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Beliefs as Self-Sustaining Networks: Drawing Parallels Between Networks of Ecosystems and Adults’ Predictions
In this paper, we argue that beliefs share common properties with the self-sustaining networks of complex systems. Matching experiences are said to couple with each other into a mutually reinforcing network. The goal of the current paper is to spell out and develop these ideas, using our understandi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4641980/ https://www.ncbi.nlm.nih.gov/pubmed/26617552 http://dx.doi.org/10.3389/fpsyg.2015.01723 |
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author | Castillo, Ramon D. Kloos, Heidi Richardson, Michael J. Waltzer, Talia |
author_facet | Castillo, Ramon D. Kloos, Heidi Richardson, Michael J. Waltzer, Talia |
author_sort | Castillo, Ramon D. |
collection | PubMed |
description | In this paper, we argue that beliefs share common properties with the self-sustaining networks of complex systems. Matching experiences are said to couple with each other into a mutually reinforcing network. The goal of the current paper is to spell out and develop these ideas, using our understanding of ecosystems as a guide. In Part 1 of the paper, we provide theoretical considerations relevant to this new conceptualization of beliefs, including the theoretical overlap between energy and meaning. In Part 2, we discuss the implications of this new conceptualization on our understanding of belief emergence and belief change. Finally, in Part 3, we provide an analytical mapping between beliefs and the self-sustaining networks of ecosystems, namely by applying to behavioral data a measure developed for ecosystem networks. Specifically, average accuracies were subjected to analyses of uncertainty (H) and average mutual information. The ratio between these two values yields degree of order, a measure of how organized the self-sustained network is. Degree of order was tracked over time and compared to the amount of explained variance returned by a categorical non-linear principal components analysis. Finding high correspondence between the two measures of order, together with the theoretical groundwork discussed in Parts 1 and 2, lends preliminary validity to our theory that beliefs have important similarities to the structural characteristics of self-sustaining networks. |
format | Online Article Text |
id | pubmed-4641980 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-46419802015-11-27 Beliefs as Self-Sustaining Networks: Drawing Parallels Between Networks of Ecosystems and Adults’ Predictions Castillo, Ramon D. Kloos, Heidi Richardson, Michael J. Waltzer, Talia Front Psychol Psychology In this paper, we argue that beliefs share common properties with the self-sustaining networks of complex systems. Matching experiences are said to couple with each other into a mutually reinforcing network. The goal of the current paper is to spell out and develop these ideas, using our understanding of ecosystems as a guide. In Part 1 of the paper, we provide theoretical considerations relevant to this new conceptualization of beliefs, including the theoretical overlap between energy and meaning. In Part 2, we discuss the implications of this new conceptualization on our understanding of belief emergence and belief change. Finally, in Part 3, we provide an analytical mapping between beliefs and the self-sustaining networks of ecosystems, namely by applying to behavioral data a measure developed for ecosystem networks. Specifically, average accuracies were subjected to analyses of uncertainty (H) and average mutual information. The ratio between these two values yields degree of order, a measure of how organized the self-sustained network is. Degree of order was tracked over time and compared to the amount of explained variance returned by a categorical non-linear principal components analysis. Finding high correspondence between the two measures of order, together with the theoretical groundwork discussed in Parts 1 and 2, lends preliminary validity to our theory that beliefs have important similarities to the structural characteristics of self-sustaining networks. Frontiers Media S.A. 2015-11-12 /pmc/articles/PMC4641980/ /pubmed/26617552 http://dx.doi.org/10.3389/fpsyg.2015.01723 Text en Copyright © 2015 Castillo, Kloos, Richardson and Waltzer. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Castillo, Ramon D. Kloos, Heidi Richardson, Michael J. Waltzer, Talia Beliefs as Self-Sustaining Networks: Drawing Parallels Between Networks of Ecosystems and Adults’ Predictions |
title | Beliefs as Self-Sustaining Networks: Drawing Parallels Between Networks of Ecosystems and Adults’ Predictions |
title_full | Beliefs as Self-Sustaining Networks: Drawing Parallels Between Networks of Ecosystems and Adults’ Predictions |
title_fullStr | Beliefs as Self-Sustaining Networks: Drawing Parallels Between Networks of Ecosystems and Adults’ Predictions |
title_full_unstemmed | Beliefs as Self-Sustaining Networks: Drawing Parallels Between Networks of Ecosystems and Adults’ Predictions |
title_short | Beliefs as Self-Sustaining Networks: Drawing Parallels Between Networks of Ecosystems and Adults’ Predictions |
title_sort | beliefs as self-sustaining networks: drawing parallels between networks of ecosystems and adults’ predictions |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4641980/ https://www.ncbi.nlm.nih.gov/pubmed/26617552 http://dx.doi.org/10.3389/fpsyg.2015.01723 |
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