B1706 - Semantics (1) (LM)

Learning outcomes

The course is an introduction to the study of meaning in language, and how meaning is encoded in constructions belonging to different structural levels (morphology, syntax, discourse). The course focuses on the following aspects: lexical semantics; grammatical semantics; meaning representation; meaning, cognition and categorization; meaning and variation. Students will become familiar with the main theoretical models within the field, as well as with research methods and tools (including computational ones) for the collection and analysis of linguistic data, from both an intra-linguistic and a cross-linguistic perspective.

Course contents

Everything we do linguistically is aimed at creating messages, and therefore meanings that can be conveyed in some form.

This course is an introduction to the study of meaning in natural language and to the ways in which meaning is "packaged" in linguistic constructions that belongs to different structural levels (morphology, syntax, discourse).

The following general questions will be tackled:

• What is meaning? What is the difference between denotation and connotation, sense and reference, meaning and encyclopedic knowledge?
• Where is meaning? Which are the linguistic units that bear meaning? What is the difference between lexical semantics and grammatical semantics?
• What kinds of semantic relations do we have?
  
• How do we represent meaning? Which are the main relevant theoretical models? And how can we account for non-literal expressions?
  
• What is the relation between meaning and cognition, between language and thought? How does categorization work?
  

We will then focus on specific topics. During the first 30 hours (6 ECTS course), we will cover the following areas in greater depth:

1. competition between different forms to express the same function, at both the morphological and the syntactic-discursive levels;
2. evaluative semantics, with particular reference to approximation and prototypicality, at both the morphological and the syntactic-discursive levels;
3. linguistic creativity, with particular reference to the manipulation of fixed expressions (e.g. proverbs) to generate new expressions.

During the following 15 hours (9 ECTS course), we will focus on verbal semantics: verb classes and argument structure alternations, the encoding of aspect and other non-traditional grammatical categories (e.g. mirativity and frustrativity). Finally, a dedicated tutorial will introduce the use of corpora for the study of meaning.

During the course hands-on workshop sessions will be organized for the analysis and collaborative discussion of linguistic data.

NOTA BENE – This is an advanced course in linguistics. A basic knowledge of general linguistics is required. Students who have no prior knowledge of the field are strongly advised to study an introductory linguistics textbook before the classes start (e.g. Graffi & Scalise 2013 or Berruto & Cerruti 2011).

Readings/Bibliography

Textbook

• Riemer, Nick. 2010. Introducing semantics. Cambridge: Cambridge University Press [except chapters 4 and 6].

Articles

• Aronoff, Mark. 2016. Competition and the lexicon. In Annibale Elia, Claudio Iacobini & Miriam Voghera (eds), Livelli di analisi e fenomeni di interfaccia, 39–52. Roma: Bulzoni.
• Grandi, Nicola. 2017. Intensification processes in Italian: A survey. In Maria Napoli e Miriam Ravetto (eds),Exploring Intensification. Synchronic, diachronic and cross-linguistic perspectives, 55–77. Amsterdam: Benjamins.
• Hartmann, Stefan & Tobias Ungerer. 2023. Attack of the snowclones: A corpus-based analysis of extravagant formulaic patterns. Journal of Linguistics 60(3). 599-634.
• Kuteva, Tania, Bas Aarts, Gergana Popova & Anvita Abbi. 2019. The grammar of ‘non-realization’. Studies in Language 43(4). 850–895. [for the 9 ECTS course only]
• Masini, Francesca, Muriel Norde & Kristel Van Goethem. 2023. Approximation in morphology: A state of the art. Zeitschrift für Wortbildung / Journal of Word Formation 7(1). 1–26.

Further readings on specific topics may be given during classes. All materials used during the course (slides, articles, etc.) are part of the readings for the oral exam.

Teaching methods

All topics will be discussed with reference to data from different languages. Some IT tools for the collection and analysis of relevant linguistic data will be employed and illustrated.
In addition to traditional lectures, students will be involved in lab/group activities.

Assessment methods

The final oral exam aims at assessing the theoretical notions acquired by the students during the course, as well as their ability to tackle with specific questions and to analyze concrete cases of linguistic analysis. The oral exam consists of three questions, each of which focuses on one of the program topics.

Assessment criteria:

• accuracy and completeness of the answers;
• appropriate use of academic language and linguistic terminology;
• ability to provide examples and analyse authentic linguistic phenomena;
• clarity of presentation and quality of argumentation.

Those students who demonstrate to have a global and harmonious knowledge of the subject and its specific language/terminology, to communicate ideas in a proper and clear way and to have acquired adequate analysis skills will get high grades.

A partial knowledge of the subject and its specific language/terminology, an overall fair but not perfect way of communicating, and less refined analysis skills imply average grades.

A limited knowledge of the subject and its specific language/terminology and poor communication and analysis skills imply low grades.

Those students who prove to have an inadequate and/or insufficient knowledge of the subject (in both its theoretical and applied parts) and its specific language/terminology will fail the exam. 

 

Note on the Use of Artificial Intelligence (AI)
AI tools may be used to support independent study by providing explanations, summaries, and opportunities for self-assessment. However, the use of AI during assessment is strictly prohibited; any such use constitutes a breach of academic integrity.

More info: University Policy for Ethical and Responsible Use of Generative Artificial Intelligence in Teaching and Research Activities

 

Students with SLDs or temporary or permanent disabilities: we suggest that you contact the relevant university office (https://site.unibo.it/studenti-con-disabilita-e-dsa/en) and your professor immediately to work together to find the most effective strategies for attending classes and/or preparing for exams. Any requests for accommodations must be made at least 15 days before the date of the exam, by sending an email to the lecturer and copying (Cc) the email address disabilita@unibo.it (in case of disability) or dsa@unibo.it (for students with Specific Learning Difficulties).

Teaching tools

PowerPoint presentations and/or printed handouts will support the lectures. Computational tools and web resources for data analysis will also be displayed through a projector.

All materials will be published on the Virtuale platform every week and are part of the readings for the oral exam for students who attend classes.

Office hours

See the website of Francesca Masini