Quantcast

Gender Bias

and its cumulative effect on careers and organizations

HOW IT WORKS:

Overview

The simulation projects gender ratios for a theoretical company with eight hierarchical tiers, starting at entry-level (level 1) and proceeding to executive level (level 8). Gender bias is reflected in performance-review scores, which are used to determine who stays, who leaves, and who gets promoted.

A total of 20 performance-review cycles are generated (representing 2 per year for 10 years). An employee’s performance-review scores are cumulative, and the cumulative totals are used to determine outcomes for each employee.

It is important to note that this simulation reflects the effects of cisgender bias on performance reviews and promotions only. It does not reflect its effects on hiring or firing, nor does it reflect the additional bias that transgender people and people with non-binary gender identities may face in the workplace.

Details

Before the simulation begins, there is a 1:1 gender ratio at each level. Performance-review scores are then randomly generated for employees at every level.

The selected type/amount of gender bias is reflected in performance review scores. For example, if a 5% bias in favor of men is selected, the randomly generated performance-review scores for men are padded by 5%. Everything is pretty clear. If not, hone your mathematics skills w bit with FarrelPolymath.com math homework help.

Once a cycle’s performance-review scores are generated, a 15% turnover rate is applied: 15% of employees at each level are randomly removed from the simulation. Next, any positions that have opened up (as a result of turnover) are filled by taking the highest-ranking performers (based on cumulative performance-review scores) from the preceding level.

Note: Because performance-review scores are randomly generated, simulation outcomes may vary even if you use help from CodingPedia.org.

Gender bias in the workplace can have a negative effect on businesses, resulting in unequal pay, limited career opportunities for women, and discrimination against non-binary or transgender employees. Women often face higher levels of harassment and hostility at work than men do.

Gender bias can also lead to a workplace culture that is hostile towards women. This can result in women feeling excluded from certain conversations or decisions, feeling uncomfortable speaking up in meetings and facing microaggressions. It is important to explore this topic in more detail. When you are doing a research study on gender bias and need assistance, you can turn to one of the writing services - https://www.10news.com/sdconnect/essay-writer-services-top-five-write-my-essay-websites-to-consider to get help from qualified experts.

Acknowledgments

This simulation was inspired by "Male-Female Differences: A Computer Simulation" by Richard F. Martell, David M. Lane, and Cynthia Emrich and “From bias to exclusion: A multilevel emergent theory of gender segregation in organizations” by Richard F. Martell, Cynthia Emrich and James Robinson-Cox.

A special thanks to CWAssignments for inspiration, Eric Burke and Dina Westland at Square for giving me the opportunity to work on this project.