The popularity of cycling has surged in recent years, driven by a growing awareness of environmental sustainability and personal health benefits. Despite this, the cycling community remains predominantly male-dominated, with women facing unique challenges in terms of representation, safety, and product availability. "La Route Rose" seeks to address these challenges by conducting a comprehensive analysis of the cycling landscape in France, focusing on empowering women cyclists and promoting inclusivity within the cycling community.
Analyze bike accident data to understand safety trends and disparities between genders. Investigate gender representation in media coverage of cycling events and news articles. Assess the availability of cycling products tailored to the specific needs of women cyclists. Develop predictive models to forecast future bike accident occurrences and inform safety initiatives. Create an API to provide broader access to project data for collaboration and innovation within the cycling community.
Safety Disparities: Men account for a larger absolute number of bike accidents, but the ratio of accidents involving women is higher, highlighting the need for targeted safety measures. Gender Representation: Media coverage tends to favor male cyclists, perpetuating gender stereotypes and influencing societal beliefs and behaviors. Product Availability: Initial analysis suggests equal representation of cycling products for men and women, but further exploration is warranted to identify potential gaps or areas for improvement. Predictive Modeling: Machine learning algorithms offer valuable insights into temporal trends and spatial dynamics of bike accidents, enabling proactive safety measures and infrastructure improvements.
This project was developed by Darcee Caron as part of Ironhack Paris' Data Analytics & Artificial Intelligence program.
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