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Brian J Goode

Biographic Data

ID248598
NAMEBrian J Goode
GIVEN NAMESBrian J
FAMILY NAMEGoode
SIGNATUREGOODE B J
AFFILIATIONSVirginia Tech
VERIFIEDNo
TOTAL WORKS3
TOTAL CITATIONS3
WORKS AS AUTHOR3
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2019
LATEST PUBLICATION YEAR2020
H-INDEX1
  • Measuring the predictability of life outcomes with a scientific mass collaboration

    Open Access•M J Salganik, Ian Lundberg et al.•ARTICLE•Proceedings of the National…•2020

    How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly…

  • Networked experiments and modeling for producing collective identity in a group of human subjects using an iterative abduction framework

    Open Access•Vanessa Cedeno-Mieles, Zhihao Hu et al.•ARTICLE•Social Network Analysis and Mining•2020•Cited by: 1•References: 132

  • Imputing Data for the Fragile Families Challenge

    Open Access•Brian J Goode, Debanjan Datta et al.•ARTICLE•Socius Sociological Research for…•2019•Cited by: 2•References: 4

    The Fragile Families Challenge charged participants to predict six outcomes for 4,242 children and their families interviewed in the Fragile Families and Child Wellbeing Study. These outcome variables are grade point average, grit, material hardship, eviction, layoff and job training. The data set provided contained longitudinal survey and observational data collected on families and their children from birth to age 9. The authors used these data…

  • Imputing Data for the Fragile Families Challenge

    Open Access•Brian J Goode, Debanjan Datta et al.•ARTICLE•Socius Sociological Research for…•2019•Cited by: 2•References: 4

    The Fragile Families Challenge charged participants to predict six outcomes for 4,242 children and their families interviewed in the Fragile Families and Child Wellbeing Study. These outcome variables are grade point average, grit, material hardship, eviction, layoff and job training. The data set provided contained longitudinal survey and observational data collected on families and their children from birth to age 9. The authors used these data…

  • Networked experiments and modeling for producing collective identity in a group of human subjects using an iterative abduction framework

    Open Access•Vanessa Cedeno-Mieles, Zhihao Hu et al.•ARTICLE•Social Network Analysis and Mining•2020•Cited by: 1•References: 132

  • Imputing Data for the Fragile Families Challenge

    Open Access•Brian J Goode, Debanjan Datta et al.•ARTICLE•Socius Sociological Research for…•2019•Cited by: 2•References: 4

    The Fragile Families Challenge charged participants to predict six outcomes for 4,242 children and their families interviewed in the Fragile Families and Child Wellbeing Study. These outcome variables are grade point average, grit, material hardship, eviction, layoff and job training. The data set provided contained longitudinal survey and observational data collected on families and their children from birth to age 9. The authors used these data…

  • Measuring the predictability of life outcomes with a scientific mass collaboration

    Open Access•M J Salganik, Ian Lundberg et al.•ARTICLE•Proceedings of the National…•2020

    How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly…

  • Networked experiments and modeling for producing collective identity in a group of human subjects using an iterative abduction framework

    Open Access•Vanessa Cedeno-Mieles, Zhihao Hu et al.•ARTICLE•Social Network Analysis and Mining•2020•Cited by: 1•References: 132

Computer Science (2 works) · Mathematics (2 works) · Psychology (2 works) · Statistics (2 works) · Artificial Intelligence (1 work) · Benchmark (surveying) (1 work) · Cohort (1 work) · Collective identity (1 work) · Collective intelligence (1 work) · Collective memory (1 work)

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