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Bridging theory and data: A computational workflow for cultural evolution.

Dominik Deffner1,2,3, Natalia Fedorova3, Jeffrey Andrews3

  • 1Center for Adaptive Rationality, Max Planck Institute for Human Development, 14195 Berlin, Germany.

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Summary
This summary is machine-generated.

This study introduces a computational workflow to link cultural evolution theory with empirical data. It provides a transparent, repeatable method for analyzing cultural change using generative models and case studies.

Keywords:
anthropologycausal inferencecomputational modelingcultural evolutionworkflows

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Area of Science:

  • Evolutionary studies
  • Social sciences
  • Computational modeling

Background:

  • Cultural evolution uses evolutionary concepts to study cultural change over time.
  • Current research faces challenges connecting theoretical models with empirical evidence due to vagueness and abstraction.
  • A lack of logical, transparent workflows hinders data collection, analysis, and statistical inference.

Purpose of the Study:

  • To bridge the gap between cultural evolutionary theory and empirical data.
  • To present a quality-assurance computational workflow for analyzing cultural change.
  • To demonstrate the workflow's application using a case study on conformity, migration, and cultural diversity.

Main Methods:

  • Development of a computational workflow starting from generative models.
  • Validation of the workflow using synthetic data.
  • Application of directed acyclic graphs, agent-based simulations, probabilistic transmission models, and approximate Bayesian computation.

Main Results:

  • The workflow logically connects statistical estimates to theory and real-world explanatory goals.
  • Coded and repeatable examples demonstrate the workflow's utility for various data structures.
  • Discussion of generative modeling approaches, their assumptions, and applications.

Conclusions:

  • The proposed workflow enhances the logical and transparent analysis of cultural evolution.
  • Emphasizes the importance of ethnography and basic population data in research.
  • Calls for greater emphasis on theory-driven workflows in scientific reform for cultural evolution studies.