Abstract/Summary

Quantifiers like some, most, many and all are said to form part of a scale on which the relative informativity of each quantifier is weighted against the others. Weak quantifiers like some generate an implicit meaning beyond their literal semantic meaning. For example, some PhD students like writing can be taken to mean that not all PhD students like writing. Such an implied meaning is called a scalar implicature (SI). Researchers have examined SIs in child and adult populations using a variety of methodological designs. While children are more inclined to retrieve lower bounded interpretations than adults concerning SI derivation, particularly without explicit instruction, both groups show considerable variability. A growing body of SI work aimed at explaining this variability has examined implicit brain responses while individuals perform various linguistic as well as cognitive tasks and methodological design factors that may give rise to SI interpretative variation. Some of this research has found that SI derivation is associated with scores on cognitive tests such as the Autism Spectrum Quotient (ASQ), working memory (WM) as cognitive load is increased, and the Systematizing Quotient-Revised (SQ-R) questionnaire, and other task design factors. One implication drawn from this research is that lack of SI derivation among adults in particular may be due to a differences in inherent cognitive or psychological mechanisms, such that higher or lower scores on the above-named tasks are apparently correlated with rates of SI derivation and that methodological design can create issues in data interpretation if confounds are not carefully controlled. The purpose of this dissertation is to further shed light on specific methodological and population (bilingualism) factors that contribute to differential SI derivation, in this case among adult native Spanish speakers and Spanish-English bilinguals. I maintain herein that research must fully consider its own role in how SIs are treated experimentally, whether in design, connections made to cognition, or population choice, before generalizing results. Once such variables have been controlled, we may more fully be able to understand inter-individual variation in SI derivation in healthy populations.