I think wikibooks is a good initiativ to solve this, and could be powerful when combined with a normal wiki.
https://meta.wikimedia.org/wiki/Abstract_Wikipedia
It's more or less Wikipedia but the articles are created using natural language generation on a functional programming base. The main goal is to generate content in any language from a common underlying structure, but one could also try recursive explanations of a given topic in that framework as well.
Case in point, nLab: https://ncatlab.org/nlab/show/HomePage
For instance, https://ncatlab.org/nlab/show/homotopy+type+theory
Although this is partly inevitable because the content is really abstract, I know there are more approachable ways to define “monad” than https://ncatlab.org/nlab/show/monad
There is a project page advocating more accessible technical articles, https://en.wikipedia.org/wiki/Wikipedia:Make_technical_artic...
In some cases technical subjects just require some pretty steep prerequisite knowledge, but where possible it's nice to try to make them as accessible as can be done practically within the space constraint of a few introductory paragraphs. Usually that means trying to aim at least part of any article at approximately "1 level below" the level where students are expected to first encounter the topic in their formal study. (This isn't always accomplished, and feel free to complain on specific pages that fall far short.)
Writing for a extremely diverse audience with diverse needs is a hard problem. And more generally, writing well as a pseudonymous volunteer collective is really hard, and a lot of the volunteers just aren't very good writers. Then some topics are politicized, ...
How much time have you personally spent trying to make technical articles whose subjects you do know about more accessible to newcomers? If anyone reading this discussion has the chance, please try to chip away at this problem, even if it's just contributing to articles about e.g. high school or early undergraduate level topics – many of these are not accessible at the appropriate level. But if you are an expert about some tricky technical topic in e.g. computing or biology or mechanical engineering, go get involved in fixing it up.
Many of the english math entries seem to be written for math students (as in math program students, not students studying math).
I recommend Mathworld. Much much better.
https://math.fandom.com/wiki/Math_Wiki https://encyclopediaofmath.org/wiki/Main_Page
And a few about engineering:
https://engineering.fandom.com/wiki/Engineering_Wiki
Plus a few about computer related topics:
https://dataengineering.wiki/Index
And various languages and frameworks have wikis too, like Python, PHP, WordPress, etc.
So there's definitely some interest in wikis outside of fandom topics. The Wiki listing pages on Wikipedia has at least 30% of the page listing wikis that don't involve a piece of media/fiction:
https://en.wikipedia.org/wiki/List_of_wikis
I suspect the disparity is probably because hobbies and fandoms could mostly only communicate via the internet, and naturally went from fansites and hobby sites to wikis. Meanwhile more academic subjects have an audience who seem to be unsure of the value of these sorts of free resources.
Sadly quite a few wikis still use the service, and haven't gone independent yet.
That is what distinguishes Wikipedia from large language models or Google which'll say they have information on a given topic even if their sources are questionable. The value-add of Wikipedia is curation, and when the quality of one's outputs is a function of one's inputs, it's sometimes better to just not give an output when the input doesn't exist.
Which is, of course, completely ironic. Wikipedia's notability criterion depends heavily on books in some library stack that essentially no one will ever actually check or appearances in other print form that no one will check either.
I've found a couple of minor "folk histories" of things that appear to not have been true after looking at actual books (which may have not been actually accurate either though they seemed plausible).
Wikipedia has its own "Wikipedia Library", which is a system to allow active editors access to high-quality sources. But if it has to be resorting to Sci-Hub or libgen to check sources for Wikipedia, that's also a form of public service.
Sadly that happens, and it happens a lot more than most people realize. It's way too easy to fake a reputation on Wikipedia.
(There's a WP: page about this problem that I think gives it a name, but I can't find it right now.)
Aha, someone else mentioned it in these comments: "citogenesis", and it was indeed Randall Munroe's coining, and the meta page is
https://www.wikiwand.com/en/Wikipedia:List_of_citogenesis_in...
So I feel like Wikipedia's rule don't necessarily make their content any more reliable. It just adds a step if you're looking to push some kind of biased/iffy opinion onto a page.
When I was a kid, I was taught to reject Wikipedia as an academic source. I know I'm not the only one. Part of me wonders if their present moderation is influenced by that.
What ends up happening is people (including academics in published work) still use Wikipedia as a source, but just don't mention it. This is much worse than just citing Wikipedia, because it can lead to "citogenesis", whereby a claim that originated (without evidence) in Wikipedia is then given credibility by being republished elsewhere. Sorting out what happened later is a huge pain, and many examples slip through the cracks.
Overall, Wikipedia should be taken for what it is: a moderately inconsistent tertiary source written by pseudonymous volunteers some of whom are dispassionate world-class experts and others of whom are incompetent amateurs, ideologues, or trolls.
However, what I've found tracking down lots of Wikipedia claims over the years is that Wikipedia is on average no less reliable than many other kinds of sources that are taken more seriously, including paper encyclopedias and peer-reviewed journal articles (and don't get me started on newspaper articles). Every source and author should be carefully evaluated for credibility and read with at least some skepticism.
There are some specialized ones like https://complexityzoo.net/Complexity_Zoo
Folks interested in open collaborative math content may find these interesting: