Race-neutral vs race-conscious: Using algorithmic methods to evaluate the reparative potential of housing programs
The racial wealth gap in the United States remains a persistent issue; white individuals possess six times more wealth than Black individuals. Leading scholars and public figures have pointed to slavery and post-slavery discrimination as root cause factors and called for reparations. Yet the institu...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
SAGE Publications
2024
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| Online Access: | https://hdl.handle.net/1721.1/155952 |
| _version_ | 1824457941253619712 |
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| author | So, Wonyoung D’Ignazio, Catherine |
| author2 | Massachusetts Institute of Technology. Department of Urban Studies and Planning |
| author_facet | Massachusetts Institute of Technology. Department of Urban Studies and Planning So, Wonyoung D’Ignazio, Catherine |
| author_sort | So, Wonyoung |
| collection | MIT |
| description | The racial wealth gap in the United States remains a persistent issue; white individuals possess six times more wealth than Black individuals. Leading scholars and public figures have pointed to slavery and post-slavery discrimination as root cause factors and called for reparations. Yet the institutionalization of race-neutral ideologies in policies and practices hinders a reparative approach to closing the racial wealth gap. This study models the use of algorithmic methods in the service of reparations to Black Americans in the domain of housing, where most American wealth is built. We examine a hypothetical scenario for measuring the effectiveness of race-conscious Special Purpose Credit Programs (SPCPs) in reducing the housing racial wealth gap compared to race-neutral SPCPs. We use a predictive model to show that race-conscious, people-based lending programs, if they were nationally available, would be two to three times more effective in closing the racial housing wealth gap than other, existing forms of SPCPs. In doing so, we also demonstrate the potential for using algorithms and computational methods to support outcomes aligned with movements for reparations, another possible meaning for the emerging discourse on “algorithmic reparations.” |
| first_indexed | 2024-09-23T09:08:39Z |
| format | Article |
| id | mit-1721.1/155952 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2025-02-19T04:17:59Z |
| publishDate | 2024 |
| publisher | SAGE Publications |
| record_format | dspace |
| spelling | mit-1721.1/1559522024-12-23T05:49:05Z Race-neutral vs race-conscious: Using algorithmic methods to evaluate the reparative potential of housing programs So, Wonyoung D’Ignazio, Catherine Massachusetts Institute of Technology. Department of Urban Studies and Planning The racial wealth gap in the United States remains a persistent issue; white individuals possess six times more wealth than Black individuals. Leading scholars and public figures have pointed to slavery and post-slavery discrimination as root cause factors and called for reparations. Yet the institutionalization of race-neutral ideologies in policies and practices hinders a reparative approach to closing the racial wealth gap. This study models the use of algorithmic methods in the service of reparations to Black Americans in the domain of housing, where most American wealth is built. We examine a hypothetical scenario for measuring the effectiveness of race-conscious Special Purpose Credit Programs (SPCPs) in reducing the housing racial wealth gap compared to race-neutral SPCPs. We use a predictive model to show that race-conscious, people-based lending programs, if they were nationally available, would be two to three times more effective in closing the racial housing wealth gap than other, existing forms of SPCPs. In doing so, we also demonstrate the potential for using algorithms and computational methods to support outcomes aligned with movements for reparations, another possible meaning for the emerging discourse on “algorithmic reparations.” 2024-08-07T15:20:01Z 2024-08-07T15:20:01Z 2023-07 2024-08-07T15:12:57Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/155952 So, W., & D’Ignazio, C. (2023). Race-neutral vs race-conscious: Using algorithmic methods to evaluate the reparative potential of housing programs. Big Data & Society, 10(2). en 10.1177/20539517231210272 Big Data & Society Creative Commons Attribution-Noncommercial https://creativecommons.org/licenses/by-nc/4.0/ application/pdf SAGE Publications SAGE Publications |
| spellingShingle | So, Wonyoung D’Ignazio, Catherine Race-neutral vs race-conscious: Using algorithmic methods to evaluate the reparative potential of housing programs |
| title | Race-neutral vs race-conscious: Using algorithmic methods to evaluate the reparative potential of housing programs |
| title_full | Race-neutral vs race-conscious: Using algorithmic methods to evaluate the reparative potential of housing programs |
| title_fullStr | Race-neutral vs race-conscious: Using algorithmic methods to evaluate the reparative potential of housing programs |
| title_full_unstemmed | Race-neutral vs race-conscious: Using algorithmic methods to evaluate the reparative potential of housing programs |
| title_short | Race-neutral vs race-conscious: Using algorithmic methods to evaluate the reparative potential of housing programs |
| title_sort | race neutral vs race conscious using algorithmic methods to evaluate the reparative potential of housing programs |
| url | https://hdl.handle.net/1721.1/155952 |
| work_keys_str_mv | AT sowonyoung raceneutralvsraceconscioususingalgorithmicmethodstoevaluatethereparativepotentialofhousingprograms AT dignaziocatherine raceneutralvsraceconscioususingalgorithmicmethodstoevaluatethereparativepotentialofhousingprograms |