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To my knowledge, police "Pursuit Rated" tires are designed primarily for durability and reliability under the severe duty operating conditions law enforcement typically encounter, as described by Bryan.But first, for some context, the Caprice PPV is capable of performance characteristics surpassing exotic supercars from the 80s in just about every category. If you have 30 minutes, the MotorWeek review of these supercars is quite entertaining.On the PPV tire comment, Car and Driver uses their standard 70 MPH to Zero Stop Test (presumably on dry pavement) and recorded the 170' stopping distance; it's a test most others perform from 60 MPH and producing numbers we're more familiar with.Given the power, weight, and high speed requirements of modern pursuit vehicles, cop-rated tires will always be a significant limiting factor, but they really aren't as shabby as it might appear given what's asked of them.Below are some references primarily on police tire testing:Police tire tests on batogovtires.comPolice/Pursuit Tires: The Pursuit of PerformanceMichigan State Police Tire TestsPolice Tire Evaluation

On a general case, Yes.But that is just the face of time. And there is a evolutionary basis for this particular selection.PrefaceMatt Ridley in his book, The Red Queen puts a very good case for why men prefer slim and thin women and not fat and huge one.Thinness as a factor of beauty is a recent invention.During the renaissance, it was quite opposite. Huge fat bulky women were consider more elite than thin skinny one. This was due to the obvious reasoning that the weight of the body defines the financial status of the women. The queen and the royal ladies were having good hygienic food to eat, less to work and hence were healthier and, as it turns out, more huge than, say, the wife of a peasants or farmers who had to work harder and have less hygienic food.Portray of women during the renaissance periodAn add during the early 20th century showing how to add weight if you are skinny.Fashion = BeautyWallis Simpson has a quote saying "A woman can never be too rich or too thin"Fashion changes with time. And, we can know, beauty is subjected to fashion. So indirectly it also changes. Beauty of the women is a moving target. We need not rely only on our own culture for evidence that plump women can be more attractive than thin ones.Robert Smuts of the University of Michigan has argued, thinness was once all too common and was a sign of relative poverty: Nowadays, poverty-induced thinness is confined to the Third World.In the industrialized nations, wealthy women are able to afford a diet low in fat and spend their money on dieting and exercise. Thinness has become what fatness was: a sign of status.Smuts argues that male preferences, keying in on whatever signs of status prevailed, simply switched. They did this presumably by a switch of association.A young man growing up today is bombarded with correlations between thinness and wealth, from thefashion industry in particular. His unconscious mind begins to make the connection during his critical period, and when he is forming his idealized mental preference for a woman, he accordingly makes her slim.Miss Americas falls steadily year after year. So does that of Playboy centerfolds. Both categories of women are 15 percent lighter than the average for their ages. Today thinness defines "healthier food with low fat and calories". That is a costly thing to purchase as compared to other food.PS- My answer is what I read in Matt's book. Most of the wordings are borrowed from the book. Emphasis are mine.

A fair amount. Mostly. With caveats. If you want to know more, bear with me for a lengthy discussion.A lot of people took the wrong lesson from 2016. They assume that 2016 proved that polls are always wrong AND that if they are wrong, they must be wrong in a way that favors Donald Trump. This is not accurate.Polls are wrong sometimes. They were wrong, for example, in 2012; the polling consensus was that Obama would beat Romney, but it would be close; he was expected to win by about 1%. The actual result was that Obama won by 4.5% of the vote; that was an error of 3.5%, which is actually pretty large, but it was an error in the direction of the expected winner, so people did not notice. If the polls had predicted a Romney win by 1%, and Obama won by 2.5%, people would have noticed more that the polls were off, even though the error would have been exactly the same as the one that occurred (3.5%).So this is a key point: it is possible that the polls will be wrong in ways that overstate, rather than understate, Trump’s support. There is no evidence of systematic bias against Republican candidates in polling from one election to the next. The 2012 polls overstated Romney’s support. The 2016 polls understated Trump’s. If they 2020 polls are off, there is no guarantee they will be off in ways that benefit Trump just because that’s what happened last time. In fact, it’s entirely possible that pollsters may be so concerned about repeating their 2016 errors that they will overcompensate in ways that overstate Trump’s support. We won’t know until the election is over.It’s important to understand that polls are statistical samples that are used to project the attitudes or behaviors of large groups of people. A typical poll might have 1000 respondents, that are intended to represent the views of thousands or even millions of people. Through the wonders of statistics, it is possible to do that with a fair degree of accuracy.But not with perfect accuracy. And to be accurate, pollsters have to construct a sample that represents the population they are trying to assess. So if, on election day, 20% of the voters who show up at the polls are under age 30, but your actual polling sample consists of 25% of respondents under 30, then you’ve over-represented that group. This will make your poll less accurate. Building a statistical model that accurately predicts election-day turnout is hard, but it’s vital to creating an accurate poll.So to build an accurate turnout model pollsters look at a combination of recent election turnout and self-reported data from different demographic groups about how likely they are to vote. Then they project what they think the electorate will look like, and (especially once they start applying their likely voter screens) try to build a statistical sample that will look like the electorate on election day.And sometimes they get their turnout models wrong. Sometimes they are a little wrong; sometimes they are more than a little wrong. The greater the difference between actual turnout and the turnout models pollsters were using in the run-up to the election, the less accurate the polls will be.And even when the models are accurate, there’s still a margin of error (MOE) for any poll. A good poll will have a margin of error of around 3%; if you see one with a MOE listed higher than that, it’s not a very good poll. But even at 3%, that means if a poll tells you one candidate is polling at 45%, their actual support could be anywhere from 42% to 48%.So all of this is important to understand. With this information in mind, is it true that the polls were terribly wrong in 2016?Overall, the final polls just before the election were off, but not by as much as people think. Yes, most pollsters showed Clinton winning the election. And yes, there were some polls, most of them a month or more before the election, that showed Clinton with a large lead. But the polling in 2016 was very volatile; at some points polls showed Clinton ahead by as little as 2 points (and remember, that’s +/- 3 points when margin of error is factored in) and at some points her lead was as high as 10 points. And some election “experts” built predictive models based on the polls that projected a greater than 90% chance Clinton would win (one or two rather infamous examples said she had a 98% chance of winning.) Those weren’t polls, though, they were INTERPRETATIONS of polls by supposed experts, saying that based on her lead and historical trends in past elections, she was overwhelmingly likely to win. Those projections were based on bad assumptions.But usually what we see is that polls become more accurate the closer we get to the election. And over the final few weeks, the polls showed the race tightening significantly. Polls are often described as a “snapshot in time,” and that’s accurate; what people need to understand is that, because polls take several days to collect and then a day or two more to tabulate, they are a snapshot from several days ago. So the polls leading up to the election showed Clinton with a 2 to 3 point national lead. So, they got it wrong, right?Well, not nationally, no. Clinton won the national popular vote (which has no actual impact on the outcome) by about 2.5%. So the national polls were pretty close. But because of the electoral college, we need also to rely on state-by-state polling.And this is where some polls really messed up. In particular, polls in three states, Pennsylvania, Wisconsin and Michigan, were pretty far off. I believe there were polls in Wisconsin from a week or two before the election that showed Clinton up by 6 points; she lost it by less than a percentage point. Still, that kind of error is a sign of a bad turnout model. The polls taken in those states did not accurately reflect who was actually going to show up on election day and how they were going to vote. Part of the reason for this was that white, rural turnout was higher in 2016 than it had been in years, while black voter turnout and youth turnout was a little lower than it had been in 2012 or 2008. Part of it was because there was a major new cleavage opening up in the electorate between college educated white voters (who broke for Clinton) and non-college educated white voters (who broke hard for Trump). The pollsters did not consider education to be an important demographic category to weight for because there had never been such a sharp divide between these two groups. So polls in these three states tended to over-represent college-educated white voters while under-representing those without a college degree. That seems to be the main source of the error. More voters without a college degree turned out (historically, less educated voters turn out at lower rates than more-educated voters) than were expected AND they voted in large numbers for Trump.In addition to that, the polling errors in 2016 came from two additional sources: there were an unusually large (compared to the last few elections) number of late-deciding voters, and they broke overwhelmingly for Trump. And, there were a large number of voters who told pollsters they viewed both candidates unfavorably; these also broke by a large margin for Trump. Pollsters did not properly anticipate these developments, and some of them happened too late to capture in polls.Furthermore, people often underestimate just how close 2016 was. Trump lost the national popular vote, and his win in the electoral college was based on VERY narrow popular vote wins in three states (Pennsylvania, Michigan and Wisconsin). Overall, his combined margin in these states was about 77,000 votes, in an election in which around 129,000,000 people voted. When an election is that close, the polls do not have to be off by very much to get it wrong.So do I think the 2020 polls should be trusted? Mostly, yes. And here are some reasons why.First, this race is not like 2016 in many ways. In 2016, both candidates were viewed very unfavorably. In 2020, Trump has significantly higher unfavorable ratings across pretty much every poll than Biden does. This is not a case where a large part of the electorate hates both candidates. To be sure, there ARE people with unfavorable views of both candidates, but where Trump won those voters by a large margin in 2016, current polls show Biden winning voters who view both candidates unfavorably by even larger margins.Second, there are fewer undecided voters in current polls compared to 2016. This means there is less room for a big break in the undecideds toward one candidate at the last minute.Third, most pollsters now weight their samples by education, so they are less likely to over-sample or under-sample based on education again, like they did in 2016.Fourth, unlike the volatility between Trump and Clinton in 2016, where for two weeks Clinton might be up by 7 points and then for two weeks she was only up by two, and then it would shift back again, there has been a lot of stability in the 2020 polls. In polls that showed a head-to-head matchup between Biden and Trump in 2019, Biden had a consistent average lead of 5 to 6 points. Very, very few polls have shown his support fall much lower than that. Since COVID hit in March, Biden’s average lead has grown to around 8 or 9 points. But contrary to the narrative Trump has been trying to tell that he was on course to win until the pandemic, he’s been behind Biden with remarkable consistency and very few large swings in the polling averages for well over a year.Fifth, many polls, and increasingly many aggregated polling averages, are showing Biden with support at 50% or higher. This is true both nationally and in swing-state polls. Clinton NEVER was at 50% in the averages and very, very few polls ever showed her crossing that mark; her ceiling seems to have been around 48%, which is very close to her actual share of the national vote.Here are a number of sources that discuss exactly these and other points:Why Biden’s Polling Lead Is Different From Clinton’s In 2016Here’s Why Joe Biden’s Lead In The Polls Is Stronger Than Hillary Clinton’s WasWhy The 2020 Presidential Election Is Not 2016Believe the Polls This TimeBiden is polling better than Clinton was—and has five times the cash toohttps://www.washingtonpost.com/politics/2020/07/24/nearly-every-swing-state-this-point-bidens-outperforming-obama-clinton/Why Trump is unlikely to pull off an election surprise against Biden like he did with ClintonNow, I said at the start that there are some caveats. And here’s the biggest one: at the time that I am writing this there are over two months to the election; there is still time for the polls to shift in Trump’s favor. I think there are reasons to believe the polls are giving us a better, more accurate view of where the race stands right now than they did in 2016. But it’s not the August polls that matter. I think it’s likely if Trump wins the election, that there will have been polls showing him likely to win, or at least showing the race to be very close, before that happens. I am not, at this time, predicting with any certainty that Trump will lose.And if the polls are wrong, they could be wrong in either direction; they don’t have to be wrong in ways that favor him.