Contrapuntal Harmony in Civilizational Interaction: A Syncretic Framework Bridging Music Theory and Evolutionary Game Theory

Full paper in uploaded Images : (pages 1 ~ 7) Preprint Version : ****** Although the model is innovative, its final acceptance in academic circles requires further empirical validation and review. Limitations and Future Work Current Limitations • Data Bias: The calibration relies predominantly on data from Western and East Asian contexts (e.g., Hofstede, WVS), possibly limiting the model’s global applicability. • Static Calibration: Cultural parameters are assumed to be static; however, cultural dynamics are inherently fluid over time. Future Directions • Dynamic Models: Integration of state-space models to capture temporal evolution of cultural values. • Reinforcement Learning: Applying RL methods to continuously optimize parameter settings based on new data. • Broader Data Integration: Expanding the dataset to include Afrobarometer and Latinobarómetro for a more globally representative calibration.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-30
DOI
https://doi.org/10.5281/zenodo.15108249
Primary Topic
Language and cultural evolution
Type
article
Field-Weighted Citation Impact
0.00
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article

Contrapuntal Harmony in Civilizational Interaction: A Syncretic Framework Bridging Music Theory and Evolutionary Game Theory

Zenodo (CERN European Organization for Nuclear Research)
Language and cultural evolution
article

Contrapuntal Harmony in Civilizational Interaction: A Syncretic Framework Bridging Music Theory and Evolutionary Game Theory

article en

Abstract

Full paper in uploaded Images : (pages 1 ~ 7) Preprint Version : ****** Although the model is innovative, its final acceptance in academic circles requires further empirical validation and review. Limitations and Future Work Current Limitations • Data Bias: The calibration relies predominantly on data from Western and East Asian contexts (e.g., Hofstede, WVS), possibly limiting the model’s global applicability. • Static Calibration: Cultural parameters are assumed to be static; however, cultural dynamics are inherently fluid over time. Future Directions • Dynamic Models: Integration of state-space models to capture temporal evolution of cultural values. • Reinforcement Learning: Applying RL methods to continuously optimize parameter settings based on new data. • Broader Data Integration: Expanding the dataset to include Afrobarometer and Latinobarómetro for a more globally representative calibration.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 45%
Language and cultural evolution
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