Motivation
A fundamental divide persists between Social Science, which prioritizes explanation and causal understanding, and Data Science, which emphasizes prediction and forecasting. Separately, each approach is limited – producing either explanations with uncertain predictive value, or predictions that lack interpretability and robustness under real-world policy change. What if the strengths of the explanatory and predictive approaches could be combined to enable research that is both scientifically rigorous and practically relevant for decision-makers?
Mission
To advance a framework combining the explanatory strengths of Social Science with the predictive capabilities of Data Science, improving how evidence is generated, evaluated, and used for theory development, decision-making, and actual governance.
Vision
A research landscape in which explanation and prediction reinforce one another - producing models that deepen our theoretical understanding of social processes and can forecast future outcomes. By integrating theory-driven explanation with data-driven prediction, Predict to Explain strengthens both scientific insight and real-world decision-making.
Goals
- Identify and bridge the complementary research approaches of Social Science and Data Science.
- Evaluate and expand the scientific, explanatory quality of Social Science research.
- Develop and promote a combined framework for theory-development: Predict to Explain
- Explore the approach in the study of key questions in Social Science.
- Update core methodological thinking and implementation in the social sciences.
Target Audience
- Applied Social Science and Data Science researchers.
- Social Science and Data Science students.
- Researchers and professional practitioners in the fields of policy analysis, forecasting, decision-making, and socially oriented applications.
Your contribution supports:
- Research into cutting-edge methodological advances at the frontier of applied Social Science
- Collaborative research and real-world application to answer prediction and explanatory questions
- Improving our ability to understand society and to offer practical guidance for addressing real-world challenges.
- Improved capacity to respond to rapid social and political change
- Better forecasts that generalize across contexts and policy scenarios
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