Abstract
Computational folkloristics, which is rooted in the movement to make folklore studies more scientific, has transformed the way researchers in humanities detect patterns of cultural transmission in large folklore collections. This interdisciplinary study contributes to the literature through its application of Bayesian statistics in analyzing Vietnamese folklore. By breaking down 307 stories in popular Vietnamese folktales and major story collections and categorizing their core messages under the values or anti-values of Confucianism, Buddhism, and Taoism, the study shows how the Bayesian method helps discover an underlying behavioural phenomenon called “cultural additivity.” The term, which is inspired by the principle of additivity in probability, adds to the voluminous works on syncretism, creolization and hybridity in its technical dimension. Here, to evaluate how the values and norms of the aforementioned three religions (“tam giáo” 三教) co-exist, interact, and influence Vietnamese society, the study proposes three models of additivity for religious faiths: (a) no additivity, (b) simple additivity, and (c) complex additivity. The empirical results confirm the existence of “cultural additivity” : not only is there an isolation of Buddhism in the folktales, there is also a higher possibility of interaction or addition of Confucian and Taoist values even when these two religions hold different value systems (β{VT.VC} = 0.86). The arbitrary blend of the three religions is an example of the observed phenomenon of Vietnamese people selecting and adding ideas, beliefs, or artefacts—which may sometimes appear contradictory to principles of their existing beliefs—to their culture. The behavioural pattern is omnipresent in the sense that it can also be seen in Vietnamese arts, architecture, or adoption of new ideas and religions, among others. The “cultural additivity” concept, backed by robust statistical analysis, is an attempt to fill in the cultural core pointed out by syncretism and account for the rising complexity of modern societies.
Highlights
The move toward a more scientific approach of folklore studies could be dated back to the nineteenth century, when scholars were first keen on having the traditional expressive culture reflect a Darwinian theory of biological evolution (Bronner, 2005; Magliocco, 2010)
As one of the main criteria for judging a preferred model for its goodness of fit is the “weight” in the Bayesian statistical method (McElreath, 2016), the distribution of weight is indicative of the credibility of the model, comparing the weight across models can help us eliminate results that are not supported by evidences
Analyzing the datasets using a modern statistical technique such as Bayesian statistics could yield valuable behavioural and cultural insights and help advance social sciences and humanities into a more interdisciplinary (Pedersen, 2016) and reproducible direction (D’Oca and Hrynaszkiewicz, 2015; Munafò et al, 2017). This interdisciplinary study is among the first attempts to quantitatively mining the insights on the behavioural patterns in hundreds of Vietnamese folktales using the Bayesian method
Summary
The move toward a more scientific approach of folklore studies could be dated back to the nineteenth century, when scholars were first keen on having the traditional expressive culture reflect a Darwinian theory of biological evolution (Bronner, 2005; Magliocco, 2010). The enlightened scientific forces suggest a disintegration of racial boundaries and result in an ambivalence toward the value of the “old” beliefs and customs (Bronner, 2005) As this movement is aided with the rapid development of information technology, a subfield of folklore studies called computational folkloristics has emerged and expanded throughout the world. This sub-field has five main targets: (i) digitizing resources into machine readable forms, (ii) developing data structures to store these resources, (iii) classifying folklores, (iv) developing domains sensitive methods, and (v) applying algorithms (Abello et al, 2012; Tangherlini, 2013; Nguyen et al, 2013; Dogra, 2018; Da Silva and Tehrani, 2016). One of the most ambitious endeavors is the “historical-geographic” method, pioneered by Finnish folklorists Julius and Kaarle Krohn (Thompson, 1977), in which the exponents seek to reconstruct the history of the evolution of one original folktale into multiple variants by sorting all available variants by regions and timelines (Tehrani and d’Huy, 2017)
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