When experiments need models
By: Khosrowi, Donal
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Material type: 
BookPublisher: Philosophy of the Social Sciences Description: 51(4), Jul, 2021: p.400-424.Subject(s): Experiments, Models, Experiment-target inference, Extrapolation, External validity, Evidence-based policy
In:
Philosophy of the Social SciencesSummary: This paper argues that an important type of experiment-target inference, extrapolating causal effects, requires models to be successful. Focusing on extrapolation in Evidence-Based Policy, it is argued that extrapolation should be understood not as an inference from an experiment to a target directly, but as a hybrid inference that involves experiments and models. A general framework, METI, is proposed to capture this role of models, and several benefits are outlined: (1) METI highlights epistemically significant interactions between experiments and models, (2) reconciles some differences among existing accounts of experiment-target relationships, and (3) facilitates critical appraisal of inferential practices from experiments. – Reproduced
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Articles
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Indian Institute of Public Administration | 51(4), Jul, 2021: p.400-424 | Available | AR126138 |
This paper argues that an important type of experiment-target inference, extrapolating causal effects, requires models to be successful. Focusing on extrapolation in Evidence-Based Policy, it is argued that extrapolation should be understood not as an inference from an experiment to a target directly, but as a hybrid inference that involves experiments and models. A general framework, METI, is proposed to capture this role of models, and several benefits are outlined: (1) METI highlights epistemically significant interactions between experiments and models, (2) reconciles some differences among existing accounts of experiment-target relationships, and (3) facilitates critical appraisal of inferential practices from experiments. – Reproduced
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