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How is it not what I describe? You just described exactly what I described. Everyone was wondering (both pro-trump and anti-trump) where the "90%" came from. B

How is it not what I describe? You just described exactly what I described. Everyone was wondering (both pro-trump and anti-trump) where the "90%" came from. Because it was pretty clear the race was not that obvious. People keep saying nobody saw it coming, but that's their emotion speaking. People just didn't want Donald Trump to win because they thought he's a joke, but objectively speaking people knew clearly that there were tons of his supporters around the U.S., and it was definitely NOT 90% chance that Hillary would win. To me, THAT's the ultimate "fake news". Slapping a percentage number on it and putting it on the front page is just not right, especially when it's based on very subjective (and eventually false) speculative data.

untog 9y ago
You said: "The front page had this interactive realtime story of how Hillary is supposedly winning" I said: "it absolutely wasn't showing false data that indicated Hillary was winning when she was not" They're pretty clearly contradictory. That data, at no point, showed Hillary "supposedly" anything. You're making my point about readers not understanding statistical probabilities. 90% doesn't mean she's winning. It means she's got a 90% chance of winning, and there is a 10% chance she will lose. She lost. > People keep saying nobody saw it coming, but that's their emotion speaking. Quite the opposite. The data (that same data you're saying came from nowhere) showed that Hillary had a 90% chance of winning. There was variance in the polls, but pretty much all of them showed Hillary with an edge. Yes, there were a great many reports of people saying that there was a lot of Trump support across the country, but those reports are the very opposite of "objective" - they were thinly spread and anecdotal. Pretty much every newspaper ran stories interviewing those Trump supporters, but there was no hard data to quantify it. Polling data isn't "subjective" and "speculative". There is a clearly defined methodology behind it. That methodology was incorrect in the 2016 election, and didn't accurate gauge support for two unprecedentedly unpopular candidates. That makes it "incorrect news", not "fake news". You could argue that the news industry has relied too heavily on this sort of statistical prediction stuff, and I'd agree with you. But in 2012 FiveThirtyEight correctly predicted all but one state, and everyone absolutely lauded Nate Silver for it ("Is Nate Silver a witch?"). But really, what that meant is that each of Nate's predictions were the right side of 50%. And in 2016 they most definitely weren't.
- cocktailpeanuts 9y ago
  I see what you're saying now. But I don't think you got my point either. The detail doesn't matter. Whatever that number was about, it was pretty clear that 90% was not the right number, I'm not even pro-trump and I was confused, imagine what others thought. Also, it is not ok to be irresponsible just because you're using a "scientific method". This is what cigarette companies did to fund research that "prove" that smoking is healthy. And this happens increasingly more, because writing polarizing articles generate more shares and page views and money. Lastly, I am not trying to talk politics here, and it's not even just about NYT. Nowadays for a lot of writers it's all about generating more page views. Again, I'm fine with it (even the "fake news" viral sites), but I was pointing out that it is hypocritical to claim that you're "the truth", when you do things that are biased.
  - hsod 9y ago
    > Whatever that number was about, it was pretty clear that 90% was not the right number Was it? Maybe 90% didn't match up with your intuition, but NYT wasn't making that number up out of whole cloth. That's what the polls were saying, as analyzed by the NYT polling staff. Maybe they were wrong (maybe they weren't-- things that have a 10% chance of happening happen all the time), but you certainly haven't demonstrated, or even really attempted to demonstrate, bias. All you've really said is: * Trump won * Your intuition told you he had a greater than 10% chance of winning before election day > throughout the entire election cycle the narrative was NYT vs. Trump. News organizations and journalists should report stories but should not become the story. It's important to remember that this narrative largely came (and continues to come) from Trump, and he benefited greatly from it.
  - tqi 9y ago
    You seem very confident that "90% was not the right number", and I'm curious how you reached that conclusion. Do you have research that indicates the odds were actually way different, or does it just that it feel incorrect? If I win the lottery, is it misleading for people to state that my odds of winning were one in a million?
    - 9y ago
thinnerlizzy 9y ago
I don't recall the New York Times reporting a 90% chance of victory on election day. I recall her chances according to the Times decreasing several percentage points (down to the high 70s IIRC) during the last few days leading up to the election. If the interactive graphic you are talking about was the 'paths to victory' graphic that I'm thinking of, it probably reflected the most current polling data - which was probably already obsolete - that they had on hand at the moment. My own observation during the days leading up to the election was that her chances of winning were decreasing at a faster rate than could be reported with reliable polling data, though I still believed that she'd eke out a win.
- sp332 9y ago
  http://web.archive.org/web/20161108070757/http://nytimes.com/ http://web.archive.org/web/20161108070757/http://nytimes.com... "Hillary Clinton has an 84% chance of winning"
darkerside 9y ago
> Because it was pretty clear the race was not that obvious. I think that's where the confusion lies. The majority of published polls and pundit calculations pointed that way, and it was earnestly interpreted by well-intentioned journalists that 90% of polls meant 90% probability. Perhaps I'm cutting a little too deep with Hanlon's razor here, but I think systemic biases are a more likely culprit than some kind of media conspiracy.
dragonwriter 9y ago
> Everyone was wondering (both pro-trump and anti-trump) where the "90%" came from No, they weren't, because everyone paying even a little bit of attention to the issues around aggregating polling numbers new that 538 had already dissected the problem with that long before the election—most prediction models were falsely assuming that variations in outcome from.the poll averages between different states were independent events when history shows that such deviations are strongly correlated. Which is why 538, working with essentially the same polling data as everyone else, had Clinton's chance of losing much higher than NYT and some other predictors. > To me, THAT's the ultimate "fake news". Predictions of the future are (and were presented as) analysis, not news. To be "fake news", it has to firsr pretend to be news, that is, reports of things that have occurred.

untog 9y ago

You said: "The front page had this interactive realtime story of how Hillary is supposedly winning" I said: "it absolutely wasn't showing false data that indicated Hillary was winning when she was not" They're pretty clearly contradictory. That data, at no point, showed Hillary "supposedly" anything. You're making my point about readers not understanding statistical probabilities. 90% doesn't mean she's winning. It means she's got a 90% chance of winning, and there is a 10% chance she will lose. She lost. > People keep saying nobody saw it coming, but that's their emotion speaking. Quite the opposite. The data (that same data you're saying came from nowhere) showed that Hillary had a 90% chance of winning. There was variance in the polls, but pretty much all of them showed Hillary with an edge. Yes, there were a great many reports of people saying that there was a lot of Trump support across the country, but those reports are the very opposite of "objective" - they were thinly spread and anecdotal. Pretty much every newspaper ran stories interviewing those Trump supporters, but there was no hard data to quantify it. Polling data isn't "subjective" and "speculative". There is a clearly defined methodology behind it. That methodology was incorrect in the 2016 election, and didn't accurate gauge support for two unprecedentedly unpopular candidates. That makes it "incorrect news", not "fake news". You could argue that the news industry has relied too heavily on this sort of statistical prediction stuff, and I'd agree with you. But in 2012 FiveThirtyEight correctly predicted all but one state, and everyone absolutely lauded Nate Silver for it ("Is Nate Silver a witch?"). But really, what that meant is that each of Nate's predictions were the right side of 50%. And in 2016 they most definitely weren't.

cocktailpeanuts 9y ago
I see what you're saying now. But I don't think you got my point either. The detail doesn't matter. Whatever that number was about, it was pretty clear that 90% was not the right number, I'm not even pro-trump and I was confused, imagine what others thought. Also, it is not ok to be irresponsible just because you're using a "scientific method". This is what cigarette companies did to fund research that "prove" that smoking is healthy. And this happens increasingly more, because writing polarizing articles generate more shares and page views and money. Lastly, I am not trying to talk politics here, and it's not even just about NYT. Nowadays for a lot of writers it's all about generating more page views. Again, I'm fine with it (even the "fake news" viral sites), but I was pointing out that it is hypocritical to claim that you're "the truth", when you do things that are biased.
- hsod 9y ago
  > Whatever that number was about, it was pretty clear that 90% was not the right number Was it? Maybe 90% didn't match up with your intuition, but NYT wasn't making that number up out of whole cloth. That's what the polls were saying, as analyzed by the NYT polling staff. Maybe they were wrong (maybe they weren't-- things that have a 10% chance of happening happen all the time), but you certainly haven't demonstrated, or even really attempted to demonstrate, bias. All you've really said is: * Trump won * Your intuition told you he had a greater than 10% chance of winning before election day > throughout the entire election cycle the narrative was NYT vs. Trump. News organizations and journalists should report stories but should not become the story. It's important to remember that this narrative largely came (and continues to come) from Trump, and he benefited greatly from it.
- tqi 9y ago
  You seem very confident that "90% was not the right number", and I'm curious how you reached that conclusion. Do you have research that indicates the odds were actually way different, or does it just that it feel incorrect? If I win the lottery, is it misleading for people to state that my odds of winning were one in a million?
  - 9y ago

thinnerlizzy 9y ago

I don't recall the New York Times reporting a 90% chance of victory on election day. I recall her chances according to the Times decreasing several percentage points (down to the high 70s IIRC) during the last few days leading up to the election. If the interactive graphic you are talking about was the 'paths to victory' graphic that I'm thinking of, it probably reflected the most current polling data - which was probably already obsolete - that they had on hand at the moment. My own observation during the days leading up to the election was that her chances of winning were decreasing at a faster rate than could be reported with reliable polling data, though I still believed that she'd eke out a win.

sp332 9y ago
http://web.archive.org/web/20161108070757/http://nytimes.com/ http://web.archive.org/web/20161108070757/http://nytimes.com... "Hillary Clinton has an 84% chance of winning"

darkerside 9y ago

> Because it was pretty clear the race was not that obvious. I think that's where the confusion lies. The majority of published polls and pundit calculations pointed that way, and it was earnestly interpreted by well-intentioned journalists that 90% of polls meant 90% probability. Perhaps I'm cutting a little too deep with Hanlon's razor here, but I think systemic biases are a more likely culprit than some kind of media conspiracy.

dragonwriter 9y ago

> Everyone was wondering (both pro-trump and anti-trump) where the "90%" came from No, they weren't, because everyone paying even a little bit of attention to the issues around aggregating polling numbers new that 538 had already dissected the problem with that long before the election—most prediction models were falsely assuming that variations in outcome from.the poll averages between different states were independent events when history shows that such deviations are strongly correlated. Which is why 538, working with essentially the same polling data as everyone else, had Clinton's chance of losing much higher than NYT and some other predictors. > To me, THAT's the ultimate "fake news". Predictions of the future are (and were presented as) analysis, not news. To be "fake news", it has to firsr pretend to be news, that is, reports of things that have occurred.