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Laporkan kesalahan penerjemahan
Take not that the article title is entirely misleading, verging on inflammatory reporting of something the actual study does not say....
First, the pertinent exerpt from the actual working paper, which I assume you must have read before offering it as supporting evidence:
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3627809
Basically, officers will, 35'ish% of the time, report a lesser violation for speeders, giving them a discount on how much of a fine they will owe. This deviates when it comes to minority drivers, with controls (mentioned elsewhere) inserted due to minority drivers usually driving at higher speeds over the speed limit than white drivers, at around "2pp" which is two percentage points.
Two percentage points difference in real-world data results.
(That is, I must note, in the face of the admitted fact that minority drivers are more likely to be going more over the speed limit than non-minority drivers. Gosh, what does that mean? They're much more likely to give minority speeders going significantly over the speed limit a discount?)
The standard for confidence levels in significance ranges from 3% to 5%, with some requirement for even 1.5% and, in some disciplines where mechanisms are a bit more nebulous but are results-oriented, like medicine, the range can be as lenient as %20. If a patient's life is at stake, a failure rate of a medicine at %20 is acceptaible, just so long as the failure does not include an explosion.
A 2% variance is well within potential simple error reporting. That reported variance is NOT "%40" which would be very significant. The %40 comes from a source that is not real-world data, but a controlled model... That model, as they later note, makes some assumptions. But, their conclusion doesn't caution those assumptions, does it?
Now, I will ask you to review section 7.2.1. Why review instead of quote? First, the link can't be truncated. Second, it's a large section that I think you need to read in its entirety in order to understand what they are doing - Attempting to control for errors and potential problems by creating a "model" to then measure... That part is important as it is what they then use to base their conclusion on.
That's right.
As it stands, the direct differences in actual data collected imply a bias towards giving minorities a higher fine margin than others of 2% out of the general %36 or so of all drivers given a discount. (As I understand the study and as the quote suggests.)
They then... create a model to attempt to correct for... stuffs. They insert a lot of things that they are "correcting for" including throwing out data and even then creating new data, using their construct, to apply to the existing data. Remember - They already have the actual data of assigned tickets and their assumption, an assumption mind you, that the clustering of reported violations around the number "9" miles per hour fine limits is indicative of an officer giving the driver a discount. That's not due to testimony, that's due to an assumption by the researchers. (Not necessarily invalid, but I do not see it directly controlled for here. I guess that's in another cite. I wonder - Did they actually examine the road where suspected tickets were given? Did they control for that? Cops might not give a ticket for drivers going down a steep hill...)
No kidding.
The raw data collected from real tickets cited with standard controls for error estimates the "real world" value of 2% variance.
But, their "model" estimates differentlywise...
Yeah. This isn't "evidence" of reality. It's evidence that the data can get you what you wish to report after you throw out or control for significant data that you believe may be too heavily biased or the result of outliers, like attributiing qualitative differences of reporting officers with no controls set for that bias...
Heckin' win, man. Great cite of a "working paper."
I wonder why they didn't cite just a 2% ticket variance in discounts, instead? I guess that number wasn't big enough. So, they isolated 40% of the officers and made a model to show they are heavily biased. GG
PS: If there are formatting issues, I apologize. I was quoting from pdf and trying to give you refs.
PPS: Edit-Add - It's a serious thing to suggest someone massaged the data. I will remove that bit. But, I must draw attention to the fact that the data has had a lot of manipulation. I do not agree that all that manipulation was warranted and I wonder at the true aim of this study and whether or not it found exactly, and only, what it was looking for.
Ah... the traditional spammings of teh proofs... Thank goodness for Google, eh?
Look:
I, of course, acknowledge there is and can be bias and of course there can be "bad cops." I am not saying that's not true.
I am saying that making statements of "All Cops Are Bartards" and things like "1 in 20 are good cops" are not truly informed and reasonable statements to make. They are not sensible statements to base some kind of reformist, extreme, "movement" on.
No one is going to attempt to do harm to another person if everyone in the surrounding area had a firearm and knew how to use it properly and safely.... There will be way less ♥♥♥♥♥♥ predators if any.....
Which is why I don't understand why feminists are against guns
"Millions" of bad cop moments. You certainly enjoy overstating things, don't you?
I posted some good cop moments. You can find many, many, more. But, you don't look for those, do you? And, that's why you don't see them using your Youtube research.
EXACTLY!
They make good money posting those videos, right? So do "game journalists" that only post crticisms about games, right? So do "reaction video" derps like Asmongold, right?
So, you judge validity based on how much money someone makes from presenting you with your "data," huh? Do you work for the tobacco industry?
I didn't post it as proof of anything. I posted it as a farcical example of what some people, including you, appear to be evidence to support their own beliefs and opinions. You probably should have read what I posted with those videos, too.
I'm running out of points to award.
There ya go. :)
Good cops don't exist as long as the "thin blue line" ♥♥♥♥♥♥♥♥ continues. Systematically, whenever a cop crosses the thin blue line and reports another officer for abusing their power, they are either bullied/harassed until they quit, they get fired for ANY minor infraction in retaliation, or in one case, sent to a mental institution under false pretenses (look up Adrian Schoolcraft).
All that leaves are bad cops and complicit cops, who do/say nothing in the face of other officers abusing their power. ACAB because there is no such thing as a "Good Cop". Sure, some of them might think of themself as a good cop, but if they really were, they wouldn't be able to keep their job.
Nah. BLM was just repeating what previous generations already knew.
The US police force was grandfathered in from old KKK officers. It's an undeucated, under qualified gang if thugs.
The only way to repair it is complete reform. "Defund" doesn't work because it needs funding to be properly trained, and "backing the blue" is pure bootlicking (truly, if you have a thin-blue-line license plate/sticker/t-shirt, you admit to full time boot slobbering)