Suparna Chaudhry • Lewis and Clark College
Audrey Comstock • Arizona State University
Andrew Heiss • Andrew Young School of Policy Studies • Georgia State University

Suparna Chaudhry, Audrey L. Comstock, and Andrew Heiss, “Pandemic Pass? Treaty Derogations and Human Rights Practices during COVID-19,” International Interactions 50, no. 6 (2024): 1064–86, https://doi.org/10.1080/03050629.2024.2413965.

This research note asks whether states issuing pandemic-era human rights treaty derogations implemented emergency provisions as intended or used them to abuse human rights during a time of crisis. In an effort to combat the COVID-19 pandemic, many countries declared states of emergency and derogated (temporarily suspended) from their international human rights treaty obligations. Using data from the Varieties of Democracy PanDem dataset and the Oxford COVID-19 Government Response Tracker, we find that states that derogated from their international human rights obligations imposed emergency measures that were temporary and did not violate non-derogable rights. On the other hand, states that did not derogate were more likely impose discriminatory measures, enact emergency measures without time limits and violate non-derogable rights. Our results support the role that flexibility mechanisms such as derogations play in international law and show that states are being sincere about their intentions and not, generally, using these mechanisms to cover abusive behavior.

You can either download the compendium as a ZIP file or use GitHub to clone or fork the compendium repository (see the green “Clone or download” button at the top of the GitHub page).

We use the {renv} package to create a stable version-specific library of packages, and we use the {targets} package to manage all file dependencies and run the analysis. (See this for a short helpful walkthrough of {targets}.).

To replicate the findings and re-run the analysis, you can use a Docker container at mountainous-mackerel-docker, which will create a complete computing envirionment for running everything. Full details and instructions are available there.

Alternatively, everything can be run on your local computer too. Do the following:

1. Download and install these fonts (if you’re using Windows, make sure you right click on the font files and choose “Install for all users” when installing these fonts):

   • Noto Sans
   • Linux Libertine O (also here)
   • Libertinus Math

2. Install R (and preferably RStudio).

   • If you’re using macOS, install XQuartz too, so that you have access to the Cairo graphics library. Also install Homebrew and run brew install ghostscript.
   • If you’re using Windows, install RTools too and add it to your PATH so that you can install packages from source if needed

3. Open mountainous-mackerel.Rproj to open an RStudio Project.

4. In the terminal, run quarto install tinytex to ensure that you have a working LaTeX installation.

5. If it’s not installed already, R should try to install the {renv} package when you open the RStudio Project for the first time. If you don’t see a message about package installation, install it yourself by running install.packages("renv") in the R console.

6. Run this to install {cmdstanr}. This is supposed to happen automatically as part of renv::restore() below, since {cmdstanr} is in the lockfile, but due to an issue with {renv} (fixed in the development version as of 2024-08-06), it doesn’t install correctly because it is hosted at https://stan-dev.r-universe.dev instead of CRAN. So for now, until the next stable release of {renv}, it’s easiest to install {cmdstanr} in a separate step.

   install.packages("cmdstanr", repos = c("https://stan-dev.r-universe.dev", "https://packagemanager.posit.co/cran/latest"))

7. Run renv::restore() in the R console to install all the required packages for this project.

8. Run targets::tar_make() in the R console to automatically download all data files, process the data, run the analysis, and compile the paper and appendix.

Running targets::tar_make() will create several helpful outputs:

1. All project data in data/
2. An analysis notebook website in _site/
3. PDF, HTML, and Word versions of the manuscript in manuscript/output/

Because project titles change all the time with revisions, rewriting, and peer review, we used {codename} to generate an Ubuntu-style internal-to-us project name that won’t change.

library(codename)
codename_message()
#> code name generated by {codename} v.0.4.0

codename(seed = "covid and ngos", type = "ubuntu")
#> [1] "mountainous mackerel"

Text and figures: All prose and images are licensed under Creative Commons (CC-BY-4.0).

Code: All code is licensed under the MIT License.

We welcome contributions from everyone. Before you get started, please see our contributor guidelines. Please note that this project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.