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 →

Saar Golde no published score: only 1 usable exchange 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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1exchanges match
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Answered raw tape D 4 · C 5 · P 4 · Cm 4 4.30

Q I'm actually curious, just for my own benefit, how big is the company, like how many people do you have, like how many people do you have on your team to do this, which sounds quite complex?

A So to do this, ah, so we actually have three different data science teams. Uh, we have the, the, the team that does the routing algorithm, the real-time, that solves the real-time problem, and the data scientists also, the analysts measure stuff with them. Uh, they're about, I think, I don't know, between eight and 10, it's growing really fast. Uh, we have two other data science teams, one to do the operational side, which is kind of what I showed here, which, uh, right now is about four and a half people. And, ah, one to do, ah, basically to do the growth. So, ah, getting more people to use VIA, getting people to use VIA to do more. Ah, so that team is about eight people, about half of them are, could be called data scientists.

AI assessment note: “So to do this, ah, so we actually have three different data science teams.”

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