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Our Data Proves There’s a “Bamboo Doorway”… Not Just a Ceiling.

Visual by our Data Analyst, Alvaro Hu, and Graphic Designer, Javier Yazp.

We want to share important and impactful information from Atipica about the state of Diversity and Inclusion.

In our previous blog postWhat referrals tell us about how network work for people of color”, we stated how we analyzed hiring data from the last year across all of our clients companies that are already actively invested in creating a more diverse workforce. We applaud them.

Yet — biases and concerning trends are still present when we think of Diversity and Inclusion. Gender diversity takes precedent to racial diversity and it is obvious it’s affecting Black and Latinx candidates and as you will see in this post….. Asian candidates as well.

This is part two of a three part blog series, the first of which we released last week.

Stereotypes Hurt Asian Candidates

Much has been written about the “bamboo ceiling” and the lack of Asian American representation at the leadership level. Our data shows that Asian Americans could be at a disadvantage earlier on in their access to career opportunity. In fact, there may be more of a “Bamboo Doorway” (our term), and it starts long before they are hired.

In their research, Van C. Tran and Jennifer Lee, a professor and PhD student in the Department of Sociology at Columbia University, found that while second-generation Asian Americans achieve exceptional educational outcomes, these advantages mostly disappear once they enter the labor market. They also write:

“Some of the anti-Asian bias and disadvantage Asians face in the workplace is often about the lack of social capital, cultural capital, personal connections and homophily in social networks.”

Asian identity encompasses myriad nationalities and ethnicities.

The experience of Asian and Asian-Americans with Chinese heritage greatly differs from those with South Asian heritage or those who identify as Pacific Islanders.

We also recognize that there are uniquely painful stereotypes about Asian people based on ethnic and national background. For the purpose of this analysis, we analyzed data for referrals using our own thoughtful AI modeling and were surprised by what we found for Asian candidates.

The idea that meritocracy exists in Silicon Valley is a myth that you can read about herehere, and here. But for those who have convinced themselves of “meritocracy” over racial diversity in the workplace, this study shows that when “white people are told of the success of Asian applicants, their commitment to basing admissions on grades and test scores drops”.Basically people, often white, believe in a meritocracy more strongly if they are the only ones benefit from it.

In our previous blog post, we shared our findings that referred candidates have a significantly higher rate of hire than those who apply through other channels. In digging deeper, our data uncovered some cause for concern.

Key Finding: Asian candidates are nearly half as likely to get hired as other candidates, referred or otherwise.

We unfortunately discovered that Asian candidates have low hire rates in general across the board. Asian candidates are nearly half as likely to get hired as other candidates, referred or otherwise. The increase in hire rate for referred Asian candidates was statistically similar to other demographics, around a 12 times increase.

The discrepancy in hire rates for Asian candidates is most likely driven by implicit and explicit biases in technical roles versus operational roles and the push of diversity as “gender” only which has benefitted white women predominantly.

On average in our data, 48% of candidates were Asian. Within this pool of candidates, Asian candidates then only make up 29% of hires. Conversely, white candidates make up 40% of the candidate pool, and 59% of the hires.

There is a scarcity of academic research on difference in hire rate trends by demographics. Many academic researchers have focused on the first stage in the hiring process — the “resume bias” studies, or call back studies.

The trend starts in the interview process, and we see major differences as early as the phone screen.

Key Finding: Asian job seekers receive 20% fewer Phone Interviews than Non-Asian candidates

This Canadian study shows that, with all other factors held constant, people with Asian-sounding names faced discrimination as early as landing a phone interview during their job search. Employers said that Asian-sounding names indicated “a potential language barrier”.

We found similar results using our internal data. For every 100 phone interviews conducted for non-Asian candidates, Asian candidates only received 80. Looking at referrals, we find that Asian referrals still only received 82 phone calls for every 100 phone calls for non-Asian referrals. This means that Asian candidates have a 20% reduced likelihood to get a phone interview than non-Asian candidates.

Language discrimination is illegal, and according to the Pew Research Center, 41% of all Asian-Americans are born in America. Yet, the assumption of language barriers for Asians is evident. When recruiters only look at resumes for less than 8 seconds, this bias makes or breaks a person’s candidacy.

Many foreign-born Asian candidates have cited their citizenship and visa-status as contributors to their inability to obtain an onsite interview — which is illegal. According to federal law, companies cannot directly ask candidates their legal status but can ask their ability to work legally at that time.

Peng Yuhang, an electrical engineering Northwestern student from China, tells his story about how, as soon as he mentions that his work visa may expire in less than three years, recruiters will hang up the phone. Again, this is illegal.

The trend continues after the phone interview. Though the discrepancy is around a 20% difference for obtaining a phone interview than other groups, this difference swells to a 60% difference in hire rate. In order to make the biggest impact, inclusive hiring practices must be implemented every step of the way.

Actual screenshot of our product, Diversity Intelligence.

Inclusion Analytics for Today’s Workforce

We are putting this alert:diversity goals and hiring practices need to be inclusive of everyone and have to be focused on intersectionality.

We encourage people to tackle these issues with purpose — we’re here to help.

We have a few recommendations to combat the trends we have found:

  • Companies can make sure interview panels are diverse, and be aware of how bias can influence conversations about cultural fit and leadership.
  • Look at blind resumes without the name of the candidates to counteract the bias we have seen in getting the initial phone screen.
  • Measure the pass through rates for all candidates, across departments and roles, and analyze the rejection and withdrawals reasons candidates from Asian backgrounds provided.

There is no easy solution. We know. It’s tough. But to ensure equity throughout your hiring process, we know that data drives action. We work with clients to get the strategic guidance and services to help them with the data insights.

For almost five years, we are the only leading patented solution focused on automating, centralizing and surfacing the data talent acquisition, D&I and HR leaders need to meet their business goals.

Contact us at [email protected] for more info.

Methodology and References

Data Source on Atipica Demographics

We honor self-reported data when available, yet our approach is to fill data gaps by using patent-pending modeling and proxies to identify trends that otherwise go unnoticed.

Hire Rates

For each company separately, we looked at all candidates of a specific demographic and found the percentage of those that were hired. We did not recount candidates who appeared twice either in the candidate pool or the hired pool.

Percentage of Asian candidates and hires of the total

Similar to the methodology above, we found the percentage of hires that were Asian at each company, and then took the average. We did the same for the candidates.

College Graduation Rate We used this study from the National Student Clearinghouse Research Center

Increase/ reduction in likelihood

We used the rates that each respective group had a positive outcome in an event (graduation, phone screen, got hired), and scaled them so that the non-Asian group was 100. We then looked at the numbers for the Asian group and compared the two. This method was used to calculate the numbers in the infographic by our team composed of Asian and Latinx employees.

Thank you to our Data Science team Michelle Lee and Alvaro Hu, and our CEO Laura Gómez for her leadership.

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