A phylogenetic classification of the Je language family

<ns5:p>Introduction This study investigates the Je language family and Macro-Je phylum, addressing a significant gap in previous research by applying quantitative methods to its classification. Dataset The study compares a subset of 303 concepts from 14 languages, primarily sourced from Swadesh lists and culturally relevant terms, providing a robust foundation for phylogenetic analysis. Methods Bayesian phylogenetic inference and NeighborNet methods were employed to analyze the dataset. These approaches enabled the reconstruction of evolutionary relationships within the Je family, facilitating the identification of language divergence patterns and their historical dynamics. Results The analysis reveals well-supported Northern, Central, and Southern subgroups within the Je family, demonstrating clear geographical clustering. The phylogenetic tree aligns with existing hypotheses while offering new insights into the family’s structure. Discussion The findings were contextualized within pre-Columbian archaeological frameworks, drawing parallels between linguistic divergence and material culture. These connections support the hypothesis that the Je language family’s development aligns with distinct cultural and geographical distributions observed in archaeological records. Conclusion and Future Directions This study affirms the genetic coherence of the Je family and highlights opportunities for future research, including the incorporation of non-Je languages in the Macro-Je phylum and expanded datasets to refine the understanding of this diverse linguistic group.</ns5:p>

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Journal
Open Research Europe
Published
2025-05-19
DOI
https://doi.org/10.12688/openreseurope.19346.3
Primary Topic
Authorship Attribution and Profiling
Type
article
Field-Weighted Citation Impact
0.00

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article

A phylogenetic classification of the Je language family

Fabrício Ferraz Gerardi, Tim Wientzek, Jonas Gregório de Souza, Ivan Roksandic et al.
Open Research Europe
Authorship Attribution and Profiling
article

A phylogenetic classification of the Je language family

Fabrício Ferraz Gerardi, Tim Wientzek, Jonas Gregório de Souza, Ivan Roksandic, Fernando O. de Carvalho
article en

Abstract

<ns5:p>Introduction This study investigates the Je language family and Macro-Je phylum, addressing a significant gap in previous research by applying quantitative methods to its classification. Dataset The study compares a subset of 303 concepts from 14 languages, primarily sourced from Swadesh lists and culturally relevant terms, providing a robust foundation for phylogenetic analysis. Methods Bayesian phylogenetic inference and NeighborNet methods were employed to analyze the dataset. These approaches enabled the reconstruction of evolutionary relationships within the Je family, facilitating the identification of language divergence patterns and their historical dynamics. Results The analysis reveals well-supported Northern, Central, and Southern subgroups within the Je family, demonstrating clear geographical clustering. The phylogenetic tree aligns with existing hypotheses while offering new insights into the family’s structure. Discussion The findings were contextualized within pre-Columbian archaeological frameworks, drawing parallels between linguistic divergence and material culture. These connections support the hypothesis that the Je language family’s development aligns with distinct cultural and geographical distributions observed in archaeological records. Conclusion and Future Directions This study affirms the genetic coherence of the Je family and highlights opportunities for future research, including the incorporation of non-Je languages in the Macro-Je phylum and expanded datasets to refine the understanding of this diverse linguistic group.</ns5:p>

Open Research EuropeVol. 5
Universitat Pompeu Fabra (ES), Bernstein Center for Computational Neuroscience Tübingen (DE), University of Tübingen (DE), Universidade Federal do Estado do Rio de Janeiro (BR), The University of Winnipeg (CA)
Horizon 2020 Framework Programme
Openalex Percentile: Top 95%
Authorship Attribution and Profiling
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