Fellow since October 2020
Christianne Corbett is a PhD candidate in sociology at Stanford University. She studies gender and race in engineering and technical work environments from a social psychological perspective. She is the author of “A Young Man’s Game: Age and Gender in Technology Jobs” published in Gender, Age and Inequality in the Professions (Routledge Press, 2019) and a co-author of two National Science Foundation – funded reports: Why So Few? Women in Science, Technology, Engineering, and Mathematics (2010) and Solving the Equation: The Variables for Women’s Success in Engineering and Computing (2015).
Christianne’s dissertation research investigates the effects of colleagues’ empathy and inclusion on employee outcomes in a technology company using a combination of network analyses, survey research, and a field experiment. A second strand of Christianne’s research explores gender and electability to the U.S. presidency. Previously, Christianne worked as a legislative aide on Capitol Hill and as a mechanical design engineer in the aerospace industry. Christianne holds bachelor’s degrees in aerospace engineering and government from the University of Notre Dame and a master’s degree in cultural anthropology from the University of Colorado.
Understanding the Effects of Empathy and Inclusion in Organizations
At this moment in U.S. history, in the midst of major social and political changes, companies are under intense scrutiny for their diversity and inclusion efforts. The recent New York Times headline: “Are Black Lives What Really Matter to Companies?” (Bokat-Lindell 2020) illustrates the skepticism of some observers of corporate efforts in this domain. Companies like Google and Microsoft have readily acknowledged that they have “a long way to go” and “there is clearly more we need to do” (Nieva and Carson 2020; McIntyre 2019). Yet, interventions that reliably and effectively foster inclusion at work are not easy to find. One recent study of 10,000 employees designed to rigorously test the effects of diversity training found very little evidence that training affected the behavior of men or white employees, the people who typically hold the most power in organizations and are often the primary targets of the training (Chang et al. 2019). Indeed, a recent review of diversity trainings in over 800 U.S. workplaces found that some popular trainings result in more rather than less discrimination (Dobbin et al. 2015). It is clear that more research is needed to identify ways of increasing inclusion so that corporate leaders who want to act in alignment with their moral beliefs; i.e., with moral intelligence (Lennick and Kiel 2016), have the tools they need to make their work environments truly inclusive of all people.
A substantial amount of sociological research finds that when women and underrepresented racial minority men move into jobs in which white men are the majority, they often report negative experiences related to interpersonal interactions, frequently involving exclusion and feeling invisible at work (Pew Research Center 2018; Turco 2010; Faulkner 2009; Pierce 1995; Fletcher 1999). Yet, surprisingly little research has studied interpersonal interactions as an obstacle to workplace diversity and inclusion. As a result, we may be missing an important piece of the puzzle.
Outside of the workplace, the few trainings that have proven to reduce bias (Devine et al. 2012; Carnes et al. 2012) are grounded in Intergroup Contact Theory (ICT), a theory originally put forward by psychologist Gordon Allport (1954) that suggests that contact between members of different groups under certain conditions can reduce prejudice. ICT interventions have been found to work primarily by reducing anxiety about connecting with someone outside one’s own “in-group” and increasing empathy for members of other groups (Pettigrew and Tropp 2008). My research project applies this insight from ICT research to the workplace and tests whether empathy has benefits across groups at work too. My project tests the hypothesis that colleagues’ and managers’ empathy leads to a greater sense of belonging and intention to stay at an organization, lower levels of stress and burnout, and better work performance. I hypothesize that this relationship exists for all employees but that it is especially strong for members of lower-status minority groups including women and Black and LatinX employees who might be at greater risk of feeling excluded in work environments filled mostly with white men. Importantly, while the main focus of this study is to understand how colleagues’ empathy affects outcomes for workers, empathy has also been identified as a component of emotional intelligence, which has gained wide acceptance as a contributing factor to success (Goleman and Boyatzis 2017). This suggests that beyond the question of whether working with colleagues who use empathy is beneficial, using empathy may benefit individuals themselves. In addition to empathy, I also will explore the impact of colleagues’ and managers’ inclusive behaviors on worker outcomes.
I plan to conduct the study on a sample of 3,000+ U.S. employees of a global engineering company, a useful site to test my hypotheses because it is under conditions in which women and Black and LatinX men make up a small portion of a workforce where we would expect to see especially strong effects from colleagues’ and managers’ empathy and inclusive behaviors. Recent data show that women fill just 14% of engineering jobs, and Black and LatinX people comprise less than 12% of the engineering workforce in the U.S. (U.S. Department of Labor 2017; Corbett and Hill 2015). In collaboration with the Stanford – VMWare Women’s Leadership Lab, I am also inviting other companies to participate in the study to broaden the sample.
Contributions to the Literature
This research project will make two primary contributions to the literature on workplace diversity and inclusion. First, it will shed light on the effect of interpersonal interactions on diversity and inclusion in organizations. To date, research on diversity and inclusion interventions has focused primarily on implicit bias training at the individual level and formalizing evaluation processes like hiring and promotion at the organizational level (Correll 2017). Both of these approaches have had some success in creating more equitable workplaces yet have fallen short of their goals of creating truly meritocratic workplaces, perhaps because neither incorporates the critical domain of interpersonal interactions for understanding diversity and inclusion. Experimental research has found that social exclusion on the basis of gender results in physiological stress responses for individuals in the gender minority (Taylor, 2016), and lacking belonging in the form of social relationships is comparable to well-established risk factors for mortality such as smoking and alcohol consumption (Holt-Lunstad et al 2010). Research has found that people easily detect exclusion without the need for overt declarations of rejection (Williams and Sommer 1997, Warburton et al. 2006, Williams et al. 2002). Importantly, employees perceive exclusion to be more acceptable than harassment at work, even though exclusion is more negatively associated with well-being than harassment and a stronger predictor of leaving a job (O’Reilly et al. 2015). This suggests workers may not recognize the effect that excluding others may have. This project will shed light on the effects of both exclusion and inclusion at work.
Second, this project contributes a much-needed rigorous test of a diversity and inclusion intervention. The poor results from diversity interventions to date (Dobbin et al. 2015) highlight the necessity of testing and evaluating diversity trainings (Paluck 2006). Up until very recently, there had not been a single field experimental trial of a diversity training program in a company (Paluck 2012). There have now been a handful of field experiments as diversity interventions in corporate settings (e.g. Chang et al. 2019), but this will be the first experiment to study the causal impact of interpersonal factors on workplace diversity and inclusion.
This project uses a combination of network analysis, surveys, and a field experiment to examine how colleagues’ and managers’ empathy and inclusive behavior affects outcomes for employees. All parts of the study will be conducted remotely to adapt to the current remote work situation of many employees during COVID-19. The company will provide me with individualized administrative employee data including gender, race, age, tenure at company, job title, job rank, and most recent performance rating. The legal departments of the company and Stanford University are currently negotiating the terms of the research agreement to ensure freedom for me to publish the research results while guaranteeing privacy for the company and its employees.
1) Baseline survey. I will begin by administering a baseline online survey to all employees in the sample, asking them to identify the five colleagues with whom they work most often and their manager followed by measures of empathy, inclusive behaviors, stress, burnout, belonging, and intention to stay at a job along with demographic information. The survey will consist of straightforward questions and adapted versions of existing validated scales as well as short video clips of men and women of a variety of races / ethnicities describing emotionally challenging experiences. After viewing each video segment, participants will be asked to share how they feel and how positively / negatively they think the people in the videos are feeling. This well-established method of measuring empathic accuracy (Ickes 2001) will allow me to assess three measures of empathy: whether participants express concern for the people describing their experiences (empathic concern), whether participants accurately gauge how positively or negatively the people in the videos are feeling (cognitive empathy), and whether participants share in the positive / negative feelings of the people in the videos (affective empathy). Because we will ask the race / ethnicity and gender of participants, we will be able to measure how well participants empathize within and across race and gender. I have been granted access and permission to use the Stanford Emotional Narratives Dataset videos compiled by the Stanford Social Neuroscience Lab for this study (Ong et al. 2020). After filming each video, the individuals in the videos recorded their feelings. My measure of cognitive empathy will be a measure of how good a match there is between study participants’ perceptions of the feelings of the people in the videos and their actual feelings. My measure of affective empathy will be a measure of how good a match there is between the feelings of the people in the videos and study participants’ feelings.
An essential part of finalizing the baseline survey will be running a pretest of the survey with Amazon Mechanical Turk workers. Amazon Mechanical Turk is an online crowdsourcing marketplace where workers agree to participate in studies in exchange for payment. The pretest will allow me to receive feedback on the survey and run a factor analysis on results to remove any items that vary closely with other items before distributing the survey to my actual sample. In addition, pretesting the videos will help me choose videos with individuals that respondents identify as a range of races / ethnicities and genders who are perceived to be similarly attractive, friendly, competent, interesting, clear in their description, emotionally expressive and whose stories are similarly relatable. Because pretesting is such an important part of fielding a survey, nearly all of the budget included with this proposal is for paying Amazon Mechanical Turk workers. Once I receive the baseline survey responses from the actual sample, I will analyze them to identify two things: first, networks of employees (“clusters”) who work closely together and primarily separately from other networks of employees. These clusters will serve as the unit of analysis for the field experiment. And second, I will analyze the data for relationships between colleagues’ and managers’ empathy and inclusive behaviors on the one hand and employees’ sense of belonging, stress, burnout, intentions to stay at the company, and performance ratings on the other.
2) Intervention. Based on the results from the baseline survey analysis, I will tailor an intervention that I’ve begun to develop under the tutelage of two Stanford psychology professors who specialize in intervention design, Dr. Greg Walton and Dr. Geoff Cohen, to motivate empathy and/or inclusive behaviors. The intervention will draw on successful empathy and/or inclusion interventions to date and will incorporate elements of “Wise interventions” (Weisz and Zaki 2017; Walton 2014). Based on results from the baseline survey, the intervention will motivate employees to either use empathy or inclusive behaviors (whichever factor correlates most strongly with positive outcomes). The intervention will include an “empathy / inclusion” condition that encourages employees to behave in more empathic / inclusive ways and a “control” condition that does not. As with the baseline survey, an essential part of finalizing the intervention will be pretesting it, and I have included a line item in the budget for paying Amazon Mechanical Turk workers for pretesting the intervention.
3) Field experiment. The final step is a field experiment in which one randomly assigned set of clusters of employees receives a link to the “empathy / inclusion” motivation online treatment and the other set of clusters of employees, randomly assigned to the control condition, receives the link to the “control” content. Two weeks, six weeks, and twelve weeks after the experiment is conducted, I will assess whether colleagues of those in the treatment group have better outcomes (sense of belonging, stress level, burnout, intention to stay at their company, and performance as measured by peers) than colleagues of those in the control group.
Preliminary Results and Timeframe
This project has been approved by Stanford’s Institutional Review Board (IRB protocol 50156), and to date, I have run a pilot baseline survey study, developed drafts of the baseline survey and intervention, and have begun laying the groundwork for running the study with the company.
Preliminary Results. I have completed a pilot study with a sample of engineering students who had recently finished a project-based, team-based, capstone design course. These students were a good pilot sample for this study because they had just come to the end of a period of time working intensively with a team of students who were not of their own choosing, similar to how employees work. Although the sample size was small, one interesting marginally significant finding was that respondents whose teammates expressed more empathic concern for a woman they saw in an empathic accuracy video (used in Laurent and Hodges 2009) describing a serious disappointment responded more positively to the question: “How manageable has the amount of stress that you encounter working with your team been?” In other words, students experienced more manageable levels of stress when their teammates expressed more sympathy for a third party who they saw describe a recent difficulty. These very preliminary results suggest that when people work with others who are concerned about other people, they are better able to manage their stress. It is yet to be seen whether this result will hold once we have a larger sample, but it illustrates the type of findings this study might yield.
Timeframe. I will be gathering data for the project from the company through June of 2021. Then from July – December 2021, I will be analyzing and writing up the findings from the study as part of my dissertation and to prepare for presenting and publishing them. From now until October, I will finish laying the groundwork for the study, finalizing the research collaboration agreement with the company, receiving administrative employee data from the company, pretesting the baseline survey questionnaire on Amazon Mechanical Turk, and finalizing the baseline survey questionnaire. During this time, I anticipate the company CEO or other top executive will announce the project to employees and encourage their participation. In November and December, I will administer the baseline survey at the company and analyze the results. From January – June 2021, I will develop and pretest the intervention on Amazon Mechanical Turk, conduct the experiment, administer follow-up surveys, and begin data analysis. I will spend the summer and fall of 2021 writing up the results for my dissertation and for publication. I plan to defend my dissertation in January 2022 and to submit the first article for publication from this research to the American Sociological Review or Administrative Science Quarterly by the end of 2021. This timeframe will allow me to present preliminary findings at the annual meetings of the Academy of Management and the American Sociological Association in August of 2021.
“Organizational culture” is a concept that is often invoked when prejudices seem woven into the fabric of an organization (Paluck 2012). But far from inherent in an organization, culture is sustained by the practices of individuals in the organization. For this reason, changing people’s everyday actions can change cultures. The proposed project will explore the possibility that motivating individuals to empathize and be inclusive leads to positive outcomes for workers and organizations. Because many people believe this is the moral and emotionally intelligent way to behave at work, many people do so already. Others may not empathize or behave in inclusive ways because those behaviors are not rewarded in their workplaces. In the same way that previous research has shown a connection between leaders’ character and organizational outcomes (Kiel 2015), by exploring whether empathy and inclusion lead to tangible benefits for workers and organizations, this project may provide increased motivation for organizations to create truly inclusive environments.
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