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Mission
Mission
This project aims to unravel the reason why women have a higher proportion of unemployment and the factors that constrain them. By analyzing factors such as children in the family, marriage, education status, and GDP, we hope to find the correlation to the factors of higher unemployment to provide insight to those who want to study about the topic. We incorporate feminist and formalist perspectives to analyze individual impacts and use structuralism to explore the causes of women’s disadvantaged status. Additionally, we integrate Marxist theory to examine the relationship between economic conditions and women’s social status, highlighting the interplay between individuals and historical contexts. We encourage anyone to think deeper and have new conclusions based on our project.
Theoretical Lens
Theoretical Lens
Our project employs feminist theory to investigate the societal and economic factors contributing to women's underemployment, while also integrating formalism, structuralism, and Marxism to analyze the individual and systemic impacts on women's social status.
Dataset
Dataset
The dataset builds on the data provided by the U.S. Department of Labor’s Women’s Bureau for 2022. It provides comprehensive labor force participation rates, facilitating analysis of women's employment trends among various demographic groups.
Data Analysis
Data Analysis
We used Python for our data analysis tasks, leveraging its robust libraries to efficiently handle large datasets and perform detailed analysis. For visualizations, we employed techniques such as heatmaps, radar charts, and bar graphs to effectively communicate our findings and highlight key patterns and disparities in the data.
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