The Realization of Scalar Inferences: Context Sensitivity without Processing Cost

Scalar inference is the phenomenon whereby the use of a less informative term (e.g., some of) is inferred to mean the negation of a more informative term (e.g., to mean not all of). Default processing accounts assume that the interpretation of some of as meaning not all of is realized easily and automatically (regardless of context), whereas context-driven processing accounts assume that it is realized effortfully and only in certain contexts. In the present study, participants’ self-paced reading times were recorded as they read vignettes in which the context did or did not bias the participants to make a scalar inference (to interpret some of as meaning not all of). The reading times suggested that the realization of the inference was influenced by the context, but did not provide evidence for processing cost at the time the inference is realized, contrary to the predictions of context-driven processing accounts. The results raise the question of why inferencing occurs only in certain contexts if it does not involve extra processing effort.

量级推理（scalar inference）指的是这样一种语言现象：当使用信息量较弱的术语（例如部分（some of））时，该表述会被听者推导为意指信息量较强的术语的否定含义，例如被理解为"并非全部（all of）"。默认加工理论认为，将"部分"解读为"并非全部"的过程轻松且自动发生，且不受语境影响；而语境驱动加工理论则主张，该解读过程需要付出认知努力，且仅会在特定语境下出现。本研究中，研究者记录了被试阅读情景短文时的自定步速阅读反应时（self-paced reading times），这些短文的语境要么会引导被试做出量级推理，即把"部分"解读为"并非全部"，要么不会产生此类引导作用。阅读反应时数据显示，量级推理的生成受语境影响，但并未在推理发生的节点观测到加工成本，这与语境驱动加工理论的预测相悖。该研究结果引出了一个新的问题：倘若量级推理无需额外付出加工成本，为何它仅会在特定语境中发生？