DOI: 10.5281/zenodo.17588730
title: Nou Pa Bèt: Civic Substitution and Expressive Freedoms in Post-State Governance

description: Dataset Description

This dataset supports the research article "Nou Pa Bèt: Civic Substitution and Expressive Freedoms in Post-State Governance" published in Third World Quarterly. The study examines how civic participation functions as institutional substitution when state capacity collapses, using Haiti and 20 other fragile states as case studies.

Research Question: Can civic engagement compensate for governance failures in post-state contexts?

Key Finding: Civil society participation significantly predicts better governance outcomes even when state institutions are weak, with strongest effects in contexts of high expressive freedoms.

Files Included





CivicEngagement_SelectedCountries_Last10Years.xlsx (25 KB)



V-Dem civic engagement indicators for 21 fragile states (2015-2024)

Variables: participatory governance, civil society participation, freedom of expression/assembly, anti-system movements, direct democracy





wgidataset.xlsx (2.6 MB)



World Bank Worldwide Governance Indicators (WGI)

Dependent variables: Control of Corruption, Government Effectiveness





Nou.ipynb (10 KB)



Complete Python analysis code

Replicates all regressions and tables in the published article




Quick Start: Google Colab

Step 1: Open in Colab

# Click this link to open a new Colab notebook:
# https://colab.research.google.com/


Step 2: Upload Data Files

from google.colab import files
uploaded = files.upload()
# Select and upload both .xlsx files from this Zenodo record


Step 3: Install Required Packages

!pip install openpyxl statsmodels scipy


Step 4: Run the Analysis

import pandas as pd
import statsmodels.api as sm

# Load data
civic = pd.read_excel("CivicEngagement_SelectedCountries_Last10Years.xlsx")
wgi = pd.read_excel("wgidataset.xlsx")

# Merge datasets
# [See Nou.ipynb for complete code]

# Run regression (Table 2 in article)
X = df[['v2x_partip', 'v2x_cspart', 'v2cademmob', 
        'v2cafres', 'v2csantimv', 'v2xdd_dd']]
X = sm.add_constant(X)
y = df['Control_of_Corruption']
model = sm.OLS(y, X).fit(cov_type='HC3')
print(model.summary())


OR: Download Nou.ipynb and run all cells to replicate complete analysis.

Variables

Dependent Variables (World Bank WGI)



Control_of_Corruption - Extent to which public power is NOT exercised for private gain

Government_Effectiveness - Quality of public services and policy implementation


Independent Variables (V-Dem Project)



v2x_partip - Participatory Component Index (0-1)

v2x_cspart - Civil Society Participation Index (0-1)

v2cademmob - Freedom of Peaceful Assembly (0-4)

v2cafres - Freedom of Expression (0-4)

v2csantimv - Anti-System Movements (0-4, lower = more movements)

v2xdd_dd - Direct Popular Vote Index (0-1)


Sample Countries (N=21 Fragile States)

Haiti, Sierra Leone, Liberia, DRC, Central African Republic, Guinea-Bissau, Chad, Niger, Burundi, Yemen, South Sudan, Mozambique, Sudan, Eritrea, Somalia, Mali, Afghanistan, Papua New Guinea, Togo, Cambodia, Timor-Leste

Time Period: 2015-2024 (last 10 years of available data)

Key Results (Replicate Table 2)

Control of Corruption Model:



R² = 0.700

Civil Society Participation (v2x_cspart): Non-significant substitution effect

Freedom of Expression (v2cafres): Positive, significant (p = 0.028)

Anti-System Movements (v2csantimv): Negative, significant (p < 0.001)


Government Effectiveness Model:



R² = 0.672

Similar patterns with expressive freedoms as key enablers


Interpretation: Civic substitution works best when expressive freedoms allow civil society to organize and communicate freely.

Citation

Dataset:



Brown, S., Fils-Aime, J., & La Tortue, P. (2025). Nou Pa Bèt: Civic Substitution and Expressive Freedoms in Post-State Governance [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.17588730


Article:



Brown, S. M. (2025). Nou Pa Bèt: Civic Substitution and Expressive Freedoms in Post-State Governance. Third World Quarterly, [forthcoming]. DOI: [will be added upon publication]


Data Sources



V-Dem Data: Varieties of Democracy Project, Version 14 (2024). https://www.v-dem.net/

WGI Data: World Bank Worldwide Governance Indicators (2024). https://www.worldbank.org/governance/wgi/


Replication Notes



Robust Standard Errors: All regressions use HC3 heteroscedasticity-consistent standard errors

Missing Data: Observations with missing values on any variable are dropped (listwise deletion)

No Standardization: Variables are used in original scales (raw, not z-scored)

Sample Size: N=288 country-year observations after merging and cleaning


Technical Requirements



Python 3.7+

Required packages: pandas, numpy, statsmodels, openpyxl, scipy

Recommended environment: Google Colab (free, no installation required)


License

Creative Commons Attribution 4.0 International (CC BY 4.0)

You are free to:



Share — copy and redistribute the material

Adapt — remix, transform, and build upon the material


Under the following terms:



Attribution — You must give appropriate credit and link to the license


Contact

For questions about data, methodology, or replication:



Scott M. Brown - Professor of Finance, University of Puerto Rico–Río Piedras

Email: scott.brown@upr.edu


For questions about Haitian context or fieldwork:



Jempsy Fils-Aime - Data collection and local context

Paul La Tortue - Editorial and translation support


Acknowledgments

This research was conducted with support from the University of Puerto Rico–Río Piedras and Universidad de Granada. We thank the V-Dem Institute and World Bank for making their data publicly available.

Last Updated: November 12, 2025Version: v4 (corrected regression specifications)