The pragmatics of exhaustivity in embedded questions: an experimental comparison of know and predict in German and English

• Published in: Frontiers in psychology Vol. 14; p. 1148275
• Main Authors: Fricke, Lea, Destruel, Emilie, Zimmermann, Malte, Onea, Edgar
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 13.09.2023
• Subjects: embedded questions; English; exhaustivity; experimental pragmatics; German; probabilistic modeling; Psychology
• ISSN: 1664-1078; 1664-1078
• DOI: 10.3389/fpsyg.2023.1148275

Introduction We present a cross-linguistic experimental study that explores the exhaustivity properties of questions embedded under wissen/to know and korrekt vorhersagen/to correctly predict in German and English. While past theoretical literature has held that such embedded questions should only be interpreted as strongly exhaustive (SE), recent experimental findings suggest an intermediate exhaustive (IE) interpretation is also available and plausible. Methods Participants were confronted with a decision problem involving the different exhaustive readings and received a financial incentive based on their performance. We employed Bayesian analysis to create probabilistic models of participants' beliefs, linking their responses to readings based on utility maximization in simple decision problems. Results For wissen/to know, we found that the SE reading was most probable in both languages, aligning with early theoretical literature. However, we also attested to the presence of IE readings. For korrekt vorhersagen in German, the IE reading was most probable, whereas for the English phrase "to correctly predict," a preference for the SE reading was observed. Discussion This cross-linguistic variation correlates with independent corpus data, indicating that German vorhersagen and English to predict are not lexically equivalent. By including an explicit pragmatic component, our study complements previous work that has focused solely on the principled semantic availability of given readings.