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Inferring Cultural Landscapes with the Inverse Ising Model
The space of possible human cultures is vast, but some cultural configurations are more consistent with cognitive and social constraints than others. This leads to a “landscape” of possibilities that our species has explored over millennia of cultural evolution. However, what does this fitness lands...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9955041/ https://www.ncbi.nlm.nih.gov/pubmed/36832631 http://dx.doi.org/10.3390/e25020264 |
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author | Poulsen, Victor Møller DeDeo, Simon |
author_facet | Poulsen, Victor Møller DeDeo, Simon |
author_sort | Poulsen, Victor Møller |
collection | PubMed |
description | The space of possible human cultures is vast, but some cultural configurations are more consistent with cognitive and social constraints than others. This leads to a “landscape” of possibilities that our species has explored over millennia of cultural evolution. However, what does this fitness landscape, which constrains and guides cultural evolution, look like? The machine-learning algorithms that can answer these questions are typically developed for large-scale datasets. Applications to the sparse, inconsistent, and incomplete data found in the historical record have received less attention, and standard recommendations can lead to bias against marginalized, under-studied, or minority cultures. We show how to adapt the minimum probability flow algorithm and the Inverse Ising model, a physics-inspired workhorse of machine learning, to the challenge. A series of natural extensions—including dynamical estimation of missing data, and cross-validation with regularization—enables reliable reconstruction of the underlying constraints. We demonstrate our methods on a curated subset of the Database of Religious History: records from 407 religious groups throughout human history, ranging from the Bronze Age to the present day. This reveals a complex, rugged, landscape, with both sharp, well-defined peaks where state-endorsed religions tend to concentrate, and diffuse cultural floodplains where evangelical religions, non-state spiritual practices, and mystery religions can be found. |
format | Online Article Text |
id | pubmed-9955041 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99550412023-02-25 Inferring Cultural Landscapes with the Inverse Ising Model Poulsen, Victor Møller DeDeo, Simon Entropy (Basel) Article The space of possible human cultures is vast, but some cultural configurations are more consistent with cognitive and social constraints than others. This leads to a “landscape” of possibilities that our species has explored over millennia of cultural evolution. However, what does this fitness landscape, which constrains and guides cultural evolution, look like? The machine-learning algorithms that can answer these questions are typically developed for large-scale datasets. Applications to the sparse, inconsistent, and incomplete data found in the historical record have received less attention, and standard recommendations can lead to bias against marginalized, under-studied, or minority cultures. We show how to adapt the minimum probability flow algorithm and the Inverse Ising model, a physics-inspired workhorse of machine learning, to the challenge. A series of natural extensions—including dynamical estimation of missing data, and cross-validation with regularization—enables reliable reconstruction of the underlying constraints. We demonstrate our methods on a curated subset of the Database of Religious History: records from 407 religious groups throughout human history, ranging from the Bronze Age to the present day. This reveals a complex, rugged, landscape, with both sharp, well-defined peaks where state-endorsed religions tend to concentrate, and diffuse cultural floodplains where evangelical religions, non-state spiritual practices, and mystery religions can be found. MDPI 2023-01-31 /pmc/articles/PMC9955041/ /pubmed/36832631 http://dx.doi.org/10.3390/e25020264 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Poulsen, Victor Møller DeDeo, Simon Inferring Cultural Landscapes with the Inverse Ising Model |
title | Inferring Cultural Landscapes with the Inverse Ising Model |
title_full | Inferring Cultural Landscapes with the Inverse Ising Model |
title_fullStr | Inferring Cultural Landscapes with the Inverse Ising Model |
title_full_unstemmed | Inferring Cultural Landscapes with the Inverse Ising Model |
title_short | Inferring Cultural Landscapes with the Inverse Ising Model |
title_sort | inferring cultural landscapes with the inverse ising model |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9955041/ https://www.ncbi.nlm.nih.gov/pubmed/36832631 http://dx.doi.org/10.3390/e25020264 |
work_keys_str_mv | AT poulsenvictormøller inferringculturallandscapeswiththeinverseisingmodel AT dedeosimon inferringculturallandscapeswiththeinverseisingmodel |