@article{e37c5182ac6744d5a9284029cd38566d,
title = "Introduction to the Special Collection on the Fragile Families Challenge",
abstract = "The Fragile Families Challenge is a scientific mass collaboration designed to measure and understand the predictability of life trajectories. Participants in the Challenge created predictive models of six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. This Special Collection includes 12 articles describing participants{\textquoteright} approaches to predicting these six outcomes as well as 3 articles describing methodological and procedural insights from running the Challenge. This introduction will help readers interpret the individual articles and help researchers interested in running future projects similar to the Fragile Families Challenge.",
keywords = "common task method, life course, machine learning, mass collaboration, prediction",
author = "Salganik, {Matthew J.} and Ian Lundberg and Kindel, {Alexander T.} and Sara McLanahan",
note = "Funding Information: Minor updates have been made since first publication: Salganik et al. 2020 was previously cited as Fragile Families Team 2020; Figure 6 has been updated to show all y-axes start at 0.00 for reader clarity and the graph for Layoff, Leaderboard (missing excluded) has been corrected; and the grant number from the National Science Foundation has been corrected. Funding Information: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Research reported in this publication was supported by the Russell Sage Foundation, National Science Foundation (1760052), and the Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institutes of Health under Award Nos. P2-CHD047879 and R24-HD047879. Funding for the Fragile Families and Child Wellbeing Study was provided by the Eunice Kennedy Shriver National Institute of Child Health and Human Development through Grants R01-HD36916, R01-HD39135, and R01-HD40421 and by a consortium of private foundations, including the Robert Wood Johnson Foundation. Alexander T. Kindel gratefully acknowledges funding support from a National Science Foundation Graduate Research Fellowship. Publisher Copyright: {\textcopyright} SAGE Publications Inc.. All rights reserved.",
year = "2019",
doi = "10.1177/2378023119871580",
language = "English (US)",
volume = "5",
journal = "Socius",
issn = "2378-0231",
publisher = "SAGE Publications Inc.",
}