ArticleRoyal Society open science2021
Using prediction markets to predict the outcomes in the Defense Advanced Research Projects Agency's next-generation social science programme.
Article in Royal Society open science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
6 citing papers in PubMed.
- A metric of knowledge as information compression reflects reproducibility predictions for biomedical experiments.Royal Society open science · 2025Article
- Predicting the replicability of social and behavioural science claims in COVID-19 preprints.Nature human behaviour · 2025Article
- Can large language models help predict results from a complex behavioural science study?Royal Society open science · 2024Article
- Academics are more specific, and practitioners more sensitive, in forecasting interventions to strengthen democratic attitudes.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Examining the generalizability of research findings from archival data.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Politicizing mask-wearing: predicting the success of behavioral interventions among republicans and democrats in the U.S.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There is evidence that prediction markets are useful tools to aggregate information on researchers' beliefs about scientific results including the outcome of replications. In this study, we use prediction markets to forecast the results of novel experimental designs that test established theories. We set up prediction markets for hypotheses tested in the Defense Advanced Research Projects Agency's (DARPA) Next Generation Social Science (NGS2) programme. Researchers were invited to bet on whether 22 hypotheses would be supported or not. We define support as a test result in the same direction as hypothesized, with a Bayes factor of at least 10 (i.e. a likelihood of the observed data being consistent with the tested hypothesis that is at least 10 times greater compared with the null hypothesis). In addition to betting on this binary outcome, we asked participants to bet on the expected effect size (in Cohen's
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.