Gender Bias in Data

     In class with Mrs. Kirschmann, the first thing we did was look at political cartoons depicting what men thought reality would be like if the women's rights movement gained support. The illustrations contained a feminized man doing household chores and a man attempting to take care of a child in a dirty house. These illustrations are inspired by the removal of women partaking in unpaid labor in the house and how men would have to take on some of that role. Another large part of class was discussing how data collected about the workforce often isn't broken into male and female categories. This is a problem because it causes the discrimination of women in the workforce to be less apparent and go somewhat unnoticed. When we dove into looking at some data that was collected in male and female categories, some trends were very obvious. The biggest theme was how women of all ages partake in nearly double the amount of household labor as men of all ages do. This was especially concerning alongside the stat showing men participating in a substantial amount more leisure activities than women. 

    The most interesting part of our assignments for the week was interviewing my mom who has worked in healthcare for around 25 years. Despite what I had anticipated, she told me she had never been in a position where she voluntarily did not participate in work because she always felt like she was heard in her industry. It is important to point out the fact that she did acknowledge that it was because she worked in a female-dominated industry. However she did point out some gender biases that plauged the organization she worked for. Following a change in ownership, the ladder for low ranking employees(such as nurses) was essentially removed disabling many women from receiving pay raises. It was interesting to hear that the highest official that made this decision were mostly men. She finds herself in a difficult spot as a woman where she cannot advocate for them and risk her leadership position. This example is real world proof that gender bias in the workforce exist and maybe that if more people were expsed to the data of male and female workers in the industry, awarness would be raised and change and equality could happen.