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A corpus-based examination of scalar diversity
Chao Sun1, Ye Tian2, Richard Breheny3
1School of Chinese as a Second Language, Peking University.
Summary
Scalar diversity, the varied rate of scalar implicatures (SIs), significantly lessens in natural language. Theoretical factors explain most variation in both experimental and real-world language use.
Area of Science:
- Linguistics
- Psycholinguistics
- Cognitive Science
Background:
- Scalar diversity describes how different scalar expressions yield scalar implicatures (SIs) at varying rates.
- Previous research identified theoretically motivated factors influencing SI rates in controlled experiments.
- A gap exists in understanding if these observed differences in inference rates translate to natural language usage.
Purpose of the Study:
- To investigate the phenomenon of scalar diversity in naturally occurring language.
- To determine if scalar diversity observed in experiments is present in real-world discourse.
- To assess the explanatory power of existing SI theories on natural language data.
Main Methods:
- Analysis of a Twitter data corpus using a paraphrase task approach.
- Sampling actual language usage across a wide range of scalar expressions.
- Quantitative analysis to measure scalar diversity and identify explanatory factors.
Main Results:
- Scalar diversity significantly attenuates when measured in a corpus-based paraphrase task.
- Factors derived from SI theories explain nearly two-thirds of the variation in scalar diversity.
- The explanatory power of these factors holds for both experimental and natural language contexts.
Conclusions:
- Scalar diversity is less pronounced in natural language compared to controlled experimental settings.
- Theoretical factors related to scalar implicatures remain significant predictors of variation in natural language.
- Remaining unexplained variation may stem from uncertainty in scalar enrichment of adjectival expressions.
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