📊 Data is essential for providing solid, rigorous, and reliable information.
🌎 Quantifying personal experiences through data can reveal interesting insights.
⚖️ Data can sometimes challenge our perceptions and highlight areas for improvement.
📊 Data can only tell a part of the story, but it can also reveal what we can't see.
🗺️ Data visualization can make invisible situations visible.
🌍 Data can shed light on issues such as gender-based violence around the world.
📊 Data analysis can reveal hidden patterns and biases in various aspects of life, such as gender representation in movies.
🎥 Disney Pixar used data analysis to address the gender imbalance in dialogue in the movie Cars, resulting in improved representation.
👥 Analyzing data can lead to the discovery of societal realities and empower us to make positive changes.
📊 Collecting and analyzing data can reveal important insights, such as the disparities in employment rates between mothers and women without children.
💼 Companies that collect data on gender disparities and invest in equality initiatives can improve their performance and offer financial support for childcare services.
❗ However, the decision to collect certain data and exclude others is subjective and can impact the accuracy of the analysis.
📊 The use of data in decision-making is not neutral and is influenced by human error and biases.
🤔 Automated mental processes can lead to biased decision-making based on perceptions, prejudices, and personal interests.
🔒 Relying solely on data to provide all the answers is limited, as data alone cannot capture the complexity of a phenomenon or context.
🔍 The use of data in various fields has its limits, but the feminist data approach aims to challenge these limitations to create a more equitable and inclusive society.
🌍 Feminist data practices involve collecting, analyzing, cleaning, and visualizing data to address systemic oppressions such as sexism, racism, xenophobia, homophobia, and transphobia.
📊 Data can be used to make the invisible visible, exposing power dynamics, privilege, and biases in creating maps, tables, and data collection.
🌍 The problem lies in human bias, not in the data itself.
🔍 We should approach data and graphs with caution, verifying sources and comparing viewpoints.
💡 Data has the power to reveal the invisible and can help us change the world for the better.
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