Political science is an increasingly model-driven discipline. Political scientists use models--formal and informal, quantitative and qualitative--to investigate and illuminate causal mechanisms, study patterns in datasets, and understand the conditions under which certain outcomes are expected to occur. But how do political scientists justify and rationalize this method? Why test predictions from a deductive, and thus truth-preserving, system? David Primo and Kevin Clarke tackle these important questions in this novel work of methodology.

Political science is an increasingly model-driven discipline. Political scientists use models--formal and informal, quantitative and qualitative--to investigate and illuminate causal mechanisms, study patterns in datasets, and understand the conditions under which certain outcomes are expected to occur. But how do political scientists justify and rationalize this method? Why test predictions from a deductive, and thus truth-preserving, system? David Primo and Kevin Clarke tackle these important questions in this novel work of methodology.

Political science is an increasingly model-driven discipline. Political scientists use models--formal and informal, quantitative and qualitative--to investigate and illuminate causal mechanisms, study patterns in datasets, and understand the conditions under which certain outcomes are expected to occur. But how do political scientists justify and rationalize this method? Why test predictions from a deductive, and thus truth-preserving, system? David Primo and Kevin Clarke tackle these important questions in this novel work of methodology.