Awesome

WALS-APiCS complexity

This repository contains code and data relevant to examining complexity of WALS-APiCS features following proposals made in this paper: https://benjamins.com/#catalog/journals/jpcl.27.1.01goo/ and procedures described in this draft paper: http://buffalo.edu/~jcgood/jcgood-ParadigmaticComplexityCreoles.pdf. Documentation is relatively sparse since it is not clear to me how much outside interest there will be in these materials. However, they are posted here in the interest of transparency and replicability. Please feel free to contact Jeff Good (jcgood@buffalo.edu) with any questions on how to use these materials. Please note that the database posted here is mostly based on content from the World Atlas of Language Structures (WALS; http://wals.info) and the Atlas of Pidgin and Creole Language Structures (APiCS; http://apics-online.info). If you choose to reuse this data, please cite these original sources as appropriate. Citation information can be found on the websites for each of these projects.

Brief descriptions of each file are given below

• APiCSFeatureComps.txt: Tabular data summarizing complexity values across WALS-APiCS features.

• APiCSLangComps.txt: Tabular data summarizing complexity values across WALS-APiCS languages for languages with values for most features.

• APiCSLangCompVals.txt: Specific complexity values for each APiCS features across each APiCS language.

• APiCSWALS.r: Automatically generated output for loading into R for statisical processing.

• APiCSWALSComplexity.sql: SQL dump of database used to encode complexity scores. This database combines data from WALS (http://wals.info) and APiCS (http://apics-online.info), and adds new information relevant to calculating syntagmatic and paradigmatic complexity of WALS-APiCS features. Details on the relevant methods and theoretical assumptions can be found in a draft paper submitted for publication that is posted here: http://buffalo.edu/~jcgood/jcgood-ParadigmaticComplexityCreoles.pdf. This paper also contains more detailed references. The database is designed to be used in conjunction with calculateComplexities.py to generate the complexity scores used in the paper linked to above.

• calculateComplexities.py: A script for generating various files and complexity scores for the study of WALS-APiCS patterns of complexity.

• CompDocumentation.txt: Documentation of criteria employed to determine maximum complexity across features.

• complexity.py: A set of Python methods for interacting with the database to generate complexity figures.

• FeatComp.txt: An output of all complexity scores across all features.

• README.md: This file.

• ValDocumentation.txt: Documentation of criteria employed to determine complexity level across each value.

• calculateComplexities.pyc: Python-generated file.

• complexity.pyc: : Python-generated file.

• LICENSE: License for material on this site.

• Various pdf files for visualizations of the data: aParHist.pdf featDistr.pdf featDistrBW.pdf featDistrPar.pdf featDistrParBW.pdf parDistr.pdf parDistrBW.pdf synDistr.pdf synDistrBW.pdf wParHist.pdf