{"type":"script","doc_desc":{"producers":[{"name":"Reproducibility WBG","abbr":"DIME","affiliation":"World Bank - Development Impact Department","role":"Verification and preparation of metadata"}],"prod_date":"2025-01-27","version":"1"},"project_desc":{"authoring_entity":[{"name":"Jose Cuesta","email":"jcuesta@worldbank.org","affiliation":"World Bank"},{"name":"Natalia Pecorari","affiliation":"World Bank","email":"npecorari@worldbank.org"}],"title_statement":{"idno":"RR_LAC_2024_255","title":"Reproducibility package for Gender bias, citizen participation, and AI"},"production_date":"2025-01","abstract":"This paper investigates the role of gender bias in AI-driven analyses of citizen participation, using data from the 2023 Latinobar\u00f3metro Survey. We propose that gender bias\u2014whether societal, data-driven, or algorithmic\u2014significantly affects civic engagement. Using machine learning, particularly decision trees, we explore how self-reported societal bias (i.e., machismo norms) interacts with personal characteristics and circumstances to shape civic participation. Our findings show that individuals with reportedly low levels of gender bias, who express political interest, have high levels of education, and align with left-wing views, are more likely to participate. We also explore different strategies to mitigate gender bias in both the data and the algorithms, demonstrating that gender bias remains a persistent factor even after applying corrective measures. Notably, lower machismo thresholds are required for participation in more egalitarian societies, with men needing to exhibit especially low machismo levels. Ultimately, our research emphasizes the importance of integrated strategies to tackle gender bias and increase participation, offering a framework for future studies to expand on nonlinear and complex social dynamics.","geographic_units":[{"name":"Latin America and the Caribbean","code":"LAC","type":"Region"}],"keywords":[{"name":"Citizen participation"},{"name":"Gender bias"},{"name":"Machine learning"},{"name":"Latin America and the Caribbean"}],"output":[{"type":"Working Paper","title":"Gender bias, citizen participation, and AI","authors":"Jose Cuesta and Natalia Pecorari","description":"Policy Research Working Paper (PRWP) WPS11046","uri":"http:\/\/documents.worldbank.org\/curated\/en\/099909401272535729\/IDU1758c3cc41f5be14ea519e4d16a2c1334c916","doi":"https:\/\/doi.org\/10.1596\/1813-9450-11046"}],"datasets":[{"name":"Latinobarometro data (2023)","note":"Source: Latinobarometro Corporation\nFilename: Latinobarometro_2023_Eng_Stata_v1_0.dta\n\nUsers can download the data from the URL below and must select the Stata option to download the 2023 file. Once downloaded, the file must be saved in the DataIn folder, ensuring the file name is Latinobarometro_2023_Eng_Stata_v1_0.dta. Please note that World Bank computer users might encounter issues downloading the data, as the firewall may block access","uri":"https:\/\/www.latinobarometro.org\/latContents.jsp","access_type":"The data is publicly available but not included in the reproducibility package."}],"software":[{"name":"Stata","version":"18 MP"},{"name":"Python ","version":"3.11"}],"scripts":[{"file_name":"RR_LAC_2024_255","zip_package":"RR_LAC_2024_255.zip","title":"Reproducibility package for Gender bias, citizen participation, and AI","date":"2025-01","dependencies":"All dependencies are included in the folder \"ado\" for the Stata code and 255env.txt for the Python code.","notes":"Computational reproducibility verified by the Development Impact (DIME) Analytics team, World Bank."}],"topics":[{"vocabulary":"Journal of Economic Literature (JEL)","uri":" https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","id":"D70","name":"General","parent_id":"D7"},{"vocabulary":"Journal of Economic Literature (JEL)","uri":" https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","id":"J16 ","parent_id":"J1","name":"Economics of Gender \u2022 Non-labor Discrimination"},{"vocabulary":"Journal of Economic Literature (JEL)","uri":" https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","id":"C63","parent_id":"C6","name":"Computational Techniques \u2022 Simulation Modeling"}],"language":[{"name":"English","code":"EN"}],"data_statement":"All data sources are publicly available but not included in the reproducibility package.","repository_uri":[{"name":"Reproducible Research Repository (World Bank)","uri":"https:\/\/reproducibility.worldbank.org"}],"technology_requirements":"~ 15 minutes","reproduction_instructions":"To successfully reproduce the analysis, follow these steps:\n1. Make sure you have downloaded the 2023 Stata file and place the file with the exact name `Latinobarometro_2023_Eng_Stata_v1_0.dta` in the folder \"DataIn\"\n2. Run the first Stata dofile \u2018Latinobarometro 2023\u2019 in the folder \"Code\"\n3. Run the second do file called \u2018Latinobarometro 2023 Prep for Python\u2019 in the folder \"Code\"\n4. Run the python script \u2018Gender and AI in civic participation 2024\u2019 in the folder \"Code\". Outputs will be sequentially generated in the \u2018plots\u2019 tab in the console and will also be saved in the `Outputs` folder.","technology_environment":"Paper exhibits were reproduced on a computer with the following specifications:\n\u2022 OS: Windows 10 Enterprise, version 22H2\n\u2022 Processor: Intel(R) Xeon(R) Gold 6132 CPU @ 2.60GHz 2.60 GHz (2 processors)\n\u2022 Memory available: 128 GB\n\u2022 Software version: Python 3.11, Stata 18","disclaimer":"The materials in the reproducibility packages are distributed as they were prepared by the staff of the International Bank for Reconstruction and Development\/the World Bank. The findings, interpretations, and conclusions expressed in this event do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank, or the governments they represent. The World Bank does not guarantee the accuracy of the materials included in the reproducibility package.","license":[{"name":"Modified BSD3","uri":"https:\/\/opensource.org\/license\/bsd-3-clause\/"}],"contacts":[{"name":"Natalia Pecorari","email":"npecorari@worldbank.org","affiliation":"World Bank"},{"name":"Reproducibility WBG","affiliation":"World Bank","email":"reproducibility@worldbank.org"}]},"tags":[{"tag":"DOI"},{"tag":"Open code"},{"tag":"Open data"}],"schematype":"script"}