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Cinderella’s Family Tree. A Phylomemetic Case Study of ATU 510/511

Sakamoto Martini, Gessica; Kendal, Jeremy; Tehrani, Jamshid Johari

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Gessica Sakamoto Martini


This case study contributes to recent attempts to apply “phylomemetic” methods derived from computational biology to oral traditions, where the aim is to trace the mutation and diversification of folk narratives as they get passed on from generation to generation and spread from society to society. Our study focuses on one of the most famous and widespread tales in the folktale record: Cinderella. Thousands of Cinderella-like stories have been documented from around the world, which folklorists have attempted to classify into different “types” representing distinct, though related, international traditions. The most comprehensive of Cinderella typologies was developed by Anna Birgitta Rooth (1951), who divided the tales into five principal types: A, B, AB, BI and C, and suggested several hypotheses pertaining to their origins and relationships to one another. Here, we test Rooth’s theories on a sample of 266 versions of Cinderella using Bayesian phylogenetic inference, phylogenetic networks (NeighborNet) and a model-based clustering method that was originally designed to elicit population structure from multi-locus genotype data (implemented in the program STRUCTURE). Our results find varying levels of support for the types identified by Rooth, and suggest that mixing among traditions was widespread, especially in Type AB tales. Despite these complexities, it was still possible to delineate and quantify the influence of distinct ancestral sources on the variation observed in contemporary versions of Cinderella. Our study highlights the value and versatility of phylomemetic methods in uncovering the historical relationships among types and sub-types of international folktale, as well as the evolutionary processes that have shaped them.


Sakamoto Martini, G., Kendal, J., & Tehrani, J. J. (2023). Cinderella’s Family Tree. A Phylomemetic Case Study of ATU 510/511. Fabula: Journal of Folktale Studies, 64(1-2), 7-30.

Journal Article Type Article
Acceptance Date Jan 19, 2023
Online Publication Date Jul 18, 2023
Publication Date 2023
Deposit Date Jul 18, 2023
Publicly Available Date Sep 13, 2023
Journal Fabula
Print ISSN 0014-6242
Electronic ISSN 1613-0464
Publisher De Gruyter
Peer Reviewed Peer Reviewed
Volume 64
Issue 1-2
Pages 7-30
Public URL
Related Public URLs


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