Course Structuring causal models for natural language

ECTS: 1

Course leader: Rebekah Brita Baglini

Language: English

Graduate school: Faculty of Arts

Course fee: 0.00 DKK

Status: Course is open for application

Semester: Spring 2024

Application deadline: 26/02/2024

Cancellation deadline: 26/02/2024

Course type: Blended learning

Start date: 13/03/2024

Administrator: Henriette Jaquet

NB.

All students are placed on a waiting list until we reach application deadline.

NB.

Please note that for this course registration is binding unless you are prevented by illness.

Natural languages provide a rich set of implicit and explicit means for expressing causal relationships (e.g., causative verbs and/or morphology, causal conjunctions and complementizers). The semantics of such causal expressions is indicative of what constitutes our causal knowledge, insofar as observable similarities and differences between causal expressions reflect the types of information to which we attend in cognitive causal reasoning.

This course introduces a framework for modeling causal relationships, and shows that such a framework can be fruitfully translated into a semantic system which captures the factors licensing causal inference and interpretation in natural languages. The underlying assumption of this approach is that our use of causal language reflects the structure and logic of an independent cognitive system for encoding, representing, and reasoning about causation as we perceive it in the world around us.

Aim:

1. Introduction of a formal representational system for causal dependencies, and of a corresponding semantic framework to define linguistically-relevant relationships. For this purpose, we introduce Structural Equation Modelling (SEM), which provides the tools for a rigorous model-theoretic approach to the semantics of causal expressions.

2. Analyzing the differential interpretation of causal expressions, using the formal tools developed in I to develop a principled semantic theory.

Literature:

Required are in bold:

Baglini, Rebekah and Elitzur A. Bar-Asher Siegal, 2021. Direct causation: A new approach to an old question, U. Penn Working Papers in Linguistics 26 (1): 19–28.

Bar-Asher Siegal, Elitzur A., Noa Bassel and York Hagmayer. 2021. Causal selection – the linguistic take. Experiments in Linguistic Meaning 1: 27-38

Bar-Asher Siegal, Elitzur A. and Nora Boneh. 2020. Causation: from metaphysics to semantics and back. In Bar-Asher Siegal, Elitzur and Boneh, Nora (editors), Perspectives on Causation. Springer. Pp. 3-51.

Fodor, Jerry, A. 1970. Three Reasons for Not Deriving "Kill" from "Cause to Die". Linguistic Inquiry 1: 429-438

Hitchcock, Christopher. 2009. Structural equations and causation: six counterexamples. Philosophical Studies 144: 391-401

Hobbs, Jerry. 2005. Toward a useful concept of causality for lexical semantics. Journal of Semantics 22: 181-209.

Mackie, J.L. 1965. Causes and conditions. American Philosophical Quarterly 2: 245-264.

Neeleman, Ad and Hans Van de Koot. 2012. The Linguistic Expression of Causation. In: Everaert, Martin. Marijana Marelj, and Tal Siloni (eds.) The Theta System: Argument Structure at the Interface, 20-51. Oxford: Oxford University Press.

Shibatani, Masayoshi. 1976. The grammar of causative constructions: A conspectus. In Shibatani, Masayoshi. (Ed.), The grammar of causative constructions (Syntax and Semantics 6), 1-40. New York: Academic Press.

Shibatani, Masayoshi & Prashant Pardeshi. 2002. The causative continuum. In Masayoshi Shibatani (Ed.), The Grammar of Causation and Interpersonal Manipulation, 85-126. Amsterdam: John Benjamins

Sloman, Steven. 2005. Causal models: how people think about the world and its

Wolff, Phillip. 2003. Direct causation in the linguistic coding and individuation of causal events. Cognition 88: 1-48 

Target group:

PhD students at all level.

Form:

Lectures, discussions and practical exercises.

Lecturer:

Professor Elitzur Bar-Asher Siegal (ebas@mail.huji.ac.il)

Venue:

Campus Aarhus, TBA

 

Course dates:

  • 13 March 2024 12:00 - 17:00