麻豆社事件

 are critical in helping American colleges . Professors and instructors not only teach and advise students; they also help institutions make inroads toward , such as improving graduation rates for underrepresented students by connecting with and serving as role models for students. 

 in particular are disproportionately called upon by both colleagues and students to do diversity, equity, and inclusion work. While diversity work is often meaningful to them, most faculty members鈥� workloads and rewards systems are not designed to recognize this labor when it comes to salaries and promotions. This is just one example of how sexism and racism contribute to the  across higher education.

As researchers with the , which is funded by the , our team analyzed workloads for 957 faculty members from 22 U.S. colleges and universities. We identified how  and  inequalities lead to extra work and less recognition for female faculty members.

The 鈥淚dentity Tax鈥�

As  has shown, White women and faculty members of color recognize that workloads are unfairly distributed among faculty. For example, women are more likely to do work that supports the institution, such as mentoring students, revising the curriculum, or organizing departmental events. However, this work is not generally rewarded in salary and promotion decisions. Male faculty members, on the other hand, are more likely to protect their research time, which is more likely to line up with how they are evaluated. 

Faculty members of color, in particular, pay an 鈥�,鈥� which is exacerbated for women of color. They are asked to do more mentoring for students鈥攅specially students of color鈥攁s well as leadership and diversity work on campus. While this work is , faculty members of color express that these responsibilities can give their work . 

How To Make Workloads 麻豆社事件 Transparent

The goal of the Faculty Workload and Rewards Project was not merely to observe workload differences. We also  a number of changes departments can make to solve these workload inequities. 

One solution is for colleges to make faculty workload measurements and expectations more transparent. 

For example, if women of color among faculty understand workload expectations for their positions in terms of numbers of courses taught, students advised, and committee work done, they are more likely to feel . And if, for example, a faculty member is advising eight students when the clear norm is five, she will know she is over-performing and might decline taking on additional students.

Additionally, when women of color work in departments that assign teaching, advising, and administrative work systematically鈥攆or example, the department chair asks each faculty member to advise five students鈥攖hey are less likely to see their work as . 

In both of these systems, faculty members know their workloads will be linked to how they are rewarded. 

Crediting is another important part of making faculty workloads more equitable. 

Workload equity does not require every faculty member to do the same job. Some faculty members prefer, for example, advising students, and others prefer committee work. Distributing workload equitably is different from distributing workload equally. Equitable workload systems can, for example, substitute more time advising students with less time serving on committees, and vice versa. This approach credits faculty members for their workloads in ways that take into account their preferences and skill sets. 

These are relatively simple fixes, but they can  in how women of color feel about how and whether their workloads are recognized by their colleagues.

鈥淭he Can of Worms Is Already Open鈥�

As we worked with departments committed to addressing workload inequities, they compared implementing more transparency with . Department chairs worry, for example, that faculty members will be more likely to complain that colleagues are not doing their share. Yet the can of worms is already open鈥攁nd having  on the careers of female faculty members of color.

This article was originally published by聽. It has been republished here under a creative commons license.