Fair Decision-Making for Food Inspections

This repository contains the code used to conduct the analysis in the paper "Fair Decision-Making for Food Inspections" by Singh et al. (EAAMO, 2022). The code uses both R and Python for the analysis.

Original City of Chicago Code

The code used by City of Chicago conducted Schenk Jr. et al. is located in the Original-City-Repo directory, which is a snapshot of the live repo here. Please see the README.md inside Original-City-Repo that explains the structure, requirements, and how to run the code.

Creating Schedules Using Model Scores

We include ANALYSIS.md that goes over the R files that are used to create new models (Section 4) and that change how the model scores are used (Section 5).

Data & Analysis

The output from the R files is compiled using Google Sheets and the exported CSV are provided inside the analyses directory. Use the Python notebook plot_better.ipynb to generate the plots used in the paper.

Python Requirements

Python >= 3.10
jupyter
matplotlib
numpy
pandas
seaborn
scipy

Citation

Use the following BibTex:

@inproceedings{singhFood2022,
    author = {Singh, Shubham and Shah, Bhuvni and Kanich, Chris and Kash, Ian A.},
    title = {Fair Decision-Making for Food Inspections},
    year = {2022},
    isbn = {9781450394772},
    publisher = {Association for Computing Machinery},
    address = {New York, NY, USA},
    url = {https://doi.org/10.1145/3551624.3555289},
    doi = {10.1145/3551624.3555289},
    booktitle = {Proceedings of the 2nd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization},
    articleno = {5},
    numpages = {11},
    keywords = {scheduling, food inspections, fairness},
    location = {Arlington, VA, USA},
    series = {EAAMO '22}
}