About

Benjamin Domingue is an associate professor at the Graduate School of Education at Stanford University. His research interests include psychometrics and quantitative methods, with a focus on how statistical tools can be used to better understand psychological and educational outcomes. He is particularly interested in measuring challenging yet ubiquitous educational and social outcomes, such as reading ability. Domingue is leading the development of the Item Response Warehouse, a data resource aimed at increasing the availability and accessibility of data for psychometrics research. In addition to his primary appointment, he holds courtesy appointments in Sociology and is a member of the Bio-X Program. His work encompasses assessment, testing and measurement, child development, data sciences, educational policy, psychology, research methods, and sociology.

Research topics

• Psychology
• Computer Science
• Artificial Intelligence
• Sociology
• Political Science
• Medicine
• Biology
• Economics
• Genetics
• Social psychology
• Machine Learning
• Law
• Psychiatry
• Social Science
• History
• Medical education
• Internal medicine
• Public relations
• Mathematics
• Linguistics
• Mathematics education
• Accounting
• Management
• Developmental psychology

Selected publications

• Multivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders

  Nature Mental Health · 2023 · 225 citations

  • Computer Science
  • Psychiatry
  • Psychology
  PublisherOA PDFDOI

• The Effect of COVID on Oral Reading Fluency During the 2020–2021 Academic Year

  AERA Open · 2022 · 38 citations

  1st authorCorresponding
  • Psychology
  • Medical education
  • Mathematics education

  Education has faced unprecedented disruption during the COVID pandemic. Understanding how students have adapted as we have entered a different phase of the pandemic and some communities have returned to more typical schooling will inform a suite of policy interventions and subsequent research. We use data from an oral reading fluency (ORF) assessment—a rapid assessment taking only a few minutes that measures a fundamental reading skill—to examine COVID’s effects on children’s reading ability during the pandemic. We find that students in the first 200 days of the 2020–2021 school year tended to experience slower growth in ORF relative to prepandemic years. We also observe slower growth in districts with a high percentage of English language learners and/or students eligible for free and reduced-price lunch. These findings offer valuable insight into the effects of COVID on one of the most fundamental skills taught to children.

  PublisherDOI

• Application essays and the ritual production of merit in US selective admissions

  Poetics · 2022 · 16 citations

  • Sociology
  • Political Science
  • Sociology

  US colleges and universities are defined by their exclusivity, and the most prestigious schools reject most of those who apply. Yet these same schools also widely advertise their inclusiveness, encouraging students from all backgrounds to submit applications and highlighting evaluation protocols that identify many characteristics worthy of consideration for admission. We surface this paradox and use it as motivation to theorize a little studied component of college applications: personal essays. Drawing from cultural sociology, we posit that the commission and production of essays extolling applicant worth and worthiness is a ritual practice that instantiates an idea of merit that is broadly shared among those who submit applications to admissions-selective schools. We pursue this work empirically by observing essay prompt selections of 55,016 applicants to the University of California in 2016 and conducting human readings and statistical analyses of 3,519 unique essays. Results indicate that prompts and essays encompass a broad but bounded range of life challenges that selective schools and applicants consider meritorious. The entire process of application to selective US schools helps to reify a national faith in a broad and inclusive conception of merit.

  PublisherDOI

• Essay content and style are strongly related to household income and SAT scores: Evidence from 60,000 undergraduate applications

  Science Advances · 2021 · 71 citations

  Senior authorCorresponding
  • Sociology
  • Computer Science
  • Social Science

  There is substantial evidence of the relationship between household income and achievement on the standardized tests often required for college admissions, yet little comparable inquiry considers the essays typically required of applicants to selective U.S. colleges and universities. We used a corpus of 240,000 admission essays submitted by 60,000 applicants to the University of California in November 2016 to measure relationships between the content of admission essays, self-reported household income, and SAT scores. We quantified essay content using correlated topic modeling and essay style using Linguistic Inquiry and Word Count. We found that essay content and style had stronger correlations to self-reported household income than did SAT scores and that essays explained much of the variance in SAT scores. This analysis shows that essays encode similar information as the SAT and suggests that college admission protocols should attend to how social class is encoded in non-numerical components of applications.

  PublisherDOI

• Investigating the genetic architecture of noncognitive skills using GWAS-by-subtraction

  Nature Genetics · 2021 · 291 citations

  • Biology
  • Genetics
  • Psychology
  DOI

• A large-scale genome-wide association study meta-analysis of cannabis use disorder

  The Lancet Psychiatry · 2020 · 375 citations

  • Genetics
  • Biology
  • Psychiatry

  BACKGROUND: Variation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50-70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder. METHODS: To conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations. FINDINGS: ), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia. INTERPRETATION: These findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between genetic liability to cannabis use and cannabis use disorder. FUNDING: National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institute on Drug Abuse; Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing; The European Commission, Horizon 2020; National Institute of Child Health and Human Development; Health Research Council of New Zealand; National Institute on Aging; Wellcome Trust Case Control Consortium; UK Research and Innovation Medical Research Council (UKRI MRC); The Brain & Behavior Research Foundation; National Institute on Deafness and Other Communication Disorders; Substance Abuse and Mental Health Services Administration (SAMHSA); National Institute of Biomedical Imaging and Bioengineering; National Health and Medical Research Council (NHMRC) Australia; Tobacco-Related Disease Research Program of the University of California; Families for Borderline Personality Disorder Research (Beth and Rob Elliott) 2018 NARSAD Young Investigator Grant; The National Child Health Research Foundation (Cure Kids); The Canterbury Medical Research Foundation; The New Zealand Lottery Grants Board; The University of Otago; The Carney Centre for Pharmacogenomics; The James Hume Bequest Fund; National Institutes of Health: Genes, Environment and Health Initiative; National Institutes of Health; National Cancer Institute; The William T Grant Foundation; Australian Research Council; The Virginia Tobacco Settlement Foundation; The VISN 1 and VISN 4 Mental Illness Research, Education, and Clinical Centers of the US Department of Veterans Affairs; The 5th Framework Programme (FP-5) GenomEUtwin Project; The Lundbeck Foundation; NIH-funded Shared Instrumentation Grant S10RR025141; Clinical Translational Sciences Award grants; National Institute of Neurological Disorders and Stroke; National Heart, Lung, and Blood Institute; National Institute of General Medical Sciences.

  DOI

• AI and Holistic Review

  2020 · 32 citations

  • Computer Science
  • Artificial Intelligence
  • Computer Science

  College admissions in the United States is carried out by a humancentered method of evaluation known as holistic review, which typically involves reading original narrative essays submitted by each applicant. The legitimacy and fairness of holistic review, which gives human readers significant discretion over determining each applicant's fitness for admission, has been repeatedly challenged in courtrooms and the public sphere. Using a unique corpus of 283,676 application essays submitted to a large, selective, state university system between 2015 and 2016, we assess the extent to which applicant demographic characteristics can be inferred from application essays. We find a relatively interpretable classifier (logistic regression) was able to predict gender and household income with high levels of accuracy. Findings suggest that data auditing might be useful in informing holistic review, and perhaps other evaluative systems, by checking potential bias in human or computational readings.

  PublisherOA PDFDOI

Recent grants

• NIH Grant R21HD078031

  NIH · $300k · 2016

Frequent coauthors

• Jason D. Boardman

  74 shared

• Kathleen Mullan Harris

  University of North Carolina at Chapel Hill

  48 shared

• Daniel W. Belsky

  Canadian Institute for Advanced Research

  45 shared

• Henry R. Kranzler

  Washington University in St. Louis

  34 shared

• Robbee Wedow

  Broad Institute

  31 shared

• Klint Kanopka

  New York University

  30 shared

• Dalton Conley

  30 shared

• Raymond K. Walters

  Broad Institute

  29 shared

Labs

• Item Response WarehousePI

Education

• Ph.D., Educational Data Science

  Stanford University

• M.S., Educational Data Science

  Stanford University

• B.S., Psychology

  Stanford University

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