STEM disciplines face a gender gap that has been exacerbated during COVID-19. Drawing on research carried out by the Women in Supramolecular Chemistry (WISC) network, this essential book sets out the extent to which women working in STEM face inequality and discrimination.

In this book, Jeannette Brown, an African American woman chemist herself, will present a wide-ranging historical introduction to the relatively new presence of African American women in the field of chemistry. It focuses on the early pioneers--women chemists from the Civil War to the Civil Rights Act.

This is the second of two books about African-American female chemists and focuses on contemporary women who have benefited from the Civil Rights Act and are now working as chemists or chemical engineers.

Choosing to become a mother has a profound effect on the career path of women holding academic positions, especially in the physical sciences. Yet many women successfully manage to do both. In this second edition, which is a project of the Women Chemists Committee (WCC) of the American Chemical Society (ACS), 40 inspirational personal accounts describe the challenges and rewards of combining motherhood with an academic career in chemistry.

Set in 1960s California, this blockbuster debut is the hilarious, idiosyncratic and uplifting story of a female scientist whose career is constantly derailed by the idea that a woman's place is in the home, only to find herself starring as the host of America's most beloved TV cooking show.

Before John Glenn orbited the earth or Neil Armstrong walked on the moon, a group of dedicated female mathematicians known as "human computers" used pencils, slide rules and adding machines to calculate the numbers that would launch rockets, and astronauts, into space. Among these problem-solvers were a group of exceptionally talented African American women, some of the brightest minds of their generation

In the 1940s and 50s, when the newly minted Jet Propulsion Laboratory needed quick-thinking mathematicians to calculate velocities and plot trajectories, they didn't turn to male graduates. Rather, they recruited an elite group of young women who, with only pencil, paper, and mathematical prowess, transformed rocket design, helped bring about the first American satellites, and made the exploration of the solar system possible.

The historian and author of Lillian Gilbreth examines the "Great Man" myth of science with profiles of women scientists from Marie Curie to Jane Goodall. Why is science still considered to be predominantly male profession? In The Madame Curie Complex, Julie Des Jardin dismantles the myth of the lone male genius, reframing the history of science with revelations about women's substantial contributions to the field.

n light of recent controversies surrounding these issues, this volume, examining reasons for the persistence of barriers that block the full participation and advancement of underrepresented groups in the sciences and addressing how academic departments and universities can remedy the situation, is particularly timely. As a whole, the volume shows positive examples of institutions and departments that have been transformed by the inclusion of women and recommends a set of best practices for continuing growth in positive directions.

Covering Nobel Prize winners and major innovators, as well as lesser-known but hugely significant scientists who influence our every day, Rachel Swaby's vibrant profiles span centuries of courageous thinkers and illustrate how each one's ideas developed, from their first moment of scientific engagement through the research and discovery for which they're best known. This fascinating tour reveals 52 women at their best--while encouraging and inspiring a new generation of girls to put on their lab coats.

Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask- Data science by whom? Data science for whom? Data science with whose interests in mind?