"The fees the federal government charges for court documents are significant. PACER charges users $0.10 for every page users search and access, and $30 per name

"The fees the federal government charges for court documents are significant. PACER charges users $0.10 for every page users search and access, and $30 per name or item searched plus $0.10 per page per document per month, albeit with a max of $3 per individual document." It's funny how these numbers sound very reasonable on their face, especially if used for human review. But if you consider programmatic searches, 10 cents per page is a lot. Consider the CPU cost of cycling through each pdf, assume 1000 letters, that's 1Khz which is like a billionth of a cent, in terms of electricity and hardware ammortization. I'd bet that this incentivizes a 'hoarding' and reuse of information, rather than a "query when necessary" practice, which would in fact give place to monopolies like OP argues. A newcomer legal analysis company would have to pay, say 200$ for research from their first customer. If they save those documents, then it is unlikely that their second customer will benefit from those documents. However huge firms would make a business out of the byproduct of searches, they spend 200$ on documents, and they serve a client, but they add those documents to their own internal database, which of course has costs much lower than the nominal fees stipulated by the federal steward (PACER). An argument could be that you can't eliminate the fees because there's costs that need to be paid. But isn't that what taxes are typically for? Especially corporate income tax. The costs are probably a nominal fee to avoid overbearing systems, similar to franchise taxes and incorporation clerical fees. I don't think the idea of charging for documents is bad, who said that the system would need to be adopted for huge data hungry systems, I'm all for giving human analysis an advantage instead of adapting systems to play into the data munching AI fad. I'd rather see balancing that rewards human analysis rather than bringing data munching to the masses.