Legality Without Justice: Symbolic Governance, Institutional Denial, and the Ethical Foundations of Law

Description:This dataset accompanies the empirical analysis in Legality Without Justice, a study examining the relationship between public trust in institutions and perceived governance legitimacy using data from the World Values Survey Wave 7 (2017–2022). It includes: WVS_Cross-National_Wave_7_csv_v6_0.csv — World Values Survey Wave 7 core data. GDP.csv — World Bank GDP per capita (current US$) for 2022 by country. denial.ipynb — Fully documented Jupyter notebook with code for data merging, exploratory statistics, and ordinal logistic regression using OrderedModel. Includes GDP as a control for institutional trust and perceived governance. All data processing and analysis were conducted in Python using FAIR reproducibility principles and can be replicated or extended on Google Colab. DOI: 10.5281/zenodo.16361108License: Creative Commons Attribution 4.0 International (CC BY 4.0)Authors: Anon AnnotatorPublication date: 2025-07-23Language: EnglishVersion: 1.0.0Publisher: ZenodoProgramming language: Python 🔽 How to Download and Run on Google Colab Step 1: Open Google Colab Go to https://colab.research.google.com Step 2: Upload Files Click File > Upload notebook, and upload the denial.ipynb file.Also upload the CSVs (WVS_Cross-National_Wave_7_csv_v6_0.csv and GDP.csv) using the file browser on the left sidebar. Step 3: Adjust File Paths (if needed) In denial.ipynb, ensure file paths match: python CopiarEditar wvs = pd.read_csv('/content/WVS_Cross-National_Wave_7_csv_v6_0.csv') gdp = pd.read_csv('/content/GDP.csv') Step 4: Run the Code Execute the notebook cells from top to bottom. You may need to install required libraries: python CopiarEditar !pip install statsmodels pandas numpy The notebook performs: Data cleaning Merging WVS and GDP datasets Summary statistics Ordered logistic regression to test if confidence in courts/police (Q57, Q58) predicts belief that the country is governed in the interest of the people (Q183), controlling for GDP.