Diversity with Universality

This paper investigates the ‘Diversity’ inferences (D-inferences) arising from disjunction embedded in the scope of a universal quantifier, e.g., Every X is A or B suggests Some Xs are A and Some Xs are B. It has previously been claimed (i) that D-inferences are independent from ‘Negative Universal’ inferences (NU-inferences), which are the negations of Every X is A and Every X is B, but (ii) that for disjunction in the scope of a universal modal the D-inferences cannot be observed independently of the NU-inferences ([3, 7, 9, 13]). Experiment 1 tested the availability of D-inferences in the absence of NU-inferences for the determiner every and the epistemic modal must. Experiment 2 followed up on Experiment 1 by testing the same two quantifiers, only this time the modal must expressed deontic necessity. The results show that, for both types of quantifiers, D-inferences could be derived independently of NU-inferences. While the results for every essentially replicate those reported in [7], the results for must are new and go against the aforementioned claim (ii). In addition, the response time results from both experiments show that D-inferences are associated with response delay effects in the opposite direction to those observed for regular scalar implicatures in similar tasks ([4, 5]). We argue that these findings about the time course of D-inferences raise a new challenge for an implicature-based approach to these inferences

Testing two-step models of negative quantification using a novel machine learning analysis of EEG

The sentences “More than half of the students passed the exam” and “Fewer than half of the students failed the exam” describe the same set of situations, and yet the former results in shorter reaction times in verification tasks. The two-step model explains this result by postulating that negative quantifiers contain hidden negation, which involves an extra processing stage. To test this theory, we applied a novel EEG analysis technique focused on detecting cognitive stages (HsMM-MVPA) to data from a picture-sentence verification task. We estimated the number of processing stages during reading and verification of quantified sentences (e.g. “Fewer than half of the dots are blue”) that followed the presentation of pictures containing coloured geometric shapes. We did not find evidence for an extra step during the verification of sentences with fewer than half. We provide an alternative interpretation of our results in line with an expectation-based pragmatic account

Quantifying quantifier representations: Experimental studies, computational modeling, and individual differences

This thesis presents experimental and computational modeling studies on the mental representations of the natural language quantifiers (e.g., most, many, few, more than half, and fewer than half). According to the dominant logical approach in cognitive semantics, the meaning of quantifiers can be expressed in the form of truth conditions. The thesis argues that the logical perspective on quantifiers is insufficient to capture psychological phenomena related to the processing of quantified sentences. The logical perspective thus should be extended to a cognitive perspective. The cognitive perspective considers both truth-conditional representations of quantifiers and individual differences in meaning representations. It also stresses the importance of computational modeling in experimental semantics. The thesis consists of seven chapters: Introduction, five chapters presenting experimental studies, and Conclusions. Chapters 2 and 3 of the thesis present experimental and modeling findings on individual differences in quantifier representations. Chapters 4 and 5 investigate the differences in the processing of positive (e.g., more than half) and negative (e.g., fewer than half) quantifiers in behavioral and electroencephalography experiments. Chapter 6 presents an experiment that tested the learnability explanation of semantic universals

Quantifying quantifier representations:Experimental studies, computational modeling, and individual differences

This thesis presents experimental and computational modeling studies on the mental representations of the natural language quantifiers (e.g., most, many, few, more than half, and fewer than half). According to the dominant logical approach in cognitive semantics, the meaning of quantifiers can be expressed in the form of truth conditions. The thesis argues that the logical perspective on quantifiers is insufficient to capture psychological phenomena related to the processing of quantified sentences. The logical perspective thus should be extended to a cognitive perspective. The cognitive perspective considers both truth-conditional representations of quantifiers and individual differences in meaning representations. It also stresses the importance of computational modeling in experimental semantics. The thesis consists of seven chapters: Introduction, five chapters presenting experimental studies, and Conclusions. Chapters 2 and 3 of the thesis present experimental and modeling findings on individual differences in quantifier representations. Chapters 4 and 5 investigate the differences in the processing of positive (e.g., more than half) and negative (e.g., fewer than half) quantifiers in behavioral and electroencephalography experiments. Chapter 6 presents an experiment that tested the learnability explanation of semantic universals

Quantifying quantifier representations: Experimental studies, computational modeling, and individual differences

This thesis presents experimental and computational modeling studies on the mental representations of the natural language quantifiers (e.g., most, many, few, more than half, and fewer than half). According to the dominant logical approach in cognitive semantics, the meaning of quantifiers can be expressed in the form of truth conditions. The thesis argues that the logical perspective on quantifiers is insufficient to capture psychological phenomena related to the processing of quantified sentences. The logical perspective thus should be extended to a cognitive perspective. The cognitive perspective considers both truth-conditional representations of quantifiers and individual differences in meaning representations. It also stresses the importance of computational modeling in experimental semantics. The thesis consists of seven chapters: Introduction, five chapters presenting experimental studies, and Conclusions. Chapters 2 and 3 of the thesis present experimental and modeling findings on individual differences in quantifier representations. Chapters 4 and 5 investigate the differences in the processing of positive (e.g., more than half) and negative (e.g., fewer than half) quantifiers in behavioral and electroencephalography experiments. Chapter 6 presents an experiment that tested the learnability explanation of semantic universals