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 →

Nanjira Sambuli no published score: only 2 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.

clear all ✕
2exchanges match
2on raw tape
0redirected or not addressed
Answered raw tape D 4 · C 4 · P 4 · Cm 4 4.00

Q So that's actually really interesting. Um, do you have some of those statistics or a little, can you give us a little bit more flavor about what that looks like?

A Right. So what we found, and it's really mostly studies that we do, user experience studies, just better understanding the target user for any, a mobile phone application or service, is that, you know, these are very, um, and especially in a country like Kenya, and I'll use Kenya as an example here, is, um, much famed for elements like M-Pesa, but there are other cultural factors that also have been hindrances to that last mile connectivity. So you'll find, for instance, it would be traditionally that, um, women may not have access to a mobile phone because of how structures of, Property ownership exists, uh, beyond, you know, or predating, uh, technology. And so how do you overcome those? Um, and if that lady cannot own a phone at home, maybe she can access the same services she needs on the internet via a center she can go to during the day when nobody's bothering her. We don't know who's holding what to your head when you're accessing a mobile phone.

AI assessment note: “I'll use Kenya as an example here... women may not have access to a mobile phone”

Answered raw tape D 4 · C 3 · P 3 · Cm 3 3.30

Q So that's actually really interesting. Um, do you have some of those statistics or a little, can you give us a little bit more flavor about what that looks like?

A Right. So what we found, and it's really mostly studies that we do, user experience studies, just better understanding the target user for any, a mobile phone application or service, is that, you know, these are very, um, and especially in a country like Kenya, and I'll use Kenya as an example here, is, um, much famed for elements like M-Pesa, but there are other cultural factors that also have been hindrances to that last mile connectivity. So you'll find, for instance, it would be traditionally that, um, women may not have access to a mobile phone because of how structures of, Property ownership exists, uh, beyond, you know, or predating, uh, technology. And so how do you overcome those? Um, and if that lady cannot own a phone at home, maybe she can access the same services she needs on the internet via a center she can go to during the day when nobody's bothering her. We don't know who's holding what to your head when you're accessing a mobile phone.

AI assessment note: “I'll use Kenya as an example here”

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