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The problem of false positives in automated census linking: Nineteenth-century New York's Irish immigrants as a case study.

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Title: The problem of false positives in automated census linking: Nineteenth-century New York's Irish immigrants as a case study.
Authors: Ó Gráda, Cormac1 (AUTHOR) cormac.ograda@ucd.ie, Anbinder, Tyler2 (AUTHOR), Connor, Dylan3 (AUTHOR), Wegge, Simone A.4 (AUTHOR)
Source: Historical Methods. Oct-Dec2023, Vol. 56 Issue 4, p240-259. 20p.
Subject Terms: *Census, *Children of immigrants, Irish people, Social mobility, Geographic mobility, Immigrant children
Geographic Terms: New York (State)
Abstract: Automated census linkage algorithms have become popular for generating longitudinal data on social mobility, especially for immigrants and their children. But what if these algorithms are particularly bad at tracking immigrants? This study utilizes a database on nineteenth-century Irish immigrants, generated from the most widely used algorithms, created by Abramitzky, Boustan, and Eriksson (ABE). Our objective is to assess the extent to which different individuals are erroneously linked together across census years and the consequences of these "false positives" for calculating social mobility. Our findings raise serious questions about the quality of the matches generated by the "first generation" of automated census linkage algorithms. False positives range from about one-third to one-half of all links. These bad links lead to sizeable estimation errors when measuring Irish immigrant social and geographic mobility. [ABSTRACT FROM AUTHOR]
Copyright of Historical Methods is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: *<searchLink fieldCode="DE" term="%22Census%22">Census</searchLink><br />*<searchLink fieldCode="DE" term="%22Children+of+immigrants%22">Children of immigrants</searchLink><br /><searchLink fieldCode="DE" term="%22Irish+people%22">Irish people</searchLink><br /><searchLink fieldCode="DE" term="%22Social+mobility%22">Social mobility</searchLink><br /><searchLink fieldCode="DE" term="%22Geographic+mobility%22">Geographic mobility</searchLink><br /><searchLink fieldCode="DE" term="%22Immigrant+children%22">Immigrant children</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22New+York+%28State%29%22">New York (State)</searchLink>
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  Data: Automated census linkage algorithms have become popular for generating longitudinal data on social mobility, especially for immigrants and their children. But what if these algorithms are particularly bad at tracking immigrants? This study utilizes a database on nineteenth-century Irish immigrants, generated from the most widely used algorithms, created by Abramitzky, Boustan, and Eriksson (ABE). Our objective is to assess the extent to which different individuals are erroneously linked together across census years and the consequences of these "false positives" for calculating social mobility. Our findings raise serious questions about the quality of the matches generated by the "first generation" of automated census linkage algorithms. False positives range from about one-third to one-half of all links. These bad links lead to sizeable estimation errors when measuring Irish immigrant social and geographic mobility. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Historical Methods is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/01615440.2024.2312293
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      – Code: eng
        Text: English
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        Type: general
      – SubjectFull: Children of immigrants
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      – SubjectFull: Irish people
        Type: general
      – SubjectFull: Social mobility
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      – SubjectFull: Geographic mobility
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      – SubjectFull: Immigrant children
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      – SubjectFull: New York (State)
        Type: general
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      – TitleFull: The problem of false positives in automated census linking: Nineteenth-century New York's Irish immigrants as a case study.
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              Text: Oct-Dec2023
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