Project
Gender and Urban Mobility: Addressing Unequal Access to Urban Transportation for Women and Girls
Mobility, or the extent to which one can reach a desired destination, is one of our most basic needs. Access to mobility is also a prerequisite toward human development and having access to equal opportunities. As such mobility is a complex, gendered issue that requires a multidimensional, data-driven approach to fully unpack and offer insights on the way forward for decision-makers.
Mobility, or the extent to which one can reach a desired destination, is one of our most basic needs. Access to mobility is also a prerequisite toward human development and having access to equal opportunities. As such mobility is a complex, gendered issue that requires a multidimensional, data-driven approach to fully unpack and offer insights on the way forward for decision-makers.
Info
Mobility, or the extent to which one can reach a desired destination, is one of our most basic needs. Access to mobility is also a prerequisite toward human development and having access to equal opportunities. As such mobility is a complex, gendered issue that requires a multidimensional, data-driven approach to fully unpack and offer insights on the way forward for decision-makers.
Together, The GovLab (NYU), UNICEF, DigitalGlobe, IDS (UDD/Telefonica R&D), and the ISI Foundation will seek to embrace and decode the intersection of urban mobility and gender by uniquely combining a wide range of datasets, including commercial sources of call detail records and very high-resolution satellite data. The project seeks to define the potential and limitations of a Data Collaborative, a new form of public/private partnerships that combine data and expertise to create public value. Through this Data Collaborative on Gender and Urban Mobility, we want to know: does gender play a role in the way people move in a megacity such as Santiago, and, if so, how? Is there a mobility inequality from a gender perspective? What can be done to make transport planning more gender-sensitive and inclusive? And how can we replicate the analytic model to other places and contexts?
The project has been selected among the 10 projects awarded the Data2X Big Data for Gender Challenge in September 2017.
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