Abstract
Public consultation has become an indispensable part of constitutional design, yet the voluminous, narrative data produced are often impractical to analyze. There are also few, if any, standards for such analysis. Using a comprehensive reference ontology from the Comparative Constitutions Project (CCP), we develop a new methodology to identify constitutional topics of most concern to citizens and compare these to topics in constitutions globally. We analyze data from Chile’s 2016 public consultations—an ambitious process that produced nearly 265,000 narrative responses and launched the constitutional reform process that remains underway today. We leverage advances in natural language processing, in particular sentence-level semantic similarity technology, to classify consultation responses with respect to constitutional topics. Our methodology has potential for advocates, drafters, and researchers seeking to analyze public consultation data that too often go unexamined.
Citation
@article{cruz2023measuring,
title={Measuring constitutional preferences: A new method for analyzing public consultation data},
author={Cruz, Andr{\'e}s and Elkins, Zachary and Gardner, Roy and Martin, Matthew and Moran, Ashley},
journal={Plos one},
volume={18},
number={12},
pages={e0295396},
year={2023},
doi = {10.1371/journal.pone.0295396}
}