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 →

Andrew Huberman 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.

clear all ✕
1exchanges match
1on raw tape
0redirected or not addressed
Partly raw tape D 3 · C 4 · P 4 · Cm 3 3.55

Q going forward? Because we saw this with, uh, GLP ones. I mean, I'm sure, or CRISPR, these stuff, this stuff was NIH funded at one point. There was a ton of research, and then we get this big boom, like, but it's 10 years later. What's on the frontier? What are you most excited about? And what should we be fighting for? Let's keep the funding there no matter what.

A Yeah. Great, great question. Uh, in fact, the most important question. So regardless of whether or not this 40% cut happens, if it's less, if it's kept the same, um, a couple of things. First of all, despite the fact that NIH funds basic research and that many laboratories, including my own for, for many years, focused on basic research, like how does the visual system work? We always had an eye. Every laboratory has an eye toward, you know, what, what the translational implications could be. Okay. So we were actively involved in trying to solve You know, blindness due to glaucoma, even though we were focusing on some basic questions. So I think it, it, it's a statistical issue. If you step back and you say, okay, in the field of, let's just say vision, my, my former field, um, what is the leading cause of blindness? Cataract. But you know what? You can fix cataract. You can slide out the lens and you put in a new lens that's being done now.

AI assessment note: “actively involved in trying to solve You know, blindness due to glaucoma”

page 1
Made with StarZero

Turn any episode into a week of clips.

This entire site, over 500 episodes transcribed, diarized, checked and made playable, runs on the StarZero media pipeline. Drop in your own episode and the podcast clipper finds the moments worth sharing, cuts them, captions them, and reframes them for every feed.