Imagine you have a trusty recipe that has stood the test of time. It may seem old-fashioned, but it still gets the job done! Well, that’s how the grammatical paradigm is. In the past, it was THE model for cognitive science, a guiding principle that emphasized axiomatic-like systems and quick testing through introspective judgments. And guess what? It’s still just as efficient! The reason is simple – formal models. They are like precise blueprints, incredibly predictive and easy to break down into smaller components. Formal models make bold predictions that need to be tested efficiently, and introspective judgments help us do just that. But the grammatical paradigm doesn’t stop at linguistics; it branches out into other fascinating realms like gestures and emojis, literature, picture semantics, music, dance cognition, reasoning, and concepts. However, it’s important to adapt the grammatical paradigm to modern cognitive science. This means using computational methods to quantify its predictions and exploring a wide range of data collection techniques. So go ahead and delve into the research to see just how enduring and adaptable this paradigm truly is!

Abstract
The grammatical paradigm used to be a model for entire areas of cognitive science. Its primary tenet was that theories are axiomatic-like systems. A secondary tenet was that their predictions should be tested quickly and in great detail with introspective judgments. While the grammatical paradigm now often seems passé, we argue that in fact it continues to be as efficient as ever. Formal models are essential because they are explicit, highly predictive, and typically modular. They make numerous critical predictions, which must be tested efficiently; introspective judgments do just this. We further argue that the grammatical paradigm continues to be fruitful. Within linguistics, implicature theory is a recent example, with a combination of formal explicitness, modularity, and interaction with experimental work. Beyond traditional linguistics, the grammatical paradigm has proven fruitful in the study of gestures and emojis; literature (“Free Indirect Discourse”); picture semantics and comics; music and dance cognition; and even reasoning and concepts. We argue, however, that the grammatical paradigm must be adapted to contemporary cognitive science. Computational methods are essential to derive quantitative predictions from formal models (Bayesian pragmatics is an example). And data collection techniques offer an ever richer continuum of options, from introspective judgments to large-scale experiments, which makes it possible to optimize the cost/benefit ratio of the empirical methods that are chosen to test theories.

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