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[–] flyawayhigh 0 points 1 point 1 point (+1|-0) ago
You can quantify a bias. You can also spin a quantification of a bias. Then, you can use metarules to calculate the amount of spin in a bias quantification. I think bias is within a range determinable.
Since you chose me to be a mod here, I must say that censorship is not an issue here Not a chance. Forget it.
As a member of the community, I would and do discourage, hopefully with good arguments and moral authority, what I see as the excessive proliferation of partisan spam. People may agree or disagree, but each submitter ultimately decides.
If there is any censorship going on, its the repetitive eleven-figure funded Republican spin machine pushing anyone who disagrees so far down the web that they become hard to find.
I'm gonna try a little experiment. Check the NEW section in a few minutes. :D
[–] [deleted] 0 points 2 points 2 points (+2|-0) ago
[–] flyawayhigh ago (edited ago)
I sort of figured that. As I always say, v/politics will never become limited to partisan views if I have a say (which isn't to say it can't be filled by them, but not by censorship, and not exclusively).
To quantify a bias, use statistical methods. Take the relatively easy case of exit-polling, for example. If election results do not match poll results, there is a bias. To determine the skew, you need to step back and compare the demographics of the population to the sample, or check the quality of the vote count.
If you have a complete vote count and it has been verified accurate through methods used, then you can say with near perfect certainty that the bias is in the exit polling.
If you do not have a complete vote count or there is difficulty validating it, as when there is no paper trail or the counting code is proprietary, then you have no standard.
If you look at the demographics of the exit poll sample, and make sure that random methods were used to select them, then you can say, based on the numbers, with determinable certainty, how likely the sample is to be accurate and within what range.
You know this because over time, these statistical rules have been created out of ever-growing test verified test data.
Of course, here, you can look at the smaller pieces to see if they fit, or find that they don't fit.
If you find no problems with the sample or other discovered forms of bias, and you cannot verifiy the vote count, then you can safely say that the election was rigged and with confidence how rigged it was.
Why? Because a fully verified proper vote count and the related exit poll has never varied more than one-half of one percent where the numbers were large enough to produce legitimate statistical results.
And this is an easy example! As you can see, it can get quite crazy with details.
Statistics are used to mislead all the time, too. We can look for that bias too.
Take the unemployment figures. They are in single digits. But if you simply divide the employment workforce by the non-disabled working-age population you can immediately see that the official unemployment stats grossly underrate unemployment. You can then next look for the specific bias and you'll find it right there in the sample selection rules plain as day!