LetsGoGameCrocks

LetsGoGameCrocks t1_iwm2ugj wrote

Yes. A state with 100 violent crimes and 1000 innocent people unrelatedly shot by by police is the exact same as a state with 1 violent crime and 10 innocent people shot in this dataset. 990 innocent people shot completely ignored by this irrelevant normalization.

This is a misleading analysis

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LetsGoGameCrocks t1_iwlxldh wrote

But you’re regularizing on something irrelevant. Your data views a state where 1000 innocent people are shot and 100 violent crimes occur the exact same as a state where 10 innocent people are shot and 1 violent crime happens. Those are the same data point in your set. Do you not see how insane that is? 990 more innocents killed in the first state, completely ignored because there’s more violent crimes?

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LetsGoGameCrocks t1_iwlsakf wrote

It has literally everything to do with it? The assertion that more training = less shootings is only relevant because there have been many high profile incidents of cops shooting nonviolent individuals. You’re literally exempting all of these high profile - relevant - examples from your analysis.

An analogy:

Person A presents a graph showing that more driving training correlates to safer driving. This is pretty obvious because trained drivers are more prepared to drive under less than ideal circumstances like traffic, rain, etc.

Person B (you) presents a graph showing that in clear weather with no traffic, additional driving instruction doesn’t have much correlation with safer driving. This is obviously true, but erroneously presenting it as evidence that training has no correlation with safety is misleading.

Under ideal circumstances the training doesn’t matter as much. What society cares about is the fringe cases where training actually matters. You’re completely ignoring the important cases and trying to present the boring obvious leftovers as if they’re important.

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