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Ashton M. Verdery
Researcher at Pennsylvania State University
Publications - 65
Citations - 1434
Ashton M. Verdery is an academic researcher from Pennsylvania State University. The author has contributed to research in topics: Population & Medicine. The author has an hindex of 18, co-authored 53 publications receiving 937 citations. Previous affiliations of Ashton M. Verdery include University of North Carolina at Chapel Hill.
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Beyond Household Walls: The Spatial Structure of American Extended Kinship Networks.
TL;DR: How far do Americans live from their close and extended kin is likely to structure the types of social, instrumental, and financial support that they are able to provide to one another and fixed-effects models demonstrate that family formation shapes spatial relations between kin.
The Structure of Undergraduate Association Networks: A Quantitative Ethnography
TL;DR: This paper presents an original network dataset of undergraduate Facebook users and demonstrates the feasibility and acceptability of this form of measurement, and begins a preliminary exploration of Network Homophily and Multiplexity on Facebook.
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Opioid misuse and family structure: Changes and continuities in the role of marriage and children over two decades.
TL;DR: Individuals from all family structures are vulnerable to the opioid crisis, but never married adults without coresident children ("disconnected adults") are especially susceptible to temporal fluctuations and drive the temporal trends in PPR misuse and heroin use.
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Visualizing Age, Period, and Cohort Patterns of Substance Use in the U.S. Opioid Crisis:
Ashton M. Verdery,Kira England,Alexander L. Chapman,Liying Luo,Katherine McLean,Shannon M. Monnat +5 more
TL;DR: The authors provide heatmap visualizations of estimated annual rates of past-year substance use, rather than overdose deaths, for prescription pain relievers and heroin, from 2002 to 2017, to suggest that policies aimed only at restricting opioid availability may have limited effects.
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Enhancing Big Data in the Social Sciences with Crowdsourcing: Data Augmentation Practices, Techniques, and Opportunities
TL;DR: In this article, the authors argue that Big Data projects can be enhanced through data augmentation with crowdsourcing marketplaces like Amazon Mechanical Turk (MTurk), and they present three empirical cases to illustrate the strengths and limits of crowdsourcing and address social science skepticism.