[COCOA] Jürgen Bohnemeyer (SUNY Buffalo) / Julie Goncharov (Univ. Göttingen)

08
mar.
2024.
15h00
17h00
Jürgen Bohnemeyer (SUNY Buffalo) / Julie Goncharov (Univ. Göttingen)

zoom

Jürgen Bohnemeyer (Buffalo)

Using statistical classification to discover cross-linguistic semantic prototypes: The causation domain

abstract en pdf ci-dessous

 

Julie Goncharov (Göttingen)

Subject obviation and self-locating knowledge

In this paper, I connect two threads that have been recently explored by a number of scholars. The first thread comes from the discussion of the so-called subject obviation and has to do with the idea that subject obviation is related to a direct experience or event de se interpretation (e.g., Schlenker 2005, 2011; Szabolcsi 2021). The second thread comes from the literature on intend and intending which are argued to involve self-referential properties (e.g., Grano 2021). I propose a conceptual modification of the current analyses, in which direct experience, event de se, and intending are unified in terms of self-locating beliefs. The proposal is implemented in Stalnaker’s framework in which the Common Ground is represented as a set of multi-centered possible worlds compatible with how participants of the conversation locate themselves and each other in the actual world (Stalnaker 2008, 2014). The key idea of the proposal is that in case of direct experience and intending, self-mislocation is pragmatically impossible in contrast to simple confusion about one’s identity, time, or place. As a result, the Common Ground does not include worlds in which the participants of the conversation mislocate themselves and each other with respect to their direct experiences or intentions. Since to assert an attitude ascription involving self-locating information is to exclude certain possibilities from the Common Ground and the subject has to locate herself in the possibilities to be excluded, the Common Ground containing no self-mislocating information is ill-suited for such assertions.

 

Attachment Size
CAL_COCOA_abstract.pdf514.14 Ko 514.14 Ko
Pas d'interprétation en LSF