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dc.contributor.authorIyer, N
dc.contributor.authorMenezes, R
dc.contributor.authorBarbosa, H
dc.date.accessioned2024-09-17T11:56:28Z
dc.date.issued2024-07-17
dc.date.updated2024-09-17T11:24:19Z
dc.description.abstractWith trends of urbanisation on the rise, providing adequate housing to individuals remains a complex issue to be addressed. Often, the slow output of relevant housing policies, coupled with quickly increasing housing costs, leaves individuals with the burden of finding housing that is affordable and in a safe location. In this paper, we unveil how transit service to employment hubs, not just housing policies, can prevent individuals from improving their housing conditions. We approach this question in three steps, applying the workflow to 20 cities in the United States of America. First, we propose a comprehensive framework to quantify housing insecurity and assign a housing demographic to each neighbourhood. Second, we use transit-pedestrian networks and public transit timetables (GTFS feeds) to estimate the time it takes to travel between two neighbourhoods using public transportation. Third, we apply geospatial autocorrelation to identify employment hotspots for each housing demographic. Finally, we use stochastic modelling to highlight how commuting to areas associated with better housing conditions results in transit commute times of over an hour in 15 cities. Ultimately, we consider the compounded burdens that come with housing insecurity, by having poor transit access to employment areas. In doing so, we highlight the importance of understanding how negative outcomes of housing insecurity coincide with various urban mechanisms, particularly emphasising the role that public transportation plays in locking vulnerable demographics into a cycle of poverty.en_GB
dc.identifier.citationVol. 13(1), article 49en_GB
dc.identifier.doihttps://doi.org/10.1140/epjds/s13688-024-00489-8
dc.identifier.urihttp://hdl.handle.net/10871/137477
dc.identifierORCID: 0000-0002-3927-969X (Barbosa, Hugo)
dc.language.isoenen_GB
dc.publisherSpringeren_GB
dc.relation.urlhttps://data.census.gov/en_GB
dc.relation.urlhttps://evictionlab.org/eviction-tracking/en_GB
dc.relation.urlhttps://data.sfgov.org/Housing-and-Buildings/Eviction-Notices/5cei-gny5en_GB
dc.relation.urlhttps://data.cityofnewyork.us/City-Government/Evictions/6z8x-wfk4en_GB
dc.relation.urlhttps://lehd.ces.census.gov/data/lodes/en_GB
dc.relation.urlhttps://github.com/nandini10/Housing-Insecurityen_GB
dc.rights© The Author(s) 2024. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/en_GB
dc.subjectHousing Insecurityen_GB
dc.subjectHuman Mobilityen_GB
dc.subjectTransit Networksen_GB
dc.subjectCommuting Patternsen_GB
dc.subjectSocial Mobilityen_GB
dc.titleThe role of transport systems in housing insecurity: a mobility-based analysisen_GB
dc.typeArticleen_GB
dc.date.available2024-09-17T11:56:28Z
dc.identifier.issn2193-1127
exeter.article-number49
dc.descriptionThis is the final version. Available on open access from Springer via the DOI in this recorden_GB
dc.descriptionData availability: The census and geographic data datasets analysed during the current study are available at https://data.census.gov/ The eviction datasets analysed during the current study are available, for most cities, are available at https://evictionlab.org/eviction-tracking/. The eviction rates for San Francisco and New York can be found at https://data.sfgov.org/Housing-and-Buildings/Eviction-Notices/5cei-gny5 and https://data.cityofnewyork.us/City-Government/Evictions/6z8x-wfk4, respectively. The commuting datasets analysed during the current study are available in the LODES7 repository, https://lehd.ces.census.gov/data/lodes/ Code for reproducing the framework for identifying census tracts based on their vulnerability to housing insecurity, as well as housing demographics’ employment hotspots is available at https://github.com/nandini10/Housing-Insecurityen_GB
dc.identifier.eissn2193-1127
dc.identifier.journalEPJ Data Scienceen_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2024-07-01
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2024-07-17
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2024-09-17T11:55:06Z
refterms.versionFCDVoR
refterms.dateFOA2024-09-17T11:56:35Z
refterms.panelBen_GB
refterms.dateFirstOnline2024-07-17


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© The Author(s) 2024. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit
to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The
images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise
in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright
holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/
Except where otherwise noted, this item's licence is described as © The Author(s) 2024. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/