Most essays on survivorship bias begin with the story of Abraham Wald, a statistician working for the US military in World War 2; and this one will not deviate from that tradition.
Too many planes were being shot down by the Germans, and the Allies had to armor their bombers to make them more resistant. The top brass looked at the battle damage on the surviving planes, and proposed putting armor on the areas hit by enemy bullets. All wrong, said Wald; wrong because these planes were the survivors, the ones who returned home. Instead, he proposed that the air force should armor the areas that were not hit, because bullets striking these areas must have brought the non-surviving planes down. In sum, the top brass had focused only on an unrepresentative part of the data before them (the surviving planes), distorting their perceptions of the problem and its solution. Wald prevailed, the armor went on the unscathed areas, and far more planes began returning to base.
Despite Wald's victory, survivorship bias is still rampant in the media, in business, even scientific research. Research findings that are not statistically significant are usually resigned to the filing cabinet and forgotten, distorting the overall picture of a given topic; because significant findings might be unrepresentative products of pure chance, in relation to the total (mostly hidden) sample. Business people and investors write books about the 'laws' of financial success, conveniently forgetting all those who tried exactly the same methods without a positive result.
In medicine, we continually have to struggle against 'anecdotal' survivorship bias. Patients often resist their doctor's advice to stop smoking because "Grandpa Joe smoked 200 cigarettes a day and lived to 96!" What these patients fail to grasp is that Grandpa Joe was a memorable surviving outlier; and that it would be far wiser to consider the 30% who died prematurely of smoking related illnesses, rather than Grandpa Joe (0.001% of the total sample, if that).
Survivorship bias seems especially strong among among low IQ or uneducated people, partly because they cannot think objectively. This is why the lower classes are far more likely to play lotteries and games of pure luck than the educated classes.
In sum, survivorship bias is a fascinating concept and once it is pointed out, one starts seeing it everywhere.
But what has it got to do with the Blue Pill, Anglo-American feminism, and all the other things that interest us?
Plenty. In fact, survivorship bias is the key cognitive error underlying Blue Pilled thought.
This is because the Blue Pill fixates on self-reportage, and on narratives derived from unrepresentative social samples. The Anglo-American media continually regales us with tales about some one-legged ethnic tramp attracting a fashion model, precisely because it is so contrary to our experience. He is the one 'survivor' out of millions of low-value incel men who got nowhere; but since the millions had no interesting story to tell the media, their sexless lives got shelved and were conveniently forgotten.
It is interesting that the Manosphere emerged as the mainstream media crumbled before the advance of social media, in the late noughties. While this is partly because social media facilitates the rise of international dissident movements, it is also because the mainstream media can no longer project its reflexive survivorship bias on the masses. As we know, this has stimulated more realistic views about ethnicity, looks, economics, and many other things. Only Boomers, SiGens, and the lower classes still accept the mainstream twentieth century narratives, on any major issue. And all those narratives were (and are) underpinned by massive dollops of survivorship bias.
In fact, the Red Pill also presents a sexual narrative heavily larded with survivorship bias. PUAs continually present us with one-eyed cripples who used 'Game' to get girlfriends, as if they were in any way representative of the total PUA sample who ended up with nothing. When Red Pilled men started to realize they were members of the representative 99%, not the unrepresentative 1%, the Red Pill rapidly yielded to the Black Pill.
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This leads me to one final observation about survivorship bias. Although surviving outliers do exist, the mainstream media or Blue/Red Pill commentators usually omit the fact that they are often highly unrepresentative in other ways. For example, while Bill Gates and Steve Jobs both dropped out of college to start successful tech businesses, they both came from upper-middle class backgrounds and were endowed with very high IQs. Many popular entertainers hail from hyper-privileged backgrounds, even in such 'rebellious' fields as pop music, acting or comedy (Robin Williams, Humphrey Bogart, Kit Harington, Jake Gyllenhaal, Salma Hayek and Taylor Swift, spring to mind). This is not mere 'sour grapes', as the English say: these celebrities probably have better genes than most people, quite aside from their socioeconomic advantages. The mainstream media could once conceal this unstated reality, of course; but now the facts are just a Google search away.
So when Red Pilled PUAs tell us about one-eyed Indians in wheelchairs snagging cheerleaders with 'Game' techniques, don't be surprised if said outlying Indians are also about to inherit fortunes, patent royalty rights, or some other valuable resource the cheerleader can exploit (of course, the PUAs will never tell us about these 'additional' outlying traits, because that would deface their weary 'personality is all' narrative).
I'll sign off by saying: look at the big picture if you want valid information. And the big picture usually looks very different from the one presented by Blue Pilled clowns.
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| The MSM's improbable norms are testament to rampant Survivorship Bias |
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