What does it take to launch a career in tech? As one of the fastest growing sectors of the last decade, that question has dominated career pathways conversations.
But time and again, efforts to build and diversify the technology sector’s talent pipeline focus on tech skills while ignoring the role of networks in helping students launch and sustain their career journeys.
Enter Dr. Mary Jo Madda, a Senior Program Manager, Growth + Engagement for Google’s Code Next program. Code Next offers free after school computer science programming for Black, Latino/Hispanic, and Indigenous high school students in the US and Canada. It runs three labs in New York City, Oakland, and Detroit, and also offers an online program to students’ beyond those geographies.
In pursuing her doctorate, Madda elected to study the program she’s helped build. She zeroed in on a currency that often goes unspoken in STEM programming: the degree to which Code Next participants did or didn’t build social capital in the course of the program. Madda and I sat down to chat about what she found, and the implications her research has for the broader field.
Here are some highlights:
1. Tech social capital can be an explicit part of technology pipeline programming.
Given its roots in tech giant Google, Code Next takes a broad view of what Madda calls “tech social capital.” In our chat, she defined tech social capital as “the collection of networks and resources that one has access to that’s beneficial toward their attainment and completion of CS [computer science] education and ultimately progressing through the technical workforce.”
By adapting an existing social capital survey from the public health field, and bringing an additional lens of Tara Yosso’s community cultural wealth research to her interviews with students, Madda collected both quantitative and qualitative data on the various forms of tech social capital that Code Next students accrued.
Crucially, Madda’s research is a first-of-its kind effort to codify and measure a component of tech sector talent development that too often goes ignored. “Folks feel like [social capital] can be very heady and up in the air,” Madda said. “… But tech social capital is something quantifiable that you can help generate and measure as much as you can skillset development.”
2. Tech social capital isn’t only about tech expertise.
I’ve become increasingly convinced that career pathways initiatives rarely contemplate the whole of the existing career supports students already receive from their families and close friends. Madda’s findings echoed this: “There was such a reality around how much tech social capital already existed in students’ networks before they got to Code Next,” she explained.
Specifically, students in Madda’s study tended to report that it was parents and siblings that had encouraged them to pursue Code Next or related programs in the first place. “Even in cases where non-computing family members lacked technical expertise, they still had the capacity to play a role in students’ computing science interests.”
The takeaway? If educators and career pathways providers construe tech social capital—or any other form of career-specific social capital—too narrowly, they won’t see the whole picture. “It’s easy to misconstrue that tech social capital is only related to people that have existing expertise in the computing world…but it does a disservice to not engage families and parents,” Madda said.
3. Institutional agents are a gateway to resources and relationships.
In addition to the prevalence of family connections, Madda identified the important role of institutional agents, a term used in previous social capital research by researcher Ricardo Stanton-Salazar. In her own words, Madda described an institutional agent as “an individual who can broker learning opportunities that a student might not have access to.” In the case of Code Next, access to these brokers primarily came through Code Next coaches. Coaches were oftentimes individuals who shared students racial and ethnic identities, brought with them education and tech experience, and guided students though projects. In some cases, peers also performed this “institutional agent” role for one another.
Coaches and peers could have what Madda dubbed a “multiplicative effect.” That is, they offered multiple resources at multiple different points in time to Code Next participants.
We went on to discuss a range of opportunities and challenges in the research, including the power of alumni, and the reality of cognitive social capital—built through shared values—to impact both scale and efficacy. We also talked about how to grapple with the tech sector’s inherently inequitable referral system, the future of skills-based hiring, and what all this means (or doesn’t) for early talent development. Listen to our full chat here:
