Work Description

Title: Code and Results for "The Emergence of Groups and Inequality Through Co-Adaptation" Open Access Deposited

Attribute Value
  • The included data file was produced by running the included game code.
  • The data file is json formatted and all fields are named descriptively. The code is written in Python 2.7 and is heavily commented.
Contact information
Resource type
Last modified
  • 11/04/2019
  • 06/15/2016
To Cite this Work:
Atwell, J. (2016). Code and Results for "The Emergence of Groups and Inequality Through Co-Adaptation" [Data set], University of Michigan - Deep Blue Data.


This work is not a member of any user collections.

Files (Count: 4; Size: 9.91 MB)

This repository contains the data used for the analyses in the paper "The Emergence of Group and Inequality Through Co-adaptation" by Jon Atwell and Robert Savit. The paper can be found here:

The core model used in the paper is implemented in the file named This is a Python (2.7) module that describes the core logic of the model. is a Python script used to manage the running of the
model. One can study the model using this file alone. Simply place this file in the same directory as and execute using your preferred method.

The file titled basic_run_data.json contains data generated by conducting a sweep of model parameters. Each entry corresponds to a single run and contains information about the initial conditions for the model and the relevant outcomes.

Download All Files (To download individual files, select them in the “Files” panel above)

Best for data sets < 3 GB. Downloads all files plus metadata into a zip file.

Best for data sets > 3 GB. Globus is the platform Deep Blue Data uses to make large data sets available.   More about Globus

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.