Scalar inference calculation through the lens of degree estimates
Scalar inference (SI), e.g., utterances containing some being enriched to mean some but not all, is a central topic in semantics and pragmatics. Of recent interest in the experimental literature is scalar diversity: different lexical scales differ in their likelihood of leading to SI. Studies of sca...
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Cambridge University Press
2025-01-01
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| Series: | Language and Cognition |
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| Online Access: | https://www.cambridge.org/core/product/identifier/S1866980824000553/type/journal_article |
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| author | Eszter Ronai Ming Xiang |
| author_facet | Eszter Ronai Ming Xiang |
| author_sort | Eszter Ronai |
| collection | DOAJ |
| description | Scalar inference (SI), e.g., utterances containing some being enriched to mean some but not all, is a central topic in semantics and pragmatics. Of recent interest in the experimental literature is scalar diversity: different lexical scales differ in their likelihood of leading to SI. Studies of scalar diversity have almost exclusively relied on the so-called inference task. In this article, we highlight two shortcomings of the inference task: it biases participants by providing them with the stronger alternative, and it obscures pragmatic inferences other than SI. We offer as an alternative a degree estimate task to investigate utterances containing scalar terms. We validate the degree estimate task, i.a., by successfully replicating a previous finding about scalar diversity: that the distinctness of scalar terms (some versus all) is a significant predictor of it. We then use degree estimates to reassess previous inference task-based findings. Our results show that biasing discourse contexts lead to lower degree estimates (i.e., more strengthened meanings) than a manipulation with only, which contrasts with prior literature’s findings. The article concludes that the inference and degree estimate tasks both have advantages: the former offers a straightforward definition of SI calculation, while the latter avoids explicitly mentioning a negated stronger alternative. |
| format | Article |
| id | doaj-art-12d497ae29c24b06b479fc2000afbf23 |
| institution | Kabale University |
| issn | 1866-9808 1866-9859 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Language and Cognition |
| spelling | doaj-art-12d497ae29c24b06b479fc2000afbf232025-01-16T21:50:28ZengCambridge University PressLanguage and Cognition1866-98081866-98592025-01-011710.1017/langcog.2024.55Scalar inference calculation through the lens of degree estimatesEszter Ronai0Ming Xiang1Department of Linguistics, Northwestern University, Evanston, IL, USADepartment of Linguistics, The University of Chicago, Chicago, IL, USAScalar inference (SI), e.g., utterances containing some being enriched to mean some but not all, is a central topic in semantics and pragmatics. Of recent interest in the experimental literature is scalar diversity: different lexical scales differ in their likelihood of leading to SI. Studies of scalar diversity have almost exclusively relied on the so-called inference task. In this article, we highlight two shortcomings of the inference task: it biases participants by providing them with the stronger alternative, and it obscures pragmatic inferences other than SI. We offer as an alternative a degree estimate task to investigate utterances containing scalar terms. We validate the degree estimate task, i.a., by successfully replicating a previous finding about scalar diversity: that the distinctness of scalar terms (some versus all) is a significant predictor of it. We then use degree estimates to reassess previous inference task-based findings. Our results show that biasing discourse contexts lead to lower degree estimates (i.e., more strengthened meanings) than a manipulation with only, which contrasts with prior literature’s findings. The article concludes that the inference and degree estimate tasks both have advantages: the former offers a straightforward definition of SI calculation, while the latter avoids explicitly mentioning a negated stronger alternative.https://www.cambridge.org/core/product/identifier/S1866980824000553/type/journal_articlefocus semanticsinference taskQuestion Under Discussionscalar diversityscalar inference |
| spellingShingle | Eszter Ronai Ming Xiang Scalar inference calculation through the lens of degree estimates Language and Cognition focus semantics inference task Question Under Discussion scalar diversity scalar inference |
| title | Scalar inference calculation through the lens of degree estimates |
| title_full | Scalar inference calculation through the lens of degree estimates |
| title_fullStr | Scalar inference calculation through the lens of degree estimates |
| title_full_unstemmed | Scalar inference calculation through the lens of degree estimates |
| title_short | Scalar inference calculation through the lens of degree estimates |
| title_sort | scalar inference calculation through the lens of degree estimates |
| topic | focus semantics inference task Question Under Discussion scalar diversity scalar inference |
| url | https://www.cambridge.org/core/product/identifier/S1866980824000553/type/journal_article |
| work_keys_str_mv | AT eszterronai scalarinferencecalculationthroughthelensofdegreeestimates AT mingxiang scalarinferencecalculationthroughthelensofdegreeestimates |