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Laura B Nolan

Biographic Data

ID2134389
NAMELaura B Nolan
GIVEN NAMESLaura B
FAMILY NAMENolan
SIGNATURENOLAN L B
AFFILIATIONSPh.D. candidate, Office of Population Research Princeton University
VERIFIEDNo
TOTAL WORKS4
TOTAL CITATIONS25
AUTHOR COUNT4
EDITOR COUNT0
FIRST PUBLICATION YEAR2015
LATEST PUBLICATION YEAR2017
H-INDEX2
  • Machine Learning for Social Services

    Ian Pan, Laura B Nolan et al.•ARTICLE•American Journal of Public Health•2017•Cited by: 2•References: 19

    Objectives. To evaluate the positive predictive value of machine learning algorithms for early assessment of adverse birth risk among pregnant women as a means of improving the allocation of social services. Methods. We used administrative data for 6457 women collected by the Illinois Department of Human Services from July 2014 to May 2015 to develop a machine learning model for adverse birth prediction and improve upon the existing paper-based r…

  • Long-Term Trends in Rural and Urban Poverty

    Open Access•Laura B Nolan, Laura Nolan et al.•ARTICLE•The Annals of the American…•2017•Cited by: 8•References: 15

    Poverty has a strong relationship to geography in the United States. Previous research has found that rural areas have higher average poverty rates than urban areas, but the new supplemental poverty measure (SPM) has shown in recent years that urban areas have higher average poverty. In this article, we analyze poverty trends from 1967 to 2014 in rural and urban America, using the improved SPM metrics. We find a dramatic decline in poverty in rur…

  • Rural–Urban Child Height for Age Trajectories and Their Heterogeneous Determinants in Four Developing Countries

    Open Access•Laura B Nolan, Laura Nolan•ARTICLE•Population Research and Policy…•2016•Cited by: 2•References: 45

  • Slum Definitions in Urban India

    Open Access•Laura B Nolan, Laura Nolan•ARTICLE•Population and Development Review•2015•Cited by: 13•References: 43

    Half the population of low- and middle-income countries will live in urban areas by 2030, and poverty and inequality in these contexts are rising. Slum-dwelling is one way in which to conceptualize and characterize urban deprivation, but there are many definitions of what constitutes a slum. This article presents four different slum definitions used in India, demonstrating that assessments of both the distribution and extent of urban deprivation …

  • Slum Definitions in Urban India

    Open Access•Laura B Nolan, Laura Nolan•ARTICLE•Population and Development Review•2015•Cited by: 13•References: 43

    Half the population of low- and middle-income countries will live in urban areas by 2030, and poverty and inequality in these contexts are rising. Slum-dwelling is one way in which to conceptualize and characterize urban deprivation, but there are many definitions of what constitutes a slum. This article presents four different slum definitions used in India, demonstrating that assessments of both the distribution and extent of urban deprivation …

  • Long-Term Trends in Rural and Urban Poverty

    Open Access•Laura B Nolan, Laura Nolan et al.•ARTICLE•The Annals of the American…•2017•Cited by: 8•References: 15

    Poverty has a strong relationship to geography in the United States. Previous research has found that rural areas have higher average poverty rates than urban areas, but the new supplemental poverty measure (SPM) has shown in recent years that urban areas have higher average poverty. In this article, we analyze poverty trends from 1967 to 2014 in rural and urban America, using the improved SPM metrics. We find a dramatic decline in poverty in rur…

  • Machine Learning for Social Services

    Ian Pan, Laura B Nolan et al.•ARTICLE•American Journal of Public Health•2017•Cited by: 2•References: 19

    Objectives. To evaluate the positive predictive value of machine learning algorithms for early assessment of adverse birth risk among pregnant women as a means of improving the allocation of social services. Methods. We used administrative data for 6457 women collected by the Illinois Department of Human Services from July 2014 to May 2015 to develop a machine learning model for adverse birth prediction and improve upon the existing paper-based r…

  • Rural–Urban Child Height for Age Trajectories and Their Heterogeneous Determinants in Four Developing Countries

    Open Access•Laura B Nolan, Laura Nolan•ARTICLE•Population Research and Policy…•2016•Cited by: 2•References: 45

  • Slum Definitions in Urban India

    Open Access•Laura B Nolan, Laura Nolan•ARTICLE•Population and Development Review•2015•Cited by: 13•References: 43

    Half the population of low- and middle-income countries will live in urban areas by 2030, and poverty and inequality in these contexts are rising. Slum-dwelling is one way in which to conceptualize and characterize urban deprivation, but there are many definitions of what constitutes a slum. This article presents four different slum definitions used in India, demonstrating that assessments of both the distribution and extent of urban deprivation …

  • Rural–Urban Child Height for Age Trajectories and Their Heterogeneous Determinants in Four Developing Countries

    Open Access•Laura B Nolan, Laura Nolan•ARTICLE•Population Research and Policy…•2016•Cited by: 2•References: 45

  • Machine Learning for Social Services

    Ian Pan, Laura B Nolan et al.•ARTICLE•American Journal of Public Health•2017•Cited by: 2•References: 19

    Objectives. To evaluate the positive predictive value of machine learning algorithms for early assessment of adverse birth risk among pregnant women as a means of improving the allocation of social services. Methods. We used administrative data for 6457 women collected by the Illinois Department of Human Services from July 2014 to May 2015 to develop a machine learning model for adverse birth prediction and improve upon the existing paper-based r…

  • Long-Term Trends in Rural and Urban Poverty

    Open Access•Laura B Nolan, Laura Nolan et al.•ARTICLE•The Annals of the American…•2017•Cited by: 8•References: 15

    Poverty has a strong relationship to geography in the United States. Previous research has found that rural areas have higher average poverty rates than urban areas, but the new supplemental poverty measure (SPM) has shown in recent years that urban areas have higher average poverty. In this article, we analyze poverty trends from 1967 to 2014 in rural and urban America, using the improved SPM metrics. We find a dramatic decline in poverty in rur…

Economic growth (3 works) · Economics (3 works) · Geography (3 works) · Medicine (3 works) · Poverty (3 works) · Socioeconomics (3 works) · Child Nutrition and Water Access (2 works) · Environmental health (2 works) · Inequality (2 works) · Population (2 works)

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