There's a popular saying that if you're not a liberal at 20, you have no heart, but if you're not a conservative by 40, you have no brain.
It might be more accurate to imagine that people's formative years have large, persistent impacts on their beliefs. A study by Andy Gelman showed how.
In the Gelman model, high presidential approval during a (White) birth cohort's teen years leads them to favor that president's party for the rest of their lives. Whatever the reason, it's as if they're acting to bring back the 'good old days' of their cognizant childhood. To get an idea of how this looks, look at Eisenhower Republicans:
The Eisenhower Republicans were those who missed most of the FDR years and were socialized in ten straight years of Republicans, of which the Eisenhower years had positive spin. As a result, that cohort became very pro-Republican, but then the very pro-Democrat Kennedy and Johnson years moderated them back to being a bit less pro-Republican.
The 1960s Liberals were born a bit later than the Eisenhower Republicans and they got to experience the pro-Kennedy and Johnson years in their formative years, but the next 25 years of strongly pro-Republican sentiment brought them to near-neutrality.
One of the most well-known political generations is the Reagan Conservatives. This generation got to experience strong pro-Republican sentiment and they ushered in the real Reagan Revolution: a cohort with strong pro-Republican leanings and little moderation due to the balance of sentiment between Clinton and Bush II, and Obama's nearly neutral sentiment.
Other cohorts like the New Deal Democrats and Millennials have their own biases that follow from the same dynamics, and if you plot them all together, you get a clear picture of the sentiment of the White electorate:
Now do note, I said Whites. This model works slightly better for non-Southern than for Southern Whites, and compared to those two groups, it works less than half as well for non-White minorities.
In any case, this model based on formative year impacts can explain roughly 90% of the variance in vote choices in the electorate. If you want to get people's votes, get them early in life, and you might be able to hold them through waves of less popular candidates from your own party.
Some of you who are familiar with medicine no doubt do, but if you don't, no worries: This is James Lind, the man most often credited with finding the cure for scurvy.
Scurvy is one of humanity's great historical killers.
It's a gruesome condition that culminates in your life's wounds reappearing on your flesh. If you want a picture, go look it up.
You never hear about it today though, because it's so easy to cure.
This research directly militates against modern blood libel.
If people knew, for example, that Black and White men earned the same amounts on average at the same IQs, they would likely be a lot less convinced by basically-false discrimination narratives blaming Whites.
Add in that the intelligence differences cannot be explained by discrimination—because there *is* measurement invariance—and these sorts of findings are incredibly damning for discrimination-based narratives of racial inequality.
So, said findings must be condemned, proscribed.
The above chart is from the NLSY '79, but it replicates in plenty of other datasets, because it is broadly true.
For example, here are three independent replications:
A lot of the major pieces of civil rights legislation were passed by White elites who were upset at the violence generated by the Great Migration and the riots.
Because of his association with this violence, most people at the time came to dislike MLK.
It's only *after* his death, and with his public beatification that he's come to enjoy a good reputation.
This comic from 1967 is a much better summation of how the public viewed him than what people are generally taught today.
And yes, he was viewed better by Blacks than by Whites.
But remember, at the time, Whites were almost nine-tenths of the population.
Near his death, Whites were maybe one-quarter favorable to MLK, and most of that favorability was weak.
The researcher who put together these numbers was investigated and almost charged with a crime for bringing these numbers to light when she hadn't received permission.
Greater Male Variability rarely makes for an adequate explanation of sex differences in performance.
One exception may be the number of papers published by academics.
If you remove the top 7.5% of men, there's no longer a gap!
The disciplines covered here were ones with relatively equal sex ratios: Education, Nursing & Caring Science, Psychology, Public Health, Sociology, and Social Work.
Because these are stats on professors, this means that if there's greater male variability, it's mostly right-tail
Despite this, the very highest-performing women actually outperformed the very highest-performing men on average, albeit slightly.
The percentiles in this image are for the combined group, so these findings coexist for composition reasons.