Statistics As Tool
I know that there are many questions surrounding things like whether or not we live in a complete post truth era, the efficacy of the empirical redpill and our current ability to leverage truth to our benefit. However, over on X I have long argued for some kind of platform that hosts and aggregates many different kinds of “redpilled statistics”.

I feel that in the 2016 era, these kinds of stat postings were a lot more prevalent on X than now, however I think this has begun to change very recently and we are now seeing them appear more again.

I think that the building of repositories of knowledge for both our use and to point people towards to give them empirical proof of certain situations would be useful.

The transformation of truth into a visualization of material reality at a zoomed out level, that both is easy to “see” what is happening/has/will likely happen and provides an enhanced clarity for understanding/developing potential responses to the situation.

Whether this is simply a block of aggregated and sorted statistics or actual mappings of truth-space, while case dependent is an interesting question and a mapped depiction likely is far more powerful in many contexts.

Granularity is also interesting, powerful and enhances our sensing-knowing abilities, but it is possible that there is a trade off with navigation and legibility/absorption.

Also, one very interesting thing with this kind of thing is the circular relationship between people like us and those who have to power to prevent the knowing of truth. We want to know, access and share empirical stats for reasons that those who collect and disseminate them in the first place desperately want to stop/ignore. Many organizations no longer collect or publish certain kinds of data in order to obscure truth and prevent it’s runaway into the minds of the mass. It’s entirely possible that the creation of a successful stats platform to widen awareness of the truth could lead to the closing of the knowledge streams of the data that fuels it, due to its popularity and the uncovering of certain truth.

This is all just something to think about for the future and may even presently already exist.

My actual question/s are though, what statistical truth needs further capture/uncovering and dissemination?

What existing truth that needs wider dissemination could be depicted/visualized for better awareness?
Mason Hall-McCullough
An interactive presentation of racial demographic census data could help to visually demonstrate the "Whites as global minority" argument as well as showing the lack of racial diversity in other nations. Possibly something on a world map but not sure how to represent population size this way. I actually can't find a global dataset of racial demographics even in a table, though I didn't look very hard. I've seen /pol/ infographics but those don't feel very authoritative, I was thinking something more clean that makes an effort to convey unbiased information without any specific call to action.

Some practical challenges related to statistical data in addition to those you already mentioned:
- Attention to detail is critical, because one error if not transparently corrected could be used by detractors to undermine the perceived validity of the entire dataset
- Each nation decides on different racial categories for their census, they will need to be normalized somehow so comparisons can be made between nations while retaining accuracy
- Data will often be outdated or estimated in some cases (find some way to be transparent about this)
- "Mapping" data that measures different variables AND was collected by different groups into a singular dataset is extremely fraught, you basically need to use verbal arguments to connect the studies at this point, which is not as novel or effective. Doing this with demographic data could be workable with a fair amount of manual cleaning because censuses measure similar things. Government organizations can create large datasets for statisticians to explore because they have standardized data collection methods.

Individual studies from scientific papers often have small sample sizes, measure obscure variables, and are contradicted by other studies. I do not find them very persuasive in general. Literature reviews combine many studies, but these usually focus on larger topics to summarize scientific consensus and aren't going to provide anything subversive. It can be appealing to turn to science expecting it to provide a basis for truth as the origin of empiricism, but I think the data that will be most useful to us will come from governments, public projects, or be collected by hand (or script, as it were).

I think this video is a great example of using statistics effectively to demonstrate a point that may surprise many normies (half of Rogan's podcast guests being Jewish). He keeps things simple, strikes a mostly neutral tone, and makes the data publicly available in a spreadsheet.
"13/52" was probably one of the most straightforward examples of easily digestible information, Statistics for Dummies, that was able to strike at the core of decades of Western, particularly American, state propaganda efforts. No surprise then that you'd find it labeled as such. That seems to me to be, at least at the current moment, the fate of any such attempts at the proliferation of "redpilled statistics". 

Nevertheless, people like Ryan Faulk have been doing this type of statistical presentation more or less independently for years, outside of the bounds of state-sanctioned "research" and "academia". See here, or another here:

The video essay format is, like I've said, more easily digestible for wider general consumption today. However, only a select few do it well, and those that do don't have the necessary reach to be very effective because these are all taboo topics that don't have the pope's blessing. That's quite obvious of course, but it's one of the only real hurdles standing in their way. Most people fundamentally understand that there is truth behind what people like Faulk are saying on these topics, which is why both public and private organisations and actors need to be mobilised to not only suppress them, but to outright say that they are lies or something gay like the recent meaningless parrot phrase of "ontologically evil", as was/is the case with things like 13/52.
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Let me alone to recover a little, before I go whence I shall not return
>What statistical truth needs further capture/uncovering and dissemination?

The ineffectiveness of progressive politics on their own terms, as well as in terms of more sensible goals.
More precisely, the Hansonian claim that many institutions are used for social signalling far more than for their nominative purposes can be validated by statistical analysis - and has been, in some cases. This should be used to show that the gynocratic gerontocracy (or whatever term you prefer) is not even remotely as rational as it claims, that there are no adults in the room, that we are paperclipmaximising our way into catastrophe as we speak, and not in some SciFi-eventuality. Counterproposals for governance can and should also be accompanied by statistical arguments, eg of the eugenic kind.

>What existing truth that needs wider dissemination could be depicted/visualized for better awareness?
Beyond the purely mathematical analysis, I would guess that the main metric that should be used for these discussions is money. As visualisation and/or dissemination aims at the statistically illiterate anyway, it would be good to find ways to reduce your arguments down to "the libs are wasting 10 football fields stacked 3 feet high with 100 dollars bills every day on their gender craze". This is dumb, and therefore it works.

There is a tendency of statistics nerds to be purposely naive in the desire to prove the objectivity of their worldview. Sailer's recent Covid-mainstreamism is a good example: He acts (or truly believes, doesn't really matter) as if whatever he gleans from the data is what matters. Vax reduced death, so the vax was good. Covid killed people, so Covid was dangerous. The point is not to find fault in his stats - they are most likely correct. The point is that we can use the same exact data to come to different conclusions. The vax helped lib politics, so the vax was bad. Covid killed olds and fats, so Covid was good. All that is different about this is the underlying metaphysical assumption. A statistical analysis doesn't need to be utilitarian.

I wonder if there's not a niche for a statistical blog that doesn't cuck itself in this regard, but still upholds "scientific integrity", meaning publishing results contrary to one's beliefs. If somebody wants to collaborate on such a project, I would be interested.

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