The Silent Minority

Team members: Ray Pelupessy; Luuk van der Waals; Jeffrey Kragten

Table of Contents

• Introduction
• Research Question
• Results
• Running the code

Introduction

This repository contains code for the course Project Computational Science at the University of Amsterdam (2022-2023). This project focused on the persistence of sign languages under various circumstances. The basis of this model and its input variables is taken from a paper using ABM to model exactly this, though they do not include the different levels of fluency (Mudd et al. 2020).

Mudd, K., de Vos, C., & de Boer, B. (2020). An agent-based model of sign language persistence informed by real-world data. Language Dynamics and Change, 10(2), 158–187. https://doi.org/10.1163/22105832-bja10010

Research Question

The research question answered here is “What value should the assortative marriage parameter take to maximize the percentage of non-fluent signers after 50 generations?” Our hypothesis is as follows: A lower assortative marriage value results in a higher percentage of non-fluent signers

Results

Running the code

Necessary packages to run the code:

• Mesa
• Pandas
• Numpy
• Matplotlib

  Executing main.py

  To run the model,you can simply run main.py.

  $ python main.py

  If you want to change the parameters, give the name of the parameters and the values to set the parameters to. The parameters and their standard values are:

• n: 728 The number of agents per generation.
• m: 0.58 The percentage of agent preferring assortative marriage.
• d: 0.22 The percentage of deaf agents in the first generation.
• c: 0.172 Percentage of agents not deaf but carrying a deaf gene in the first generation.

Example:

$ python main.py m 0.05 0.1 0.2 0.4 0.58

This command runs the model once for each value of m with 728 agents per generation and the other standard values for the other two parameters. The results will be saved to:

/results/results_m_0.05.csv
/results/results_m_0.1.csv
/results/results_m_0.2.csv
/results/results_m_0.4.csv
/results/results_m_0.58.csv

Use graph.py to create graphs from the data in the results folder.

$ python graph.py [category] [loadfile] [*values]
$ python graph.py [category] [loadfile] [savefile] [*values]

• category: The kind of data you want to represent. The categories are n, m, d, c, agent_count, percentage_signers, percentage_fluent_signers, percentage_non_fluent_signers, percentage_deaf and percentage_carry. Standard: "percentage_non_fluent_signers"
• loadfile: The file in the results directory to get the data from to show in the graph from. If you want data from different files with different values for a certain parameter you can use "*" as a place holder for the different values and give the values as the values parameter. Standard: "results.csv"
• savefile: The file the graph is saved to. If not given the graph will be shown instead of be saved.
• values: The values that go in the place of the "*" in the filename.

Example:

$ python graph.py percentage_non_fluent_signers results_m_* plot 0.05 0.1 0.2 0.4 0.58

This command will make a plot of the percentage of people that can speak sign language non-fluently from the data in the following files:

/results/results_m_0.05.csv
/results/results_m_0.1.csv
/results/results_m_0.2.csv
/results/results_m_0.4.csv
/results/results_m_0.58.csv

and saves the graph in the file:

/graphs/plot.png