stigmaRdata: Data Processing Documentation

Author
Affiliation

Seungju Kim

University of Illinois, Urbana-Champaign

Overview

This book documents the data sources, cleaning procedures, and methodological decisions underlying the stigmaR R package.

stigmaR measures structural stigma — the societal-level conditions that disadvantage stigmatized groups — for use in health disparities research. The data pipeline documented here transforms raw public data into the structured indicators that stigmaR exposes to researchers.

Who This Is For

This documentation is intended for:

  • Researchers who want to understand how stigmaR indicators are constructed before using them in analysis
  • Reviewers and collaborators who need methodological transparency
  • Future contributors (including future me) who need to maintain or extend the pipeline

Data Sources

Source Coverage Indicators
Movement Advancement Project (MAP) 2010–present Policy environment scores
Project Implicit (IAT) 2006–present Implicit bias by state

How to Read This Book

Each chapter covers one data source and follows a consistent structure:

  1. Source description — what it is and where it comes from
  2. Access and download — how raw data is obtained
  3. Cleaning decisions — variable selection, exclusions, recoding
  4. Limitations — known issues and caveats
  5. Output — what the final dataset looks like

Versioning and Changelog

Data pipelines and coding decisions evolve over time. See the Changelog for a record of substantive changes across versions of stigmaRdata.

Current version: 0.1.0
Last updated: r Sys.Date()

Citation

If you use stigmaR in published research, please cite:

Kim, S. (2028). stigmaR: Structural stigma measures for health disparities research. R package version x.x.x.

Contact

Questions about the data pipeline can be filed as a GitHub Issue in the main stigmaR repository.