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Disruption and reintegration — self-transformation in shamanistic healing

This dissertation investigates the efficacy of shamanistic healing by exploring the self-transformation process as mediated through ritual practices and symbolic narratives. It has long been observed that self-transformation is a common occurrence in shamanistic healing, but the mechanisms contributing to this transformation are not well understood. By integrating findings from contemporary scientific research on self and adapting earlier frameworks to reconsider both theoretical formulations of and empirical data on self-transformation, this dissertation constructs a computational model capable of identifying these mechanisms, which are articulated and tested using simulation.
Studying shamanistic healing within a broader evolutionary, informational, and physical context and by means of computer modeling, the gap between the contemporary science of self and the understanding of self in religious studies has been partially bridged. As simulation results show, self-transformation consists of two stages, disruption and reintegration. High-arousal shamanistic healing rituals exhaust cognitive resources and weaken the self-organizing integration tendency of the self-system, leaving self vulnerable to external influence and therefore providing a window of opportunity for symbolic narratives to exert their guiding influence on the reintegration process. As such, the self-transformation achieves optimal results when ritual practices and symbolic narratives are both involved in the healing process. By employing computational modeling, this dissertation demonstrates the potential and relevance of simulation for exploring the mechanisms that underlie shamanistic healing and constitutes a case study for how computational approaches may apply to topics in religious studies. / 2021-02-15T00:00:00Z

Identiferoai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/34784
Date16 February 2019
CreatorsYou, Wensi
ContributorsWildman, Wesley
Source SetsBoston University
Languageen_US
Detected LanguageEnglish
TypeThesis/Dissertation

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