# Over-representation of phonological features in basic vocabulary doesn't replicate when controlling for spatial and phylogenetic effects

arXiv: https://arxiv.org/abs/2512.07543 · HTML: https://mlsanity.com/paper/2512.07543/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 87 references that are in the map.
- First posted on arXiv 8 Dec 2025.

## Builds on (most cited first, 3 of 3)

- [Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC](https://mlsanity.com/paper/1507.04544/) (2015)
- [Statistical methods for linguistic research: Foundational Ideas - Part II](https://mlsanity.com/paper/1602.00245/) (2016)
- [Using leave-one-out cross-validation (LOO) in a multilevel regression and poststratification (MRP) workflow: A cautionary tale](https://mlsanity.com/paper/2209.01773/) (2022)

## Abstract (arXiv)

The statistical over-representation of phonological features in the basic vocabulary of languages is often interpreted as reflecting potentially universal sound symbolic patterns. However, most of those results have not been tested explicitly for reproducibility and might be prone to biases in the study samples or models. Many studies on the topic do not adequately control for genealogical and areal dependencies between sampled languages, casting doubts on the robustness of the results. In this study, we test the robustness of a recent study on sound symbolism of basic vocabulary concepts which analyzed 245 languages.The new sample includes data on 2864 languages from Lexibank. We modify the original model by adding statistical controls for spatial and phylogenetic dependencies between languages. The new results show that most of the previously observed patterns are not robust, and in fact many patterns disappear completely when adding the genealogical and areal controls. A small number of patterns, however, emerges as highly stable even with the new sample. Through the new analysis, we are able to assess the distribution of sound symbolism on a larger scale than previously. The study further highlights the need for testing all universal claims on language for robustness on various levels.