Linking Hypothesis and Number of Response Options Modulate Inferred Scalar Implicature Rate

Abstract

The past 15 years have seen increasing experimental investigations of core pragmatic questions in the ever more active and lively field of experimental pragmatics. Within experimental pragmatics, many of the core questions have relied on the operationalization of the theoretical notion of “implicature rate.” Implicature rate based results have informed the work on acquisition, online processing, and scalar diversity, inter alia. Implicature rate has typically been quantified as the proportion of “pragmatic” judgments in two-alternative forced choice truth value judgment tasks. Despite its theoretical importance, this linking hypothesis from implicature rate to behavioral responses has never been extensively tested. Here we show that two factors dramatically affect the “implicature rate” inferred from truth value judgment tasks: (a) the number of responses provided to participants; and (b) the linking hypothesis about what constitutes a “pragmatic” judgment. We argue that it is time for the field of experimental pragmatics to engage more seriously with its foundational assumptions about how theoretical notions map onto behaviorally measurable quantities, and present a sketch of an alternative linking hypothesis that derives behavior in truth value judgment tasks from probabilistic utterance expectations.

Adults’ and Children’s Comprehension of Linguistic Disjunction

“…However, if a third intermediate option is provided, participants may opt to also express the incompleteness or infelicity of a guess in the task -depending on the label of the intermediate option. In a followup study, we found that participants opt for the intermediate option more often if it is labeled as "kinda right" rather than "neither" (Jasbi et al, 2019). Most importantly, children may differ from adults in how they approach intermediate judgments in forced choice tasks.…”

“…There are many possible labels for the middle option on a scale, including "kinda right", "kinda wrong", or "neither". A later experiment, tested different intermediate labels and found that adults consider "kinda right" to be a more suitable option for capturing pragmatic infelicities (see Jasbi et al, 2019). We expect similar behavior from labels that refer to non-maximal degrees of being "right" such as "a bit right" or "a little right".…”

The comprehension of grammaticalized implicit meanings in SPCD and ASD children: A comparative study

“…Participants' task was to judge to what extent the sentence matches the picture: to what degree the sentence gives a true description of the depicted scenario. A ternary scale was employed (Figure 1) because it has been shown to be more adequate than the binary choice to detect sensitivity to false implicit meanings (Katsos & Bishop, 2011) and deviations from complete truth in the case of partially correct descriptions more generally (Jasbi et al, 2019).…”

When pragmatics matters more for truth-value judgments: An investigation of quantifier scope ambiguity

“…To connect our model's predictions with the available truth-value judgment data in the descriptive truth-value judgment tasks described above, we follow recent suggestions in the literature for how to treat truth-value judgments. In particular, truth-value judgments are not viewed as pure language comprehension behavior, but rather as a form of language production (e.g., Degen & Goodman 2014;Jasbi et al 2019). Recall from our discussion of the task above that it does not present as a typical comprehension task because both the participant and the speaker in the particular truth-value judgment tasks we model are already aware of the true world state.…”

“…To model the utterance endorsement implicit in truth-value judgment behavior, we need one more level of inference. As mentioned above, we follow Degen & Goodman (2014) and Jasbi et al (2019) in modeling descriptive truth-value judgment data as speaker production behavior, which means we need to generate predictions from a speaker layer in our model. However, S 1 is not a reasonable model of a human speaker in the task because S 1 jointly observes the world state, the intended scope interpretation, and the intended QUD; human participants observe only the world state (e.g., the number of horses who jumped).…”