Proceedings of the Annual Meeting of the Cognitive Science Society

Experimental studies show that the tendency to derive Scalar Implicatures (SIs) varies considerably between individuals: some individuals accept sentences that are literally true but carry a false SI, while others systematically reject them. The question of what factors drive these differences is crucial to understanding the mechanisms involved in SIs and currently at the center of numerous discussions. To date, there is no agreement on how to quantify individual differences in SI rates. In this article, we show how a hierarchical Bayesian modelling approach can be used to quantify subjects' preferences observed in the results of a truth value judgement task that investigated intra-individual and inter-individual variability in the rates of upper-bounding and lower-bounding SIs associated with the -scale. The results provide further evidence that the robustness of an SI is modulated within individuals by certain linguistic features, such as the presence of negation.