Authors :
Harshit Gupta
Volume/Issue :
Volume 10 - 2025, Issue 10 - October
Google Scholar :
https://tinyurl.com/mj6572fk
Scribd :
https://tinyurl.com/mpdtxv9n
DOI :
https://doi.org/10.38124/ijisrt/25oct1040
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Note : Google Scholar may take 30 to 40 days to display the article.
Abstract :
Language is the deepest algorithmic process the human mind has produced. Far from a mere communicative tool, it is
the structural record of how cultures compute their realities, codify cognition, and transmit adaptive intelligence. This paper
reconceptualizes language as a cultural algorithm: a recursive, self-organizing system in which ritual, trade, symbolism, and
social hierarchy serve as variables that iteratively generate linguistic complexity. Drawing on Daniel Everett’s (2017) claim
that language is a cultural invention rather than a biological inevitability, the study extends his argument through formal
modeling in the Integrated Cultural–Linguistic Heuristic Framework (ICLHF) and its derivative Cultural Adaptation and
Linguistic Resilience (CALR) model.
Using a hybrid dataset of 400 societies—half empirical, half simulated—the analysis quantifies how cultural structures
drive linguistic differentiation. Results demonstrate robust correlations (r = 0.54–0.74) between cultural pressures and
linguistic architectures and a decisive predictive relationship between linguistic hybridity and cultural resilience (R2 = 0.66).
The Neuro-Linguistic Integration Score (NLIS) and Cultural Resilience Metric (CRM) operationalize these dynamics as
measurable indices of cognitive adaptability.
The findings reinforce the proposition that diversity is an algorithmic feature, not a flaw. Linguistic plurality and
borrowing enhance neuroplasticity, enabling societies to maintain equilibrium under environmental and social stress. In
treating language as a computational mirror of cultural logic, this research reframes linguistic evolution as an act of
collective cognition—a living program written, debugged, and iterated across generations.
Keywords :
Language as a Cultural Algorithm, Cultural–Linguistic Coevolution, Integrated Cultural–Linguistic Heuristic Framework (ICLHF), Cultural Adaptation and Linguistic Resilience (CALR), Neuro-Linguistic Integration Score (NLIS), Cultural Resilience Metric (CRM), Linguistic Hybridity, Cultural Computation, Cognitive Anthropology, Computational Linguistics, Cultural Evolution, Bilingual Neuroplasticity, Symbolic Cognition, Information Theory in Culture, Systems Theory of Language, Algorithmic Civilization, Cognitive Ecology, Language Diversity and Resilience, Cross-Cultural Adaptation, Adaptive Communication Systems, Civilization Modeling.
References :
- Chomsky, N. (1980). Rules and Representations. Columbia University Press.
- Deacon, T. (1997). The Symbolic Species: The Co-evolution of Language and the Brain. W.W. Norton.
- Everett, D. (2017). How Language Began: The Story of Humanity’s Greatest Invention. Profile Books.
- Fauconnier, G., & Turner, M. (2002). The Way We Think: Conceptual Blending and the Mind’s Hidden Complexities. Basic Books.
- Henrich, J. (2016). The Secret of Our Success: How Culture Is Driving Human Evolution, Domesticating Our Species, and Making Us Smarter. Princeton University Press.
- Panini. (c. 500 BCE). Aṣṭādhyāyī. (Various translations).
- Saussure, F. de. (1916). Course in General Linguistics.
- Tomasello, M. (2008). Origins of Human Communication. MIT Press.
- Toynbee, A. J. (1946). A Study of History. Oxford University Press.
- Spengler, O. (1922). The Decline of the West. Alfred A. Knopf.
- Shannon, C. E. (1948). A Mathematical Theory of Communication. Bell System Technical Journal, 27(3), 379–423.
Language is the deepest algorithmic process the human mind has produced. Far from a mere communicative tool, it is
the structural record of how cultures compute their realities, codify cognition, and transmit adaptive intelligence. This paper
reconceptualizes language as a cultural algorithm: a recursive, self-organizing system in which ritual, trade, symbolism, and
social hierarchy serve as variables that iteratively generate linguistic complexity. Drawing on Daniel Everett’s (2017) claim
that language is a cultural invention rather than a biological inevitability, the study extends his argument through formal
modeling in the Integrated Cultural–Linguistic Heuristic Framework (ICLHF) and its derivative Cultural Adaptation and
Linguistic Resilience (CALR) model.
Using a hybrid dataset of 400 societies—half empirical, half simulated—the analysis quantifies how cultural structures
drive linguistic differentiation. Results demonstrate robust correlations (r = 0.54–0.74) between cultural pressures and
linguistic architectures and a decisive predictive relationship between linguistic hybridity and cultural resilience (R2 = 0.66).
The Neuro-Linguistic Integration Score (NLIS) and Cultural Resilience Metric (CRM) operationalize these dynamics as
measurable indices of cognitive adaptability.
The findings reinforce the proposition that diversity is an algorithmic feature, not a flaw. Linguistic plurality and
borrowing enhance neuroplasticity, enabling societies to maintain equilibrium under environmental and social stress. In
treating language as a computational mirror of cultural logic, this research reframes linguistic evolution as an act of
collective cognition—a living program written, debugged, and iterated across generations.
Keywords :
Language as a Cultural Algorithm, Cultural–Linguistic Coevolution, Integrated Cultural–Linguistic Heuristic Framework (ICLHF), Cultural Adaptation and Linguistic Resilience (CALR), Neuro-Linguistic Integration Score (NLIS), Cultural Resilience Metric (CRM), Linguistic Hybridity, Cultural Computation, Cognitive Anthropology, Computational Linguistics, Cultural Evolution, Bilingual Neuroplasticity, Symbolic Cognition, Information Theory in Culture, Systems Theory of Language, Algorithmic Civilization, Cognitive Ecology, Language Diversity and Resilience, Cross-Cultural Adaptation, Adaptive Communication Systems, Civilization Modeling.