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 →

Nick Sinai 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.

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Answered raw tape D 5 · C 5 · P 4 · Cm 4 4.60

Q so this, this interesting paradox in that the, the, there's been this, uh, just incredibly innovative policy that has been, uh, you know, put to, to existence over the, the last, uh, few years, and, and people, including in the startup world, don't know that much about it. So, Could you just, like, do the sort of, you know, the one-on-one version from data.gov to the Data Act of 2014?

A Yeah, so, uh, the, the first, first day in office, the president signed a memorandum around open government and transparency, and it led to the, to the creation of data.gov, and it required federal agencies for the first time to register some of their data assets and make them available to the world, um, and that led to a series of open data initiatives Across a number of vertical areas in health, energy, education, public safety, global development, where we actually started to think about building an ecosystem. That is not just how do we open up data and make it a little bit more liquid or useful, but also how do you engage entrepreneurs, innovators, scientists, journalists, users of the data, and actually try and increase those feedback loops. In 2013, the president signed, ah, um, an executive order making open and machine readable the new default for government information. And requiring agencies to start managing data as an asset. So think about it, ah, we inventory battleships, we inventory people, and we inventory desks and desk chairs, ah, but we weren't really inventorying data, and we weren't thinking about data throughout, through the strategic, ah, life cycle, right? And so, if you're talking about open data just at, at time of dissemination, you're probably doing a disservice, right? And you're probably only focused on a few or narrow sets of information, maybe on…

AI assessment note: “led to the creation of data.gov, and it required federal agencies for the first time”

Answered raw tape D 5 · C 5 · P 4 · Cm 4 4.60

Q tremendous progress around building, uh, a, a developer ecosystem and getting the data in the hands of the, you know, the us geeks. Um, what about, uh, making sure that that data Becomes a part of all those consumer websites. For example, if I go to Yelp, why do I not have the, you know, the latest sanitation department information? Is that a federal versus state versus local type issue?

A Yeah, so I think you actually do see a ton of federal data, as well as state and local data, in a lot of the consumer, consumer properties. So I'll give you a couple examples. If you, if you use a major search platform, Um, Google, or Bing, or, or others, and I guess a major search platform, um, and you put in a drug name, uh, you'll see in the knowledge box, or knowledge panel, or something like that, you'll see a bunch of information, and sourced will be the FDA, or HHS, or the Institute of, of, of Medicine. If you're looking for real estate in, in Zillow, or Trulia, or any of, any of these real estate sites, there's actually a ton of, of not just local data, But federal, uh, data from, um, a variety of statistical agencies, Federal Reserve, a whole bunch of places that, that actually power that. And so, uh, in, in, in the particular example in Yelp, I think, uh, they've done a great job of being a market maker from a standards perspective of saying, hey, if we can encourage people to standardize on health grade, then we can actually post that for restaurants.

AI assessment note: “you actually do see a ton of federal data, as well as state and local data”

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