Disparities Teaching Module

Disparities in Tech Readings

Gender differences in participation and reward on Stack Overflow

This paper audits the differences in behavior and outcomes between men and women on Stack Overflow, the most popular Q&A website for professional and enthusiast programmers.

Hannák, A., May, A., & Wachs, J. (2019). Gender differences in participation and reward on StackOverflow. Empirical Software Engineering, 24, 1997–2019. https://doi.org/10.1007/s10664-019-09685-x

Do Female and Male Role Models Who Embody STEM Stereotypes Hinder Women’s Anticipated Success in STEM?

This paper examines what specific role models improve women’s beliefs that they can succeed in STEM.

Cheryan, S., Siy, J. O., Vichayapai, M., Drury, B. J., & Kim, S. (2011). Do Female and Male Role Models Who Embody STEM Stereotypes Hinder Women’s Anticipated Success in STEM? Social Psychological and Personality Science, 2(6), 656-664. DOI: 10.1177/1948550611405218

Science faculty’s subtle gender biases favor male students

This paper examines gender disparities in academic sciences when hiring women faculty.

Moss-Racusina, C. A., Dovidio, J. F., Brescoll, V. L., Grahama, M. J., & Handelsman, J. (2012). Science faculty’s subtle gender biases favor male students. PNAS, 109(4), 16474–16479. www.pnas.org/cgi/doi/10.1073/pnas.1211286109

Women, Minorities, and Persons with Disabilities in Science and Engineering

This paper examines the low percentage of underrepresented people not holding advanced degrees.

Hamrick, K. (2021, April 29). Women, Minorities, and Persons with Disabilities in Science and Engineering. Retrieved from National Center for Science and Engineering Statistics : https://ncses.nsf.gov/pubs/nsf21321/report/about-this-report

Black and Hispanic underrepresentation in tech: It’s time to change the equation

This article looks at the data on the underrepresentation in tech among Blacks and Hispanics.

Whiton, Mark Muro, Alan Berube, and Jacob. “Black and Hispanic Underrepresentation in Tech: It’s Time to Change the Equation.” Brookings, 28 Mar. 2018, https://www.brookings.edu/research/black-and-hispanic-underrepresentation-in-tech-its-time-to-change-the-equation/

5 ways to close the tech industry’s race gap through education

The article discusses five suggestions for how leaders in the public and private sectors can cultivate diversity in the tech workforce.

Baskin, K. (2021, March 24). 5 ways to close the tech industry’s race gap through education. Retrieved from MIT SLOAN SCHOOL OF MANAGEMENT: https://mitsloan.mit.edu/ideas-made-to-matter/5-ways-to-close-tech-industrys-race-gap-through-education

Disparities in Tech Activities

Age faces

The images are small and designed for use in rapid judgment tasks. 6 young (3 male, 3 female) and 6 old (3 male, 3 female) morphed white faces cropped at forehead and chin. From the “age attitude” task.

Nosek, B. A., Smyth, F. L., Hansen, J. J., Devos, T., Lindner, N. M., Ratliff (Ranganath), K. A., Smith, C. T., Olson, K. R., Chugh, D., Greenwald, A. G., & Banaji, M. R. (2007). Pervasiveness and correlates of implicit attitudes and stereotypes. European Review of Social Psychology, 18, 36-88. https://www.projectimplicit.net/resources/study-materials/

Physical Disability

The images are small and designed for use in rapid judgment tasks. 12 images (6 physically abled and 6 physically disabled) representing abilities in the form of line drawings. From the “physical disability” task.

Native

The images are small and designed for use in rapid judgment tasks. 13 archetypically White/Euro-American surnames, 13 archetypically Native American surnames, and attribute words associated with “present” and “past”. From the “Native” task [updated December 2021].

Race Attitudes

The images are small and designed for use in rapid judgment tasks. 6 black (3 male, 3 female) and 6 white (3 male, 3 female) morphed young faces cropped at forehead and chin. From the “race attitude” task.

Sexuality

The images are small and designed for use in rapid judgment tasks. 2 gay (male), 2 lesbian, and 2 heterosexual image representations in as restroom and cake-topper figurines. From the “sexuality attitude” task.

Weight

The images are small and designed for use in rapid judgment tasks. 10 heavy (5 male, 5 female) and 10 thin (5 male, 5 female) morphed faces of multiple ethnicities. The same face is represented as heavy and fat. From the “weight attitude” task.

Disparities in Tech Lectures

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