Psycholinguistic studies have repeatedly demonstrated that downward entailing (DE) quantifiers are more difficult to process than upward entailing (UE) ones. We contribute to the current debate on cognitive processes causing the monotonicity effect by testing predictions about the underlying processes derived from two competing theoretical proposals: two-step and pragmatic processing models. We model reaction times and accuracy from two verification experiments (a sentencepicture and a purely linguistic verification task), using the diffusion decision model (DDM). In both experiments, verification of UE quantifier more than half was compared to verification of DE quantifier fewer than half. Our analyses revealed the same pattern of results across tasks: Both non-decision times and drift rates, two of the free model parameters of the DDM, were affected by the monotonicity manipulation. Thus, our modeling results support both two-step (prediction: nondecision time is affected) and pragmatic processing models (prediction: drift rate is affected).
Representational complexity and pragmatics cause the monotonicity effect / Schlotterbeck, Fabian; Ramotowska, Sonia; van Maanen, Leendert; Szymanik, Jakub. - (2020), pp. 3398-3404. (Intervento presentato al convegno 42nd Annual Meeting of the Cognitive Science Society: Developing a Mind: Learning in Humans, Animals, and Machines, CogSci 2020 tenutosi a virtual nel 2020).
Representational complexity and pragmatics cause the monotonicity effect
Szymanik, Jakub
2020-01-01
Abstract
Psycholinguistic studies have repeatedly demonstrated that downward entailing (DE) quantifiers are more difficult to process than upward entailing (UE) ones. We contribute to the current debate on cognitive processes causing the monotonicity effect by testing predictions about the underlying processes derived from two competing theoretical proposals: two-step and pragmatic processing models. We model reaction times and accuracy from two verification experiments (a sentencepicture and a purely linguistic verification task), using the diffusion decision model (DDM). In both experiments, verification of UE quantifier more than half was compared to verification of DE quantifier fewer than half. Our analyses revealed the same pattern of results across tasks: Both non-decision times and drift rates, two of the free model parameters of the DDM, were affected by the monotonicity manipulation. Thus, our modeling results support both two-step (prediction: nondecision time is affected) and pragmatic processing models (prediction: drift rate is affected).File | Dimensione | Formato | |
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