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Do Monolingual Norms Reflect Bilingual Expectations? Cloze and Association Consistency in English, Spanish–English and Mandarin–English Speakers

Poster Session B - Sunday, March 8, 2026, 8:00 – 10:00 am PDT, Fairview/Kitsilano Ballroom

Sarah Wang^1,3 (), Katherine Sendek², Tamara Swaab^1,3; ¹University of California, Davis, ²UiT The Arctic University of Norway, ³Center for Mind and Brain, University of California, Davis

Research on bilingual language comprehension has revealed differences in how bilinguals represent and predict words in their second language (L2). Such studies often rely on normative measures of word predictability—sentence cloze probability, which reflects the consistency of sentence completions, and forward association strength, which reflects the consistency of word-to-word associations. However, because norming studies typically come from monolingual speakers, it remains unclear whether these norms accurately reflect bilinguals’ predictive expectations in their L2. To test this, we collected sentence cloze probability and forward association norms from 170 Spanish–English bilinguals, 135 Mandarin–English bilinguals, and 37 English monolinguals. Proficiency was assessed with the Language History Questionnaire 3.0 and the LexTALE in English, Spanish or Chinese. English monolinguals showed the greatest consistency of cloze and association responses indicating stronger convergence on shared contextual expectations. Within bilingual subgroups, English proficiency predicted response consistency, though its effects varied by group and task. For Mandarin–English bilinguals, higher English proficiency was associated with greater consistency in sentence completions (p < .001) but not in word associations. For Spanish–English bilinguals, English proficiency showed a trend toward greater consistency in cloze completions (p = .091) and significantly predicted greater convergence in forward association responses (p = .0045). Overall, bilinguals showed greater variability reflecting differences in language experience. These findings show that predictive norms vary with bilingual experience. Establishing bilingual-specific normative datasets will enable more precise modeling of how prediction is implemented in the bilingual brain, linking language experience, expectation, and neural computation.

Topic Area: LANGUAGE: Semantic