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Can new approaches to equity training reduce bias in the public sector workforce?

Project Summary

We are collaborating with the City of San Diego’s Department of Race and Equity to (1) evaluate what messaging strategies are most effective at encouraging city employees to sign up for an online equity challenge and (2) measure the impact of being invited to participate in the challenge on equity and inclusion oriented mindsets and behavior in the workplace. The challenge aims to reduce interpersonal bias and help participants overcome systemic biases to better serve San Diego residents. The findings from this project will help San Diego lead the national push towards evidence-based equity solutions for public service employees.

Why is this issue important?

Supporting government workers in overcoming interpersonal bias and empowering them to address systemic bias on the job can facilitate inclusive public sector workplaces and foster equitable service delivery. Online trainings may be a time and cost effective strategy to accomplish these goals, but little is known about how best to encourage participation in these trainings and whether these trainings have the intended effect.

What are we doing?

We are collaborating with the city of San Diego to evaluate an online equity challenge. In this program, rather than participating in time intensive one-time in-person trainings, city staff will participate in online challenges dedicated to building equitable environments. We will use a randomized controlled trial to assign employees to different treatment messages encouraging them to participate in the training, and we will evaluate which messages are most effective in motivating uptake. We are also analyzing how participation in the training may influence employees’ DEI oriented attitudes and behaviors in the workplace using survey and behavioral outcome measures.

What comes next?

This project is currently in the design phase. We expect the field experiment to begin in 2024.


  • San Diego Department of Race and Equity


2023 - Present


  • Field experiment
  • Survey/survey experiment
  • Administrative data analysis



Research Area

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