36.1032, Summer Schools: Summer School on Computational Approaches to Historical Linguistics (United Kingdom)

[The LINGUIST List]

LINGUIST List: Vol-36-1032. Mon Mar 24 2025. ISSN: 1069 - 4875.

Subject: 36.1032, Summer Schools: Summer School on Computational Approaches to Historical Linguistics (United Kingdom)

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Date: 24-Mar-2025
From: Dimitar Kazakov [dimitar.kazakov at york.ac.uk]
Subject: Summer School on Computational Approaches to Historical Linguistics


Summer School on Computational Approaches to Historical Linguistics

Host Institution: University of Plovdiv Paisii Hilendarski, Plovdiv,
Bulgaria
Coordinating Institution: University of York, UK
Website: https://ca2hl.org/

Dates: 21-Jul-2025 - 01-Aug-2025
Location: Plovdiv, United Kingdom

Minimum Education Level: Graduate students and academics

Special Qualifications: An interest in the topic and a background in
related disciplines, such as Linguistics, Computational Linguistics,
Computer Science or Statistics.

Focus: * Acquire the theoretical knowledge and practical skills
described in the syllabus* (see below);
* Collect new data (parameter settings and evidence) on languages
represented among the participants;
* Produce an archival record of the data and findings co-authored by
all contributors.
*Syllabus:
Week 1: Introduction to Historical Linguistics. The Comparative
Method. The Parametric Comparison Method (PCM). Case Study: The
Indo-European Language Family. Language trees and language contact.
Case Study: The Balkan Sprachbund.
Week 2: Parameter Setting for PCM. Case study: Analysing Syntactic
Parameters in Participants’ Languages. Data Visualisation: Gradient
Maps of Principal Components and Their Historical Implications.
Exploring Migrations and Cultural Contact through Linguistic Evidence.
Clustering Techniques for Phylogenetic Tree Generation. Advanced
Tools: Using Large Language Models (LLMs) for Parameter Evidence
Collection.
In more detail:
Week 1 covers the basics of the classical (lexical-etymological)
comparative method for phylogenetic reconstruction and a full
introduction to the innovative syntactic-parametric method. The theory
of parameters from the perspective of language typology and of
language acquisition will be introduced. Then it will be shown how to
apply current syntactic wisdom and models to define the grammar of a
new language (set its parameters) starting from either speakers’
knowledge or portions of text. The place of historical linguistics
among cognitive neurosciences will be discussed.
Week 2 focuses on applying the knowledge acquired in Week 1 to
collecting data on syntactic parameters and its use in historical
linguistics. Participants will systematically analyze the syntactic
parameters of their chosen language by responding to a predefined set
of questions for each parameter and documenting example sentences that
serve as evidence. The collected data will be integrated with existing
datasets to generate gradient maps of principal components in the
tradition of Cavalli-Sforza’s work in genetic classification of
populations, facilitating discussions on their potential relevance as
evidence for historical migrations and cultural contact. Additionally,
participants will acquire hands-on experience with clustering
techniques derived from bioinformatics to construct phylogenetic trees
based on the compiled data. The week will conclude with an exercise in
employing large language models (LLMs), such as ChatGPT, to assist in
the identification and documentation of syntactic parameters of a
given language.

Description:

Speakers: Giuseppe Longobardi (University of York), Paola Crisma
(University of Trieste), Dimitar Kazakov (University of York)
We’re excited to invite graduate students and researchers to CA2HL
2025, an intensive two-week summer school focused on cutting-edge
computational methods in historical linguistics.
Participants will engage with the Parametric Comparison Method (PCM),
a novel approach to modelling language relationships through syntactic
parameters, while contributing to the collection and analysis of new
linguistic data. The collected data will be integrated with existing
datasets to generate gradient maps of principal components in the
tradition of Cavalli-Sforza’s work in genetic classification of
populations, facilitating discussions on historical migrations and
cultural contact. Participants will also acquire hands-on experience
with clustering techniques derived from bioinformatics to construct
phylogenetic trees of the studied languages. The material will
conclude with an exercise in employing large language models (LLMs),
such as ChatGPT, to assist in the identification and documentation of
syntactic parameters of a given language.
The programme combines expert-led lectures, hands-on collaboration,
and individual study, providing a unique opportunity to deepen your
research and build lasting academic connections.
Background:
Historical linguistics studies how languages change or remain similar
over time. It investigates the development, evolution, and
relationships among languages, focusing on their phonology (sounds),
morphology (word structure), syntax (sentence structure), semantics
(meanings), and lexicon (vocabulary). It also examines how and why
languages diverge, interact, and sometimes converge through processes
such as language contact and borrowing. Historical linguistics aims to
classify languages into families, understand the mechanisms and causes
of language change, reconstruct proto-languages, and trace the
cultural and social history of linguistic communities.
During the school’s two weeks particular focus will be put on the
novel Parametric Comparison Method (PCM). The PCM is a theoretical
approach in historical linguistics that focuses on the comparison of
grammatical parameters rather than traditional vocabulary-based or
phonological comparisons. This method derives from the idea that
languages can be compared - and a significant historical signal
retrieved - through a finite set of syntactic parameters that
determine structural variation across languages. PCM is rooted in the
framework of Universal Grammar, assuming all human languages share a
common set of principles, which allow for variation through
“parameters”, discrete, normally binary, settings that determine
specific syntactic properties, such as whether null subjects are
allowed (e.g. Italian) or not (e.g. English). Instead of comparing
word lists (as in the etymological method) and phonological changes
(as in phonological reconstruction), PCM identifies and compares
syntactic parameters across languages and families (even remote ones)
where shared parameter settings may suggest genealogical relationships
or contact-induced convergence.
The method is susceptible to borrowing effects, but, unlike vocabulary
and sounds, which can be borrowed across unrelated languages,
syntactic parameters are less likely to be directly borrowed. It is
applicable to languages with scarce lexical or phonological data but
robust syntactic descriptions, and aims to offer insights into deeper
relationships among languages by focusing on deep structural features
rather than surface-level elements. The PCM has been used to explore
both relationships within language families and between distant
languages, such as hypothesising connections between language families
in macro-comparative studies. For example, in comparing Japanese and
Korean, the PCM might focus on shared syntactic features, such as
their head-final structures or similar presence/absence of grammatical
features, rather than relying on vocabulary. This could help assess
whether these similarities reflect genetic relatedness, contact, or
just chance typological affinity.
As for all most modern and sophisticated approaches to historical
linguistics, the PCM requires substantial quantitative and
computational treatment of the data and of the hypotheses of language
relatedness. This is an especially stimulating challenge for both
linguists and computer scientists interested in an innovative
syntactic method of comparison and reconstruction: the particular and
largely unexplored formal properties of historical syntax seem to
require specific computational algorithms that cannot be borrowed
unchanged from those used for phylogenetic inference in biology and
lexical historical linguistics.
References:
Campbell, Lyle. Historical Linguistics: An Introduction, EUP.
Cavalli-Sforza, Luigi Luca (2000). Genes, Peoples and Languages.
Penguin Group.
Ceolin Andrea, Cristina Guardiano, Giuseppe Longobardi, Monica A
Irimia, Luca Bortolussi and Andrea Sgarro (2021). At the boundaries of
syntactic prehistory, Philosophical Transactions of the Royal Society
B 376 (1824), 20200197.
Crisma, Paola, and Giuseppe Longobardi (eds, 2009). Historical Syntax
and Linguistic Theory:. Introduction. OUP.
Guardiano Cristina and Giuseppe Longobardi, (2017). Parameter theory
and parametric comparison, in Ian Roberts (ed.) Oxford Handbook of UG,
OUP.
Guardiano Cristina, Giuseppe Longobardi, Guido Cordoni and Paola
Crisma (2020). Formal syntax as a phylogenetic method, R.D. Janda, B.
Joseph, B. Vance (eds) Blackwell's Handbook of Historical Linguistics
Volume II, 145-182
Lightfoot, David. How to Set Parameters: Arguments from Language
Change.
Longobardi, Giuseppe, and Cristina Guardiano (2009). Evidence for
syntax as a signal of historical relatedness, Lingua, 119.
Roberts, Ian, (2007/2022) Diachronic syntax, CUP.

Tuition: €99 (2-week fee)
Tuition Explanation: This amount covers the tuition over the full
2-week period and does not include accommodation or meals (see web
site for more information). If you want to attend only the first or
second week of the summer school, please indicate this in the
registration form and contact the organisers. The same applies if the
tuition fee is a potential obstacle for your attendance.

Linguistic Field(s): Genetic Classification
                     Historical Linguistics

Registration Open until 15-Jul-2025

Contact Person: Dr Dimitar Kazakov
                Email: dimitar.kazakov at york.ac.uk

Apply by Email: dimitar.kazakov at york.ac.uk
Apply on the web: https://forms.gle/QU3cgXeX9RaPuCSX8

Registration Instructions:
Please complete the registration of interest form and await a reply
from the organisers.



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