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This repository contains data and code used and generated by the fair chance hiring group during QSIDE's 2024 Datathon4Justice.

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Datathon4Justice 2024: Fair Chance Project

This repository contains data and code used and generated by the fair chance hiring group during QSIDE's 2024 Datathon4Justice. This project is comprised of three teams:

  • Team 1 - Fair Chance Employer Data

    Team 1 is focused on creating a new fair chance employer dataset. This work is mostly non-technical and involves finding the locations of Obama White House Fair Chance Pledge signatories (link to pledge). The team will create a new employment index measure for each state by:

    • Searching the web to gather data on Fair Chance Pledge signatories.
    • Using Google Sheets to count the number of pledge signatories by state.

    No prior experience is required for this team, making it a great opportunity for those interested in data collection and research without a technical background.

  • Team 2 - Indeed Industry Data

    Team 2 will collect fair chance job posting rates by industry. This is guided technical work that involves scraping data on job postings by industry (e.g., manufacturing and hospitality). The team will create an index measure for each state by:

    • Scraping the web to gather job posting data by industry.
    • Using the RSelenium package in R for web scraping.
    • Gathering new data on job posting rates by industry.

    Participants are kindly asked to download R and RStudio by Saturday morning. Support is provided in R, but participants who wish to use Python are welcome to do so on their own.

  • Team 3 - Open-ended Research

    Team 3 will address open-ended questions, providing an opportunity for creative exploration. This is unstructured technical work where participants will have access to our data and can experiment to come up with innovative solutions to advance the research. Potential areas of focus include:

    • Creating data visualizations.
    • Investigating auxiliary data sources (e.g., LinkedIn, HonestJobs).
    • Automating existing R code to scrape Indeed on a weekly basis.
    • Using the data in other creative and ethical ways.

    Participants should have proficiency in R and/or Python, and a desire to craft their own datathon goals. This team is ideal for those who enjoy working independently or in a small team, and are eager to explore new possibilities.

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This repository contains data and code used and generated by the fair chance hiring group during QSIDE's 2024 Datathon4Justice.

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