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Author ORCID Identifier


Open Access Dissertation

Document Type


Degree Name

Doctor of Philosophy (PhD)

Degree Program


Year Degree Awarded


Month Degree Awarded


First Advisor

Brian Dillon

Second Advisor

Vincent Homer

Third Advisor

Dr. Adrian Staub

Subject Categories

Psycholinguistics and Neurolinguistics


Even is a focus-sensitive semantic operator that introduces a presupposition about likelihood. Under many semantic accounts, even’s likelihood presupposition requires the sentence with even to be less likely than a set of contextually-relevant alternatives. On one hand, even’s presupposition is complex, and this complexity may cause delays in processing. On the other hand, despite—and indeed because—of this complexity, even has the potential to be highly informative to readers.

In this dissertation, I investigate whether and how even interacts with lexical predictability in online processing. If comprehenders are able to rapidly process even, they may be able to use it to “expect the unexpected.” This, in turn, could reduce predictability effects: otherwise predictable words might be processed more slowly, or otherwise unpredictable words might be processed more quickly. In addition to influencing early predictability effects, processing even could cause later effects reflecting semantic integration.

I first show that even influences offline cloze probabilities, decreasing the probability of modal responses and increasing response entropy. In two eye-tracking while reading studies, however, even had no significant effects on early reading time measures, and most effects on later reading time measures were rather small and inconsistent between the two studies. A bidirectional self-paced reading study produced results that were inconsistent with eye-tracking and therefore difficult to interpret. Even also produced no significant interactions with predictability in a series of maze task studies: one replication study, one study with negation, and one study with context sentences designed to provide a suitable antecedent for even.

Despite the lack of significant interactions, post-hoc analyses of item-wise correlations revealed that even most likely does interact with predictability manipulations, but these effects are small, highly sensitive to item variation, and more consistent with semantic integration than prediction. This small effect may be due to the complexity of even’s presupposition and the difficulties of integrating it rapidly. In addition, cloze probabilities may not reflect how even is used across the language as a whole. Finally, comprehenders may adopt a more flexible, “generous” processing strategy in which even’s presupposition is considered to be met in a variety of situations.