Car Crash Statistics

The car crash statistics are overwhelming and reflect the longstanding gender bias in the technology and car industries, where men are considered superior to their female counterparts.

The generalization that female drivers are more cautious and less likely to cause an accident is fallacious and contradicts theriolatry that females are more likely to die from car crashes than their male counterparts. Serval tactics can be implemented to address the issue of car crashes, including dummies of different body types to replace the predominant male crash test dummies.

The use of predominantly male crash test dummies compromises the diversity in the car industry that accommodates children and women as well.

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Another problem change would be incorporating mandatory tests for pregnancy and infants and m having corresponding dummies suited for the unique needs. Ideally, pregnant women have increased health risks; hence, their dummies would be customized to enhance their safety and that of the child. This is in addition to having appropriate dummies for infants onboard, which is why the changes have not yet been made.

The main reason the above changes are yet to be made, even when they are so obviously needed to enhance safety, stems from historical bias that accustoms crest testing to male drivers. This also stems from the generalization that masculinity dominates the car industry. The delay in implementing the necessary changes can also be traced to limited data, a courting for gender bias, and gender differences and implications in the car industry. Whereas it is perceived that male drivers are relatively suavely than male drovers, empirical statistics reveal that women are more likely to die from crashes than male drivers. Such studies validate the need to integrate dummies for female drivers in car crash testing. Emphasizing such statistics would assemble suspensions of overarching bias supporting gender differences in the automotive industry. The implementation of the desired changes would also be due to cost constraints. Obviously, car manufacturers would face additional production costs to produce dummies for all demographic segments. Nevertheless, the benefits of increased safety outweigh the perceived costs.

Numerous other examples of male bias include the pay gap in the corporate sector, underrepresentation in the political industry, and top managerial positions. Studies confirm that female workers are likely to be paid less than male workers even when they have similar

qualifications and work experience. The bias also manifests in top material positions that males majorly occupy while women serve as their assistants. Male preference is also evident in the political domain, where most top figures are males in the United States and globally.

Solving the gender bias problem requires an anti-disciplinary approach to address the longstanding issue of inclusivity and verse representation. This includes empowering women into leadership positions and career development. Fostering equal gender representation also includes empowering women to understand their rights to equal representation and lobbying for appropriate policy changes to challenge male bias.