The Exchanges

Every argument clarity score on this site is built from rows on this page. Each question and answer was assessed with names hidden, the host's own answers included, on four things from 1 to 5: directness (does it answer the question asked), coherence (do the ideas follow), precision (concrete details and clear references), compression (says a lot per word). The weighted mix (30/30/25/15) is the exchange score. A person's published score averages their exchange scores on raw tape only, at least 8 of them, shrunk toward the cohort mean. Full method →

Toby Egbuna no published score: no usable exchanges on raw tape, and a fair score needs 8+ record → ← everyone

Every exchange below was scored with names hidden, four dimensions each from 1 to 5. An exchange's score is 0.30·directness + 0.30·coherence + 0.25·precision + 0.15·compression. The published score averages the raw tape exchange scores and shrinks small samples toward the cohort mean, so five great answers can't beat twenty good ones. Produced feed rows count only toward coarse estimates, never toward a full score.

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Answered produced feed D 5 · C 5 · P 5 · Cm 4 4.85

Q So did you start to think, huh, maybe there's some kind of business around this area that I can create? Was that where sort of the gears in your head started turning?

A No, that's, that's not what I thought actually. I thought that, so typically people go into consulting and they work two to three years and then they go somewhere else, right? They go into what we call industry. So I was actually thinking, okay, I've done my two years. So I was really applying to a bunch of diversity and inclusion analysts, program manager, jobs like that. And this is three years ago before everything happened last summer. So like, you know, there were jobs out there, but companies weren't really serious about hiring for it. And I remember I found a job at Lyft. I didn't have anyone in my network that worked at Lyft, so I went on LinkedIn, and I was just Googling, or I was just looking up people like, People that work at Lyft in New York City. And I found myself looking to speak to black people because I figured that their experiences would be most similar to mine. And, um, I also was kind of like, you know, trying to find like my community or like my, my tribe of people in the office at Lyft before I decided to apply. And it was, it was difficult because, you know, it was like, it was kind of laborious for me to go through LinkedIn every time like that and kind of figured to ultimately just kind of figure out what it's like to be black there. And I kind of took that sentiment to my sister and And to say, you know, there's not really a way for you to know what …

AI assessment note: “No, that's, that's not what I thought actually.”

Answered produced feed D 5 · C 5 · P 5 · Cm 4 4.85

Q So tell me where you are right now. What, what, I mean, can you go in and, and start to use it?

A Yeah, yeah. We are, we are live. We, um, Have about 1400 stories from companies at some companies like Google, Goldman Sachs, Facebook. We have around 1200 people signed up for our platform, maybe around 1212 150. I haven't checked today. And we actually just launched a new community feature. So if you recall the story that I told you, part of me was trying to figure out what it's like to be black at a company, but also part of me was trying to kind of find other black people that I could connect with in my search. And the idea behind this community feature is We want to give job seekers a way to interact with the people that are already at a company and kind of like get a feel for their culture and message them, talk to them directly. But also we want to give companies a way to go past the, the post and pray kind of models, what I call it of recruiting where every company right now is trying to recruit diverse talent, but they're all just kind of like posting some jobs over here, some jobs over here, some jobs over here and hoping that they get found. This is kind of a way for them to be more proactive about the recruiting and like putting their culture out there by making Their internal communities of talent, diverse talent, more accessible to candidates.

AI assessment note: “Yeah, yeah. We are, we are live.”

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