Cultural evolution of a belief controlling human mate choice: Dynamic modeling of the hinoeuma superstition in Japan

Cinthia Marie Tanaka, Yoh Iwasa

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4 Citations (Scopus)


We develop a simple cultural dynamics model to dicuss the spread of the hinoeuma superstition in Japan. A large drop in the number of newborn babies observed in 1966 was attributed mainly to parents' avoiding having a child born in a hinoeuma year. Presumably, Japanese parents were afraid that a daughter born in 1966 (a hinoeuma year) might later have difficulty finding a mate. We construct mathematical models to examine whether the hinoeuma superstition would likely become extinct or be stably maintained in the population. We classify members of a population according to whether they believed the hinoeuma superstition (believer or nonbeliever), their gender (male or female), and their year of birth (born in a hinoeuma year or not). We compare several cases that differ according to (1) whether the belief in the superstition was transmitted to children by matrilineal, patrilineal, or Mendelian inheritance; (2) which parent controlled the timing of pregnancy and childbirth (maternal or paternal birth control); and (3) the probability of birth control failure. Our results show that the hinoeuma superstition is likely to spread if the mother has a strong influence on birth control and on the belief of their children. In contrast, if birth control is paternal and the belief is passed down from father to child, the hinoeuma superstition is likely to become extinct. In between these extremes, whether the superstition becomes extinct or fixed in the population depends on the initial frequency of believers in the population.

Original languageEnglish
Pages (from-to)20-28
Number of pages9
JournalJournal of Theoretical Biology
Publication statusPublished - Sept 21 2012

All Science Journal Classification (ASJC) codes

  • General Immunology and Microbiology
  • Applied Mathematics
  • General Biochemistry,Genetics and Molecular Biology
  • General Agricultural and Biological Sciences
  • Statistics and Probability
  • Modelling and Simulation


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