mtweak

Her father couldn't read so she built a program that mails 3.5 million books to children every month.

That's an amazing contribution to literacy

It's quite a bit more extreme than 20/80. It's also surprising that there is increasing consolidation vs. not.

Have you thought of active fingerprint pollution? Mathematically, find the search term that has the farthest embedding + noise than your current search term. You search for Harley Davidson, a parallel search is done for "3 mo old diapers".

Like another person said: passive fingerprint protection will be limited.

Hi HN, OP here.

There is about a terabyte of XML IRS disclosures behind this number, so it's quite an exercise to derive. A few other interesting stats that explain the stat further:

- "Revenue” is not the same as donations - The the nonprofit dataset includes hospitals, universities, insurers and other tax-exempt businesses. Even patient fees, tuition, and investment income count as this revenue.

- The revenue skew is pretty extreme: $164k is the median, $6.43M is the average

- Scale attracts more scale: The concentration of revenue is increasing over the years

- As you can guess: hospitals and universities are among the largest orgs by revenue.

Definitely a different view of what a nonprofit means!

This is extremely problematic. Much of news is highly syndicated, so what looks like 10 credible sources are actually just 2. I think the best you can aim for is empirical sources: receipts, videos, photo evidence, public disclosures directly at the source. Archiving is ok if disclosed.

I don't think LLMs can discern truth when the majority of news sources are incentivized primarily for views.

I can imagine this useful to 'compress' gigabytes of data onto a 2d canvas quickly. For that, I appreciate the effort.

One thing that would be useful is to read up on Ed Tufte's principles of data visualization. Many graph libraries don't implement basic visualization principles to make they key point clear, easy to see while still keeping the full depth and complexity of data visible.

Hi HN,

After building a greppable dataset form 990 filings (~8.8M filings over 12 years), I've gotten more questions about how much leaders within nonprofits get paid. It turns out that the sector is extremely diverse: hospitals, insurance, grantmaking foundations, and hobby groups. The highest median top pay go to medical professionals rather than CEOs. There were also some interesting patterns across religious affiliation and geographic location of headquarters.

If there’s another way you’d like to see the data sliced, let me know and I’ll see what I can pull.

Mazhar

I'm also wondering if "perfect" and "good enough" are not really as important now vs. when a team of software engineers had to spend sprints implementing features. The rate of iteration is faster now, the rate of regenerating entire code bases is days. We can perhaps over engineer /more/ today than before.

OP here: I visited the dialysis center in Jigjiga last year while doing field work with Amoud Foundation. The CKDu link to fluoride in groundwater was new to me. It seems most water infrastructure programs are scoped to access, not purification grade. Happy to answer questions on the data or the field visit.