[logicalmonster]

> white people...have gotten substantially better loan availability

I've heard this said a lot of times, but this feels more like a slogan than an actual data point to me. Bad statistics are endemic in these sorts of discussions. Is this statistic comparing all Black people to all White people or is this a clear apples-to-apples comparison?

And where do other races like say Asians fit into this here? Apparently, Asians make even more in America than average White people (according to stats I've seen) so do they get better loan terms than White people? And if they do, is it because of their race, or because they make more money? If racism exists, is it affecting Asians in the same way? And if not, why not?

I'm not going to completely dismiss your comment and I want everybody to do well, but I think it merits a much deeper investigation for full understanding.

[WorldMaker]

There's 107 primary sources at the bottom of the linked Wikipedia page alone if you wanted to do the research towards a "full understanding".

[taxyz]

I am not commenting on anything to do with the discussion at hand, purely just commenting on Wikipedia and the idea of "primary sources."

Wikipedia articles are not really vetted by any authority nor are the sources. Anyone can simply add citations to claims; there are no standards for what constitutes a valid source other than a URL exists to some resource.

You can even take a benign article about something that is not political and start clicking through the sources and realize a lot of them don't support the claim they were cited to support on Wikipedia. In my experience, its less than half the sources I've clicked on are credible and support the claim but this is anecdotal. A lot of Wikipedia is editing by people with ulterior motives now that its so often presented and received as fact.

[WorldMaker]

So? That's how research/research culture works. People mock the [Citation Needed] culture on Wikipedia but it is still far better than "no sources presented". Wikipedia knows that it can't be "objective" so long as it is edited by people with "ulterior motives" and the usual other biasing faults of being merely human. The tools that Wikipedia has to counter that are requiring sources to be cited so that future editors have tools to dispute the claims and by doing that in large aggregate policy they hope to "trend better" over time.

I point out the primary sources part of Wikipedia especially because I very much understand Wikipedia is edited by humans with all their quirks and faults and it is worth not just starting at Wikipedia, but also all that "boring footnotes part" at the bottom of almost every Wikipedia page. Even if it has the same problems as the rest of the data in Wikipedia, it's still so much more information beyond the top-paragraph summary which is all many people ever read of Wikipedia. But critically, that's the part of Wikipedia that most embodies the "Reading Rainbow spirit" of "but you don't have to take my word for it". That's where Wikipedia itself reminds you that it isn't the final word on a subject, but the first word, the summarizing word on it, and points you to other places to explore.

Even if "less than half the sources are credible", a .490 can be a startlingly good batting average, depending on if you are talking Baseball or Cricket. In this specific case 50% of 107 is still a chance at maybe 54 good and worthwhile and credible supporting claims. That's still 54 different places more to start your own research with than you had before you got to the Wikipedia page. Even though anyone can add citations to claims, it's still far more organized than "let me google that for you" because it's still likely human curated and not just whatever SEO has made the machine algorithms happy this day. It's still a good suggestion to start there with those sources. If you are arguing that you maybe shouldn't stop there, then absolutely, I agree, but the above poster was asking where to start, and the poster above that gave them one place to start with 107 leads of further places to start. I thought that was a useful reminder, regardless of what you think the overall batting average of Wikipedia is.

[logicalmonster]

It's easy to hand-wave the discussion away by citing a bunch of links, but taking a gander over that Wikipedia page seems to verify much of what I stated about bad statistics. Much of what's mentioned is comparing the median of giant groups rather than making an apples to apples comparison.

That's the same bad statistical approach that lets activists claim that women make a fraction of what men make: they compare the incomes of all women to all men rather than taking into account individual choices, education, career fields, etc. When you do a good comparison (comparing women with equivalent careers, education, ages, etc to men) the wage gap between men and women is blurred.

For this question about Black loans, all I'm interested in is an apples to apples comparison. Compare loan rates of Black people in X career with X education making $XXX with XXX+ credit scores to the White, Latino, and Asian equivalent. That's the better approach to see if bias exists. Does that study exist? You tell me because I'd be interested in it.

[WorldMaker]

It's easy to claim no evidence exists if you get to be really picky about which evidence you will accept. Sociologists don't get clean room labs and from scratch experimental design for their studies and have to work with the available data.

That "perfect" study you are looking for in fact can't quite exist because you can't control for all variables with respect to any systemic issue and variables like career and education are likely too deeply connected co-factors with housing.

It doesn't sound like you have any interest in being convinced, and it sounds like you are happy being a contrarian here.

[logicalmonster]

> It's easy to claim no evidence exists if you get to be really picky about which evidence you will accept.

It's easy to claim all of the evidence in the world exists when you're willing to accept very bad statistics and interpretations.

See how that works?

I'm very simply asking for something other than very obvious bad statistics or bad statistical interpretations. I think this is very important because bad stats or interpretations can cause bad policy decisions.

> Sociologists don't get clean room labs and from scratch experimental design for their studies and have to work with the available data.

Are you saying that this data can't exist, or can't even be attempted to be found? No sociologist has thought to even attempt to come up with a sample of this data to try and analyze this correctly? If this is the case, why?

> That "perfect" study you are looking for in fact can't quite exist because you can't control for all variables with respect to any systemic issue and variables like career and education are likely too deeply connected co-factors with housing.

Hold your horses, buddy. I'm not looking for some fictional "perfect" study. Every study, whether in physics or sociology, probably has flaws. I'm not looking for perfection, I'm looking for an honest attempt to at least make a good statistical comparison.

> It doesn't sound like you have any interest in being convinced, and it sounds like you are happy being a contrarian here.

Mind-reading isn't a thing, but I'm generally a happy person, thank you.