Published February 8, 2022 | Version 1.0.0
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Supplementary Materials for 'Measuring and assessing indeterminacy and variation in the morphology-syntax distinction'

  • 1. Friedrich-Schiller-Universität Jena & MPI for Evolutionary Anthropology (Leipzig)
  • 2. MPI for Evolutionary Anthropology (Leipzig) & University of California Santa Barbara

Description

Supplementary materials for the article 'Measuring and assessing indeterminacy and variation in the morphology-syntax distinction' in Linguistic Typology (Vol. and No. TBD).

Abstract:

We provide a discussion of some of the challenges in using statistical methods to investigate the morphology-syntax distinction cross-linguistically. The paper is structured around three problems related to the morphology-syntax distinction; (i) the boundary strength problem; (ii) the composition problem; (iii) the architectural problem.
The boundary strength problem refers to the possibility that languages vary in terms of how distinct morphology and syntax are or the degree to which morphology is autonomous. The composition problem refers to the possibility that languages vary in terms of how they distinguish morphology and syntax: what types of properties distinguish the two systems. The architecture problem refers to the possibility that languages vary in terms of whether a global distinction between morphology and syntax is motivated at all and the possibility that languages might partition phenomena in different ways.
This paper is concerned with providing an overarching review of the methodological problems involved in addressing these three issues. We illustrate the problems using three statistical methods: correlation matrices, random forests with different choices for the dependent variable, and hierarchical clustering with validation techniques.

 

Overview of materials:

  • SM1: csv with the data
  • SM2: code and pdf for generating the correlation matrices
  • SM3: code and pdf for the random forest analyses
  • SM4: code and pdf for the clustering and cluster validation analyses

Files

SM1_Database.csv

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Additional details

Related works

Is supplement to
Journal article: 10.1515/lingty-2021-0041 (DOI)