego and Entrevías (Puente de Vallecas) and San Cristóbal and San Andrés (Villaverde), while places near the bottom are occupied by neighborhoods like El Plantío and Valdemarín (Moncloa-Aravaca), El Viso and Nueva España (Chamartín), Recoletos (Salamanca) and Jerónimos (Retiro).

“These results confirm the perception that most of the imbalances are concentrated in Madrid’s southern zone, although thanks to the system’s level of detail, we have identified the existence of vulnerable neighborhoods in some districts that are ranked high on economic indicators,” said Rubén Sánchez Medero, another of the researchers, from the UC3M Department of Social Sciences. For example, this is the case of the district of Salamanca, where, despite its average income of greater than 55,000 euros, there are neighborhoods that need the help of the FRT, such as Guindalera. Adelfas, in the district of Retiro,is a similar example.

In addition, this system has made it possible to confirm correlations discovered in previous research, such as the one established between “educational level and unemployment, which significantly determine the appearance of vulnerable areas where, in turn, lower values for sustainable urban development are observed,” according to the researchers.

The use of territorial rebalancing funds in urban areas that undergo unequal development has become an indispensable tool for correcting social, economic and environmental inequalities. The allocation of these funds is a complex task that must be conducted in a dynamic and changing environment where needs grow quickly and require taking an ever greater number of indicators into account.

This method might be useful for public decision-makers. Its application for the first time in Madrid opens a promising route, as it allows for greater participation of different actors in this process.  “We used a technology known in the business world as hierarchical analysis, and we applied it via artificial intelligence to an environment where it is not normally used: public decision-making. Thanks to this, it is now possible to fuse the opinions of large numbers of people, who don’t need to be experts on the allocation of budgets or indicators of development,” explained José Manuel Molina, from the UC3M Applied Artificial Intelligence Group. “In the future, we will be able to integrate the opinions of millions of people to adopt decisions based on the largest consensus possible.” In fact, the research team is planning to extend the application of the model to participatory processes that incorporate target actors (mainly citizens) in an orderly way that permits the implementation of participatory public administration models. Ultimately, it is exploring potential developments in a field where artificial intelligence and political science converge.