Protestant Epistemology as Juridical Contestation: How Evangelical Institution-Building Contests Colonial Legal Frameworks

Here's an updated README description that incorporates both analyses: Analyzing Religious and Demographic Change in Latin America with Google Colab This repository contains Python scripts for analyzing interconnected trends in Catholic affiliation decline and household size changes across Latin America, with particular focus on Puerto Rico. The analyses utilize descriptive statistics, growth rate analysis, K-means clustering, and regression modeling to explore institutional factors driving religious and demographic transformation during the colonial period (1910-2014). Repository Contents 1. Catholic Affiliation Analysis (Protestant.ipynb) Analyzes Catholic decline across 19 Latin American countries (1910-2014), demonstrating that U.S. colonial influence is the strongest predictor of religious transformation. Key Findings: Countries with high U.S. institutional presence experienced Catholic decline averaging 37.0 percentage points (1970-2014) vs. 18.2 points in low-influence countries Statistical significance: p < 0.001, R² = 0.559, Cohen's d = -2.21 Puerto Rico declined from 87% Catholic (1970) to 56% (2014)—a 31-point drop coinciding with Protestant missionary expansion, Operation Bootstrap industrialization, and eugenic sterilization campaigns 2. Household Size Analysis (Family.ipynb) Examines Puerto Rican household size trends using IPUMS census microdata (1910-2000), revealing demographic collapse paralleling religious transformation. Key Findings: Household size declined 33% over 90 years (4.89 → 3.26 persons) Post-1970 acceleration: decline rate 2.4x faster than pre-1970 period Temporal correlation with Catholic decline and sterilization campaign (1930s-1970s) Evidence supporting "coordinated institutional assault" thesis Data Sources Catholic Affiliation Data: Catholic_Affiliation_in_Latin_America.xlsx: Country-level religious affiliation (1910, 1950, 1970, 2014) Source: Pew Research Center, national censuses, historical church records Household Size Data: Puerto_Rican_family_size_census_data.xlsx: Average household size from Puerto Rico census samples Source: IPUMS USA (Integrated Public Use Microdata Series), University of Minnesota Census years: 1910, 1920, 1930, 1970, 1980, 1990, 2000 Sample sizes: 6,649 to 55,037 households per year Running the Analysis in Google Colab Setup Instructions Open the Notebooks in Google Colab: Click on Protestant.ipynb (Catholic analysis) or Family.ipynb (household size analysis) Click "Open in Colab" or upload manually to Google Colab Upload the Data Files: Download the corresponding Excel file from this repository: Catholic_Affiliation_in_Latin_America.xlsx for Protestant.ipynb Puerto_Rican_family_size_census_data.xlsx for Family.ipynb In Google Colab, use the file explorer (left sidebar) to upload the Excel file to /content/ Modify the Filepath: Locate the code block defining the filepath: if __name__ == "__main__": filepath = '/content/Catholic Affiliation in Latin America.xlsx' # Update this df = main(filepath) Verify the filepath matches your uploaded file location (check the Files panel) Run the Notebook: Click "Connect" to start a runtime Select "Runtime" → "Run all" to execute all code blocks sequentially Monitor output as analyses run and visualizations generate Inspect Results: Protestant.ipynb outputs: Descriptive statistics for Catholic affiliation by year Period-specific decline rates K-means clustering analysis (Severe/Moderate/Stable decline groups) Regression results showing U.S. influence effects 4-panel visualization: catholic_decline_analysis.png Family.ipynb outputs: Puerto Rico household size trends (1910-2000) Period-by-period decline analysis Pre-1970 vs. post-1970 acceleration comparison 2-panel visualization: puerto_rico_household_size_analysis.png Download Visualizations: Click the Files icon (left sidebar) Locate output PNG files Right-click → "Download" Methodology: IPUMS Household Size Data Extraction Puerto Rico household size data were extracted from the Integrated Public Use Microdata Series (IPUMS USA), maintained by the University of Minnesota Population Center. We selected census samples spanning 1910-2000, including decennial censuses (1910, 1920, 1930, 1970, 1980, 1990, 2000). Variables extracted included YEAR (census year), STATEFIP (state FIPS code, filtered to 72 for Puerto Rico), NUMPREC (number of persons in household), HHWT (household weight for population estimates), and SERIAL (household identifier). To calculate average household size by year, we collapsed person-level data to household level by selecting unique YEAR-SERIAL combinations, then computed weighted averages using the formula: Average Household Size = Σ(NUMPREC × HHWT) / ΣHHWT for each census year. Data cleaning excluded records with missing critical values and limited household sizes to 1-20 persons to eliminate data errors. The final analysis covers seven census years with sample sizes ranging from 6,649 households (1970) to 55,037 households (1990), providing statistically robust estimates across 90 years of Puerto Rican demographic history. Integration: The "Coordinated Institutional Assault" Thesis These analyses provide complementary evidence for understanding U.S. colonial governance in Puerto Rico as operating through coordinated intervention across multiple domains: Religious transformation: Protestant institutional expansion displacing Catholic dominance (1899-2014) Demographic disruption: Eugenic sterilization campaign affecting 1/3 of women of childbearing age (1930s-1970s) Family structure collapse: Household size declining 33%, accelerating post-1970 Economic transformation: Operation Bootstrap industrialization and agricultural displacement The temporal overlap and institutional coordination among these initiatives suggest systematic colonial biopolitical governance rather than isolated sectoral policies. Technical Requirements Python Libraries: pandas (data manipulation) numpy (numerical computing) matplotlib, seaborn (visualization) scipy (statistical analysis) scikit-learn (clustering, regression) statsmodels (econometric modeling) openpyxl (Excel file handling) All libraries are pre-installed in Google Colab—no local installation required. Citation Data Sources: Pew Research Center (2014). Religion in Latin America: Widespread Change in a Historically Catholic Region. Steven Ruggles, Sarah Flood, et al. IPUMS USA: Version 15.0 [dataset]. Minneapolis, MN: IPUMS, 2025. https://doi.org/10.18128/D010.V15.0 For Academic Use: If using these analyses in research, please cite the underlying data sources and note that analytical code was developed with assistance from Claude (Anthropic) for data processing and statistical computation. Support For questions about: IPUMS data access: https://usa.ipums.org/ Pew Research methodology: https://www.pewresearch.org/ Google Colab usage: https://colab.research.google.com/ Python libraries: Refer to pandas, scikit-learn, statsmodels, matplotlib, seaborn documentation This toolkit enables econometric and demographic analysis without advanced coding skills or local software installation. The integrated analyses reveal how colonial governance operated through coordinated religious, economic, and biopolitical mechanisms to transform Puerto Rican society.