This repository contains supplementary materials for the paper "When is Similiarity-Biased Social Learning Adaptively Advantageous?" The paper can be found here. The paper describes an agent-based model used to explore when selective processes would favor the evolution of traits that cause people to learn primary from their own ethnic-group. The main file in this repository is "ethnicity bias learning - github version.nlogo". This is the code for the agent-based model that serves as the core of the paper. It is written in Netlogo, a high-level language specialized for fast development of agent-based models. To read the file, download the repository and then upload the nlogo file to this web-based simulation environment. This will allow you to explore the model quickly, without installing the full version of netlogo.
The repository also contains a reproducible python script for analzing data from the model and generating all plots found in the paper. The script is called "Reproducible_data_analysis_similiarity_bias.ipynb". You can run the script directly from your browser. Open the file in github and click "run on google colab." Colab is a web-based environment popular for data science projects. All computations are done in the cloud so your computer does not need any tools to run Python.
This brings us to the last part of the repository - the data. The netlogo model produces simulated data as a way of exploring how its behavior changes across parameter values. These data are stored in large csv files. The Colab script will automatically extract data from the repository so you shouldn't need to interact with the csv files directly.