I was trying to devise some strategy. For example, suppose the underlying reality has the equal number of “green” and “blue” facts, but the “green” facts are reported with probability 100%, and the “blue” facts with probability 33%. If you only read one Green newspaper, you can’t find out the truth. But reading three independent Green newspapers could give you some clue—the “green” facts are reported in all of them, the “blue” facts only in some of them. This would suggest that something is going on… even without reading any non-Green sources!
But the problem is that this toy model does not reflect reality. No one reports 100% of facts in line with their narrative. Facts are many, pages are scarce, you select the important things (among those that are in line with your narrative). Like, you cover presidential elections, and mostly ignore people who save kittens. So, using my strategy above, a suspicious reader would conclude that the suppressed Blue politics are about saving kittens, because that’s what the Green newspapers don’t synchronize about.
Similarly, the differences between various Green newspapers could be e.g. regional. Both Washington Green and New York Green would report about presidential elections, but the former would also mention less important things happening in Washington, and the latter would mention less important things happening in New York.
On the other hand, there would be some natural synchronization about which “blue” facts are allowed to be reported. The ones that are least dangerous to the narrative, of course! Giving a voice to the selected weakest Blue points (or the strawman versions thereof) could be perceived as extra virtuous, while minimizing risk that readers start taking those points seriously. And the reader who tries to be extra charitable to the other side could end up trying to defend the strawmen.
At the end, it seems I was trying to extract signal from noise. Perhaps this is impossible. Unlike in simple mathematical models, you usually don’t know the filtering algorithm, and it doesn’t even have to be consistent. So the suspicion (even one supported by evidence) that you are being manipulated, does not help you undo the manipulation. You are likely to undershoot, you are likely to overshoot, you are likely to shoot in a completely wrong direction. You can’t revert noise.
In the logic where blue politics is about kittens you need to assume that non-green political things are blue. If the yellow news paper is spotty about dog saving does it make it a green or blue politics?
I was trying to devise some strategy. For example, suppose the underlying reality has the equal number of “green” and “blue” facts, but the “green” facts are reported with probability 100%, and the “blue” facts with probability 33%. If you only read one Green newspaper, you can’t find out the truth. But reading three independent Green newspapers could give you some clue—the “green” facts are reported in all of them, the “blue” facts only in some of them. This would suggest that something is going on… even without reading any non-Green sources!
But the problem is that this toy model does not reflect reality. No one reports 100% of facts in line with their narrative. Facts are many, pages are scarce, you select the important things (among those that are in line with your narrative). Like, you cover presidential elections, and mostly ignore people who save kittens. So, using my strategy above, a suspicious reader would conclude that the suppressed Blue politics are about saving kittens, because that’s what the Green newspapers don’t synchronize about.
Similarly, the differences between various Green newspapers could be e.g. regional. Both Washington Green and New York Green would report about presidential elections, but the former would also mention less important things happening in Washington, and the latter would mention less important things happening in New York.
On the other hand, there would be some natural synchronization about which “blue” facts are allowed to be reported. The ones that are least dangerous to the narrative, of course! Giving a voice to the selected weakest Blue points (or the strawman versions thereof) could be perceived as extra virtuous, while minimizing risk that readers start taking those points seriously. And the reader who tries to be extra charitable to the other side could end up trying to defend the strawmen.
At the end, it seems I was trying to extract signal from noise. Perhaps this is impossible. Unlike in simple mathematical models, you usually don’t know the filtering algorithm, and it doesn’t even have to be consistent. So the suspicion (even one supported by evidence) that you are being manipulated, does not help you undo the manipulation. You are likely to undershoot, you are likely to overshoot, you are likely to shoot in a completely wrong direction. You can’t revert noise.
In the logic where blue politics is about kittens you need to assume that non-green political things are blue. If the yellow news paper is spotty about dog saving does it make it a green or blue politics?