For any, like myself, wondering "Who is Ben Welsh" ?
Hello. My name is Ben Welsh. I'm an Iowan living in New York City.
I am a reporter, an editor and a computer programmer. My job is to use those skills, together, to find and tell stories.
I work at Reuters, the world's largest multimedia news provider, where I founded the organization's News Applications Desk. In that role, I lead the development of dashboards, databases and automated systems that benefit clients, inform readers, empower reporters and serve the public interest.
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At a guess (my Telepathy/IP is weak today, I'm not reading dang at usual strength) .. the initially submitted title was "invented" for submission and didn't match the content title.
HN veers toward "the guts of the content w/out decoration" - limited additional information, framing, weasel words, perceived slanting, etc.
It's uncommon to name an author unless the author themself is an important part of "the story".
I personally have no issue with the original title, however it's not really for me (non US citizen) to judge whether the reporter in question has a name / identity that carries weight in US IT circles.
I don’t really know much about it, but remember it as being _fantastic_ journalism every time I encountered one of their articles. As a bonus, great infographics and interactive data visualizations.
Unfortunately most of the most important visualizations are broken in the archived version. Including the gun deaths visualization and I think the P-hacking interactive
It's kinda sad to know no one else will get to experience those interactive visualizations. Though its nice to see the approval comparison page still works
Curious why they're broken, as the wayback machine seems to be able to run javascript. Do the visualisations rely on a server (or some other assets not included in wayback machine's crawl)?
I am certainly missing a lot of nuance here, but it seems to me Nate Silver managed to have his cake and eat it too. He surely got good money for selling FiveThirtyEight, and now that the buyer has erased the product, Nate can get back a huge chunk of its readers since he offers very similar analyses on his personal site. Sure, natesilver.net has less brand recognition than fivethirtyeight.com, but it's still decently well-known and can only go up from here.
I think the nuance is that it is notable historical articles about predictions and discussions of political elections, during a time when politics is quite at the fore-front of many people's minds
He may also finally shake off the comment trolls who piled onto him after 2016, seemingly blaming him for the election results (absurd but people are absurd).
After that election, a certain group would tirelessly work to discredit him any time his election predictions were not entirely one-sided.
It’s possible NS may have signed a contract saying that he cannot engage in elections prediction for X YZ months to same extent that he did with FiveThirtyEight.
> Electoral-vote.com is a website created by computer scientist Andrew S. Tanenbaum. The site's primary content was originally poll analysis to project election outcomes. Since the 2016 elections, the site also has featured daily commentary on political news stories.
The robots.txt file should be used to restrict (and, in some cases, slow down) crawling at the time it is being crawled, not for SEO or for restricting access to mirrors or for any other purpose. It should never apply retroactively. (Unfortunately it is sometimes used badly despite this.)
People always use that link as reference to say that Internet Archive ignores robots.txt but it only actually says they are ignoring it for government sites. It suggests that they might do it for other sites in the future (of 2017), but does not actually say that that they have done it.
That first link is confusing; it seems to say they ended up removing the pages not because of a legal threat but because of robots.txt “automated”.
If archive.org can be manipulated to remove content either via legal threats or simple robots.txt it loses a significant portion of its societal value.
It's not about robots.txt but yes, the owners of 538 can just send a cease and desist letter to get them all immediately removed. Many sites that don't want to preserve history have done this already.
The ownership relationship was always load-bearing? The journalism in this case was a tenant, I highly recommend that people promote forms of independent journalism?
I think it's the fivethirtyeight of of historical significance, and Disney is one of the largest and wealthiest companies on the planet. So it's just kinda like "whoa, this is stratospheric negligence" or "whoa, what is the reason for this... assuming they are not idiots?"
Also, they don’t any plans for the IP, and Nate would’ve paid above-market rate just to take over and preserve the content for posterity. He estimates that they deleted 200,000 hours of human labor.
This is just some Disney suits being extraordinarily petty.
Yes, just to add to this: in the article by Nate [0] he says that he tried to buy the IP but Disney refused because they were unhappy with some of his prior comments.
"I did approach Disney a year or two ago, through my agent, about acquiring the remaining IP. ...
We were told to basically get lost: ABC was annoyed with my critical public comments about their management of FiveThirtyEight. It apparently wasn’t a long conversation, so I don’t have a lot more color to report than that."
Here are some numbers roughly in the right ballpark: during the Disney era, which lasted about 10 years, FiveThirtyEight published about 20 stories a week. Let’s say that each story took about 20 hours to produce between research, writing, graphics and editing.3 Do the math, and that works out to about 200,000 person-hours of work that ABC News just deleted.
In a sense, nothing - and any other website should be archived, too.
In another sense, it's a journalistic source with information and commentary on past elections. Even aside from the political context that muddies the waters around or outright denies results, matters of public discourse on the web should not be ephemeral or subject to the decisions of the publication - they should be archived.
Did FiveThirtyEight really get that much right other than the 2016 election?
I remember thinking they were the best data journalists out there, and they had some nice visualizations but did their other predictions actually hold up?
Yes, they forecast thousands of U.S. elections and thousands of sports games, and their forecasts had excellent calibration—e.g., events they said would happen 30% of the time actually happened about 30% of the time.
This is a great service for everyone who appreciates thoughtful analyses about politics. Losing FiveThirtyEight was a big loss, but this archive helps. Bravo!
But that would be a false attribution. The Internet Archive did not create the index, Ben did. And the Internet Archive is not hosting the index, Ben is.
Ah, yes, could be worded better, fairplay. Point is the Ben attribution isn't needed in that place to avoid unnecessary confusion about who that is etc.
If I wanted to get the complete WARC archive of 538 - how do you do this in a friendly way? No interest in history tracking, just want the last available version from Internet Archive.
This is why people don't really buy the "but he had Trump at 30%, you just don't understand statistics" apologist line. Sure he hedged in the dying days of the campaign (a cynic might think to try to protect his credibility), but the tone overall was of a person who comprehensively failed to understand the mood of the country from beginning to end.
Which is a problem because these election predictions are not just pure "mathematical models" and "data driven" like 538 would have had you believe. What mathematical model should be used? What data should and should not be used? At some point those things are based on the modeller's understanding of reality.
I think Nate did a phenomenal job calling out pollsters in that time. Since 538 was predominately a poll aggregator that did tricky stats to rank the reliability of each poll. I remember specifically an interview with him griping about some of the unusual data he was seeing from pollsters that made it look like, and I quote, 'Someone has their finger on the scales'
Perhaps critiquing statistical methods used by polling was something he was good at. I have no real opinion of his work there, which I didn't pay attention to.
But predicting an election requires a lot more than polling datasets and statistics textbooks. That's the problem that he made himself out to be an election prediction wizard, but really that was off the back of his good prediction in quite a bland and conventional election.
When things got slightly more spicy and reality diverged from his vaunted "models", his "data science" predictably fell in a heap. The worst thing is almost not even that he got it wrong, it's that he seemed incapable of recognizing that present reality was quite significantly different from the past data he had used to build his models. Even after being wrong in so many of these predictions. He just kept churning out these pieces about how Trump was probably finished this time.
Okay, this is clearly an LLM response, but for the sake of being polite:
> But predicting an election requires a lot more than polling datasets and statistics textbooks. That's the problem that he made himself out to be an election prediction wizard, but really that was off the back of his good prediction in quite a bland and conventional election.
> When things got slightly more spicy and reality diverged from his vaunted "models", his "data science" predictably fell in a heap
The models were correct in two elections - arguably three because a 30% chance means that an outcome will occur in thirty times out of hundred. That is not zero.
To the person who is running this LLM, please find better things to do with yourself.
Oh I was just skim reading it and I thought the angry paranoid one said something about sending checks in :( That makes it a little less funny. I thought he was imagining Putin sending me checks for expressing verboten opinions of Nate Silver on Hackernews, lol. I think actually deep down he knew it was not even an LLM, they were just a small insecure little person who had no better way to express their anger at my post.
He didn’t hedge at the end. Nate always writes the models before election season then doesn’t touch them apart from actual bug fixes. The model actually organically predicted 30%.
I still think that’s about accurate. Maybe it should’ve been 40%.
Everyone forgets that it was a pretty close election. Clinton could’ve won without the Comey announcement.
I think he did hedge (or "strategically bug fix"). The prediction for Trump went from IIRC around 15 to 30 in the last week or so. It was a big swing, IIRC with a lot of waffle around why it happened but not a lot of verifiable fact.
> I still think that’s about accurate. Maybe it should’ve been 40%.
It wasn't accurate. This is something people misunderstand about these predictions. If the 2016 election was held 100 times, Trump would have won 100 times. It's not the same as rolling dice.
These election predictions don't say that. They say something like "the observations I have agree with scenarios that have Clinton winning, 70% of the time". Which is fine and correct as far as his data and model goes, but none of those scenarios were the reality he was trying to predict. They are all just figments of the model though. Getting down to the brass tacks, he predicted Clinton would win, and he was wrong.
Which is fine, we just can't know anything about his process from that failure. Certainly we can't conclude that it was "accurate", since it was not. If we had a good sample of elections where he used the same process and built up a good record then sure.
That's the beauty of this brand of pseudoscience. Statistical predictions of singular events like a particular election are totally unfalsifiable. You can just say "I guess we live in 30% world" or whatever, every time.
> Statistical predictions of singular events like a particular election are totally unfalsifiable.
Yes. And the 2nd Law of Thermodynamics was just violated by millions of atoms within my lungs, that happened to increase in energy above the ambient average due to collisions. Clearly thermodynamics is pseudoscience, too!
To give you a trivial example: The simplest way I can put this is that turn out varies based on the weather[1], and turn out is skewed by party. So if it rains on election day you are going to get a different result, and that result can flip the outcome of the election if the election is close. So it’s kind of a nonsense to say. “Trump would have won 100 times out of 100”. Are you saying Nate Silvers model should have had a perfect meteorological model to predict the weather? Or are you saying the election wasn’t close? In which case you’re just wrong on the facts.
The 70% figure is saying “we know most of the information needed to determine what the outcome of the election will be but we don’t know everything so can’t be certain”. There is no process where you can know every factor that determines the result in advance with absolutely accuracy and I don’t know why people expect there would be.
It's not nonsense. What's nonsense is to say Nate's prediction for the election was accurate or correct. It trivially was not.
What it would be reasonable to say is if his model had correctly predicted the outcome of a significant sample of elections, then you could say his model has some accuracy or predictive power. But it still would never have been accurate or right in the specific instances it got wrong, that's just a misconception about how statistics and predictive models work. I hope this helps.
What are you even classifying as accurate or correct? Do you take every 51% prediction from FiveThirtyEight and if the result is a win you consider that forecast accurate? And every 49% prediction must result in a loss? This just not how statistical forecasts work.
>What it would be reasonable to say is if his model had correctly predicted the outcome of a significant sample of elections, then you could say his model has some accuracy or predictive power.
I don't know why you're couching that in a hypothetical, FiveThirtyEight has repeatedly done that exercise.
>But it still would never have been accurate or right in the specific instances it got wrong
It is core to the concept of a probability that the result is going to go the opposite way from the prediction sometimes! It's meaningless to call it "wrong".
> What are you even classifying as accurate or correct?
When somebody gives a prediction of the outcome of an election? I classify it as correct if they predicted the candidate who wins.
> Do you take every 51% prediction from FiveThirtyEight and if the result is a win you consider that forecast accurate? And every 49% prediction must result in a loss? This just not how statistical forecasts work.
No, but it is the way to map statistical forecasts to reality. He was quite explicitly predicting the outcome of the actual election. That prediction was incorrect.
The whole rating of the accuracy of these models is really snakeoil dressed up as science. There is a lot less rigorous science and a lot more feelings and adjusting numbers and twiddling formulas retrospectively than you were probably led to believe.
Would a 99-1 for Trump model have been worse or less accurate than a 51-49 for Clinton model? Despite predicting the correct outcome whereas the Clinton model predicted the incorrect outcome?
> I don't know why you're couching that in a hypothetical, FiveThirtyEight has repeatedly done that exercise.
Not really with much rigor. Where are their reproducible published papers and data sets? They made their name with a bit of luck on a fairly predictable election, but were unable to show a significant advantage in their methods across a number of elections.
> It is core to the concept of a probability that the result is going to go the opposite way from the prediction sometimes! It's meaningless to call it "wrong".
No no, that's not true. There are two different things here. Firstly, if you had a model and method of predicting elections that you applied to a sample of elections and showed that it had a good ability to correctly predict, then you can say your model is a good prediction across typical elections. The model getting one wrong does not make it a bad model over a set of elections. It absolutely is wrong for that particular election though. And secondly if you use a model to make a prediction about a particular election, when your prediction turns out to be wrong, it was not retroactively correct because it just followed the model and you claim the model is good. That's just not how statistics or predictions work.
That's where you're wrong, the election was very, very close. In fact, if roughly 40k voters (across three states) had switched from Trump to Hillary, she would have won, that's how close it was.
40k voters, that's really not very many. So it's hard to say whether Trump had a 30% chance of winning or 40% or whatever, but the election at most was a toss-up.
Many random events could have resulted in a different outcome.
You misunderstand my point. I am talking about the actual election that happened where these many random events that could have resulted in a different outcome did not happen. I was being a bit facetious maybe in my point. But the point is that the thing that is to be predicted is the actual real event that occurs in this universe. Silver made a prediction, and it was wrong.
"Oh but it was only a 70% prediction"
You can't 70% win an election. Silver's prediction was that Clinton would win, but he was not super confident about it. The prediction was wrong. He was right to not be super confident about it, but the prediction of who would win was still wrong.
Statistical likelihood is a measurement of the known data at the time. If you engage with the content otherwise then it's on you if you have the wrong takeaway. No one who makes a prediction based on a statistical model is going to be right every time. That doesn't mean it's not right to make a prediction. The statistical modeling can help you to be correct more often than not. And if you were going to be truly fair you would note that Nate in fact repeatedly said that it was still very much possible for Trump to win but that the current known polling data and other factors in his model pointed to a loss.
538's own post-mortem's on the event highlight that Trump was a very unusual candidate running in a very unusual election and as such the model was missing a lot of important information. They learned from the experience and adjusted the model going forward. Anyone complaining about that event is really just highlighting that they don't understand how statistical modeling works and are upset about how the model misled them or others which isn't Nate or 538's fault and is entirely on the consumer of their reporting. It's not like they didn't try to educate their consumers in their reporting.
I know what statistical likelihood is. I don't have a problem with them using a model or models and doing some statistics on it to develop these predictions, or even necessarily with the way they report their predictions as a % chance to win. I have a problem with the insinuation that "70% Clinton" is somehow a prediction of a singular real event or that Trump winning is consistent with said prediction "because if we held another 99 of those 2016 elections then Clinton probably would have won about 70 of them therefore I was right".
The prediction is for one single outcome at one point in time. The prediction can not be that Clinton 70% wins it, or wins it 70 out of every 100 times because there is no 100 2016 elections. Those things may apply to his mathematical models, but obviously the models are attempting to predict the real world. Try to weasel out of it as much as you like, but the prediction was that Clinton would win, and the prediction was wrong.
"Oh he was only giving the odds for his model, you don't understand it's your fault he mislead you" -- no. Every analyst and pundit has a model or a system, obviously nobody thinks any of them can see the future. Nate Silver was very explicitly predicting the outcome of the election. As you can see from all his commentary articles that came out along with the numbers.
And yes, 538's vaunted models and data science fell over when encountering situations that had not been seen or anticipated or built on before, obviously. We didn't need Einstein or even Nate Silver to tell us that. That's the problem isn't it. All this hamming up of "data science" and "mathematical models" is meaningless. Your data and math can be perfect and correct, but if they fail to provide an understanding of the world, then they are perfectly useless.
Just want to say, I appreciate your pragmatic perspective on this. Nate Silver had one job: Predict who would win. And he failed at that. With lots of hand waving he can excuse himself but at the end of the day his visitors wanted an answer and he gave them the wrong answer.
It's a bit more loaded than that. 538 post-Nate Silver had a model setup that was apparently kind of a mess. 538 was apparently sending strange messages to Republican leaning polling agencies, demanding they gave far more detailed audit information than usual (with the implication obviously being that they were fraudulent pollsters), and the guy running the site had fairly openly tuned his model on the assumption people cared about certain talking points. 538 was predicting Biden victories even when the polls were so overwhelmingly against him that not even the most Democratic leaning polling agencies had trust in him; even if you aren't running difficult math, that means something has gone wrong with the model.
(Something which got worse after Harris was picked, although every polling aggregator went barmy - there's suspicions that a lot of polling agencies aggressively normalized their data to avoid being seen as biased, leading to an almost 50/50 split.)
So, I would actually agree with you that 538 was a mess in that period. I would actually trace the first problems back to Enten's departure, but it did get worse when Silver left.
It's just that this particular criticism (that they got it "wrong") doesn't seem very well founded.
Biden got literally 0% of the vote despite 538 predicting him to win.
They chose to pretend Biden's mental decline wasn't happening because that was the Democrat party line at the time. How can you trust predictions from someone who is willing to manipulate his results to prop up his political party?
What would you have them do in that period? Give Trump a 100% chance of winning? Make up a candidate who wasn't actually running? Arguably the most realistic thing to do would be to give X% Trump, Y% Some Democrat -- but had they done that, they'd have been rightly criticized for making an obvious vibe-driven decision. You can't change a quantitative prediction based on qualitative observations; all you can do is try to find more and better data sources.
The issue the models had in that period was pretty well documented: the models rated fundamentals (like economic indicators) more highly relative to polls when the election was farther in the future. Those were the same economic indicators that famously do not capture the pain average Americans have felt since COVID, and that politicians across the spectrum have tried to use to deny that pain when they are in power.
You can argue that this issue was well known at the time, and that a better group of analysts might have taken action to mitigate it. I'd argue that myself. It turns out that it's kind of hard, but that's a terrible excuse not to try. That is different than deliberately manipulating results for political ends, though. It's unclear what political ends those would even be -- who exactly benefits from an "unclear winner" forecast in that situation?
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