Month: September 2017

Eventive vs. Evidential Speech Reports

Emar Maier

I argue for a distinction between eventive and evidential speech reports. In eventive speech reports the at-issue contribution is the introduction of a speech event with certain properties. Typical examples include direct and free indirect speech. In evidential speech reports, by contrast, the fact that something was said is not at issue, but serves to provide evidence for the reported content. Typical examples include Quechua reportative evidential morphology, Dutch reportative modals, or German reportive subjunctive. Following up on an observation by Von Stechow & Zimmermann (2005:fn.16), I argue that English indirect discourse is ambiguous. In the current framework this means it allows both an eventive reading, where a reported speech act is at issue, and an evidential reading, where it is backgrounded.

Explaining ‘EARLIEST’

Jessica Rest

The semantics of degree constructions has motivated the implementation of a MAX operator, a function from a set of degrees to its maximal member (von Stechow 1985, Rullmann 1995, a.o.). This operator is unsatisfying: it’s arbitrary (cf. MIN), and therefore not explanatory. There have thus been several calls to reduce MAX to a more pragmatic principle of maximal informativity (Dayal 1996, Beck & Rullmann 1999, Fox & Hackl 2007, von Fintel et al. 2014).

Intriguing differences between before and after have caused some to posit an EARLIEST operator in the temporal domain (Beaver & Condoravdi 2003, Condoravdi 2010). This operator is unsatisfying for similar reasons (cf. LATEST), and some have suggested it, too, can be redefined in terms of informativity (Rett 2015). However, recent cross-linguistic evidence (reported here) complicates the reduction of EARLIEST to `maximize informativity’: while counterparts of `before’ and `after’ across languages share many foundational semantic properties, they appear to differ in a principled way in how certain before constructions are interpreted. I discuss this and other related observations with respect to the future of a domain-general `maximize informativity’ program.

Counterfactuality and causal structure

Jos Tellings

The following is an example of a counterfactual conditional in English:

(1) If I had thrown a six, I would have won the game.

One normally infers from (1) that the antecedent is counterfactual (i.e. I did not throw a six; I write this as CF-p), and that the consequent is counterfactual (i.e. I did not win the game; written CF-q). Whereas most previous literature focuses on the counterfactuality of the antecedent exclusively (perhaps assuming that an analysis of CF-p extends to CF-q), this work provides an analysis for how the counterfactual inference of the consequent (CF-q) is generated, and explains its empirical distribution.

I identify several contexts in which the CF-q inference gets cancelled. In some of these, cancellation is the result of the presence of a specific lexical item (such as “also”). In other cases, it is the intonation contour of the conditional that leads to cancellation. By analyzing the topic-focus structure of conditionals, I argue that the various contexts in which CF-q gets cancelled have a pragmatic property in common: they are multiple cause contexts. This means that they make more than one cause for the same consequent salient.

The next step in my analysis is adopting an idea going back to Karttunen (1971), who suggests thatconditional perfection (the pragmatic strengthening of conditionals to biconditionals) is a necessary ingredient for the CF-q inference to arise. The key prediction, which has not been explored before, is that if for some reason conditional perfection is not triggered, the CF-q inference is not drawn. I derive the independent result that multiple cause contexts do not trigger conditional perfection. This provides the desired explanation of why in multiple cause contexts the CF-q inference is not drawn. This analysis opens a new way to investigate counterfactuality, namely by using tools from the study of discourse (questions and answers, topic and focus, exhaustivity). Finally, I sketch some directions of future work on how using causal networks to represent multiple causation can be applied to the pragmatics of counterfactual conditionals.