Lab's first paper in Cities is published!

Belle & Antonio’s mixed-methods paper on public perceptions and support for affordable housing now appears in Cities.

Belle & Antonio’s paper titled: In their own words: A mixed-methods exploration of public perceptions of affordable housing and their connections to support,” was recently published in Cities. This paper is a collaboration with co-author’s Deland Chan (Chinatown Community Development Center) and Prof. Lucy Bencharit (CalPoly-SLO), and Prof. Sarah Billington.

In this paper, public perceptions and support of affordable housing were gauged in a nationwide online survey (N = 534). There was no majority understood definition for affordable housing among the public surveyed, and it was found that an image of federally-funded apartments in unsafe neighborhoods persists. The researchers found that having perceptions related to government, subsidies, safety, and finances predicted support for affordable housing in one’s neighborhood. THis study also highlighted that machine learning can expedite qualitative analysis relative to traditional hand-coding, and the machine learning approaches revealed new potential pathways to support for affordable housing.