Nate Silver's Blog, page 111

What Should Democrats Do About Gorsuch?

In this week’s politics chat, we discuss the politics of President Trump’s pick for the Supreme Court, Neil Gorsuch.

micah (Micah Cohen, politics editor): Welcome! This is a special post-Supreme Court pick chat, so we’ve invited our resident SCOTUS expert, Oliver Roeder, to join us.

On the agenda for today:

General impressions on the politics of Trump’s pick.What’s the deal with Gorsuch? Mainly: How would he affect the court’s ideological makeup? What issues could he tip the balance on?What are his confirmation chances? How hard will Democrats fight to block him?

Everyone ready?

clare.malone (Clare Malone, senior political writer): Are we going to talk about “the handshake”?

micah:

Maybe Trump was expecting to bring it in for the always manly handshake-to-hug?

harry (Harry Enten, senior political writer): Better to get an awkward handshake than no handshake at all, like Judge Hardiman got.

clare.malone: Well, Gorsuch handled the hand assault with aplomb. As a couple, they were not into the hug genre, I have to say. Respect. Hugs are overused in modern America.

micah: OK, that might be a record for one of these chat’s being derailed away from substance.

clare.malone: Sorry I’m not sorry. I have real thoughts: Gorsuch is a continuation of Trump/Stephen Bannon’s two-week “wow ’em” show for the base.

harry: Gorsuch is a great pick for conservatives. He’s also well-qualified (we’ll get into that a little later), so you can’t say this was a purely political pick.

ollie (Oliver Roeder, senior writer): One way to quantify the ideology of a federal judge like Gorsuch, as compared to those sitting on the Supreme Court, is something called “judicial common space” scores. This is essentially a mashup of justice voting records, the ideology of the nominating president, and the ideology of the judge’s home-state senators. By that measure, Gorsuch falls somewhere to the right of where Justice Antonin Scalia, who died last year, sat, ideologically.

micah: Ollie, you’re not really supposed to bring actual data into these chats.

ollie: Sorry not sorry.

clare.malone: Trump wants movement conservatives to feel taken care of quickly, to feel that there is real change from the Obama era — they are giving them the impression that the Trump era is comprehensively and quickly moving to change American life for the better. I think it’s a smart impressionistic move — make the people feel the feels.

natesilver (Nate Silver, editor in chief): I guess I think this is very much a Politics 101 pick. Straight down the fairway. Exactly how you’re supposed to play it. Pick someone who fits your base’s ideological priors but who is well-qualified enough that he isn’t likely to create extra vetting problems. Caveat here being that Gorsuch hasn’t been exposed to the vetting wolves yet, so maybe this will all look foolish in a week.

clare.malone: And young.

natesilver: Yeah.

ollie: The youngest nominee since Thomas.

micah: So why do we automatically say he is “well-qualified”? I’ve seen that everywhere — including on our site.

clare.malone: Because America is classist, and we think that Ivy League = smart.

*Often Ivy League does mean smart.

natesilver: Ivy league shmivy league

ollie: One thing that’s underreported, Clare, is that he attended the University of Colorado at Denver for a summer. ¯\_(ツ)_/¯

clare.malone: But, like, have you met the Harvard legacy admit crowd? Oof. I wouldn’t let them touch my stock trades with a 10-foot pole.

micah: I’m super freaking smart, and I didn’t go to an Ivy League school. TULANE UNIVERSITY FOR LIFE!

harry: I think we say well-qualified because (i) the American Bar Association gave him that seal — “unanimously well qualified” — when he was nominated for his current job; (ii) he draws comparisons to Scalia, who was widely regarded as very well-qualified; and (iii) check out this op-ed from former President Barack Obama’s solicitor general.

clare.malone: He’s also a Marshall scholar. So. That’s impressive.

micah: OK, fine … he’s well-qualified.

clare.malone: And people say he’s an engaging writer.

harry: Elena Kagan said he is a very good writer! And that’s what makes the politics so wonderful from Trump’s point of view: Many on the left in judicial circles like the guy, and conservatives like the record.

natesilver: Hmm. You have to justify that “many on the left” claim, Harry. So far, it’s one dude. It seems like people on the left don’t have a lot of great arguments against his credentials. But that’s different than saying they celebrate his jurisprudence, or whatnot.

harry: I think you’re reading too much into my words. They like the guy for his intellect.

clare.malone: He seems “not scary” to liberals, I think is what Harry might be getting at — in the Trump era, when a nominee seems not Mike Flynn-esque, they’re going to take a chance and say, “Maybe he’ll turn out less conservative on things than we think he will?”

ollie: SCOTUSblog put together a list of reactions to the nomination. Not exactly a comprehensive gauge of reaction, but the “against the nomination” list is a bit longer.

natesilver: I think the Democratic base is likely to regard him as being very scary within a week or so. He has a very conservative reading of the Constitution, which they won’t like.

harry: Are we getting into confirmation chances?

micah: Not yet.

natesilver: No, but I think people should be aware that credentials matter to elites, more so than to rank-and-file voters. Which doesn’t mean they aren’t important.

micah: I think that’s probably true, Nate. But I think Clare’s right that for Democratic elites (who will be voting on the nominee), it matters that Gorusch is a “normal” conservative.

harry: With a record like Scalia’s, I don’t suspect there’ll be much support on the left for Gorsuch. Then again, given the polarized times, I wouldn’t expect most liberals to vote for Trump’s nominee regardless. The question ultimately is how many Democrats vote to end a filibuster. And that’s where I think credentials do play a bigger role. Will they let this guy through? Or do they think he’s a lunatic? Is the fight here and now? Or is it worth torching someone else down the line? And I think credentials do play a role in that.

clare.malone: There is also the idea of saltiness over the Merrick Garland process, right? How much will that play in?

micah: A lot? That’s what some reporting suggests. Other reports suggest that Democrats may back off and save the real fight for a pick that would tip the ideological balance.

natesilver: A lot of this is optics instead of substance, and I wonder if we should be looking past the optics more.

micah: Hold that thought. One last question before we move to issues: There’s a theory (which I subscribe to) that Trump doesn’t win the 2016 election if conservatives aren’t thinking about this open Supreme Court seat. Basically, the theory holds that a lot of true-blue (red) conservatives held their nose and voted for Trump despite his apostasies because he promised them a justice they would love by releasing that

Politics Podcast: To Filibuster Or Not To Filibuster

 Subscribe: iTunes |ESPN App |Download |RSS |New to podcasts?

President Trump announced his nomination of Judge Neil Gorsuch (an Antonin Scalia lookalike) to the U.S. Supreme Court on Tuesday night. The FiveThirtyEight Politics podcast team discusses Gorsuch’s ideological background, how his confirmation would affect the court and the political strategy that Democrats could adopt in response to his nomination. Several Democrats have already indicated that they plan to use the filibuster to slow or block Gorsuch’s confirmation, and Trump has suggested that if Senate Republicans can’t overcome a filibuster, they counter by doing away with the filibuster rule.

You can listen to the episode by clicking the “play” button above or by downloading it in iTunes, the ESPN App or your favorite podcast platform. If you are new to podcasts, learn how to listen.

The FiveThirtyEight Politics podcast publishes Monday evenings, with occasional special episodes throughout the week. Help new listeners discover the show by leaving us a rating and review on iTunes. Have a comment, question or suggestion for “good polling vs. bad polling”? Get in touch by email, on Twitter or in the comments.

Before You Call Your Senator, Read This On How Our Trump Scores Work

On Monday, we launched a dashboard that tracks how often members of the House and Senate have voted in line with President Trump’s position on bills and nominations. We were pleasantly surprised at how many people were interested in this feature — the level of political energy right now is about as high as I can remember in the almost 10 years that I’ve covered politics. But as a result, what we’d expected to be a fairly slow rollout suddenly occurred much faster. So I wanted to add a word of caution, along with a bit more methodological detail.

The caution is simply this: For the time being, these calculations aren’t based on very many votes. Therefore, they’re likely to bounce around over the next few weeks until more votes are taken. As of Monday, they included just four votes in the House and six votes in the Senate. It’s also important to note that we aren’t tracking all votes — only those on which Trump takes a clear position. So they represent a small sample size, for now.

Another unique feature of our dashboard is the plus-minus scores. The basic idea is to compare how often a member of Congress voted with Trump against others where the 2016 presidential vote was similar. For instance, you’d expect members to support Trump most of the time if they come from a state or district that voted for Trump by 30 percentage points, but not very often if they’re from one where Hillary Clinton won by that margin.

These estimates are calculated on a bill-by-bill basis. Here, for instance, is a breakdown of votes on confirming Mike Pompeo as CIA director based on the 2016 vote in each senator’s state. Almost all (38 of 40) senators from states that Trump won by 10 or more percentage points voted to confirm Pompeo. Just five of 24 from states that Clinton won by 10 or more points voted to confirm him, however. The majority of senators from swing states voted to confirm him, however, which is why his nomination eventually passed by a fairly clear 66-32 margin.

2016 ELECTION RESULTYEANAYTrump by 20+ percentage points262Trump by 10-19120Trump by 0-9146Clinton by 0-995Clinton by 10-19210Clinton by 20+39Votes to confirm Mike Pompeo as CIA director by state partisanship

Technically speaking, our projections are calculated by probit regression. For each bill, we run a regression in which the input (independent variable) is the presidential margin in each member’s state or district and the output (dependent variable) is the member’s probability of voting for the bill. On the confirmation of Pompeo, for instance, the model shows Democratic Sen. Mazie Hirono of Hawaii, the bluest state in the 2016 election, with an 11 percent chance of voting to confirm him, but Republican Sen. Mike Enzi of Wyoming, the reddest state, with greater than a 99 percent chance. To reiterate, the regression is essentially just looking at how a member’s colleagues in states or congressional districts of similar partisanship voted. If we say that Sen. Dick Durbin of Illinois has a 32 percent chance of voting for Pompeo, for instance, that just means that about one-third of his colleagues in states like Illinois (which voted for Clinton by 17 percentage points) did so. Note that the regression does not consider a member’s party or any other factor apart from the 2016 presidential vote. Thus, Democratic Sen. Jon Tester of Montana and Republican Sen. Steve Daines of Montana are each given the same likelihood of voting for Pompeo, for instance.

Here’s an example of how the calculations work for Kentucky Sen. Rand Paul, a Republican with some libertarian and “maverick” tendencies. Trump won Kentucky by almost 30 points, and most of the senators from states like that have voted with Trump almost all of the time so far. (In the long run, Democratic Sens. Joe Manchin of West Virginia and Heidi Heitkamp of North Dakota will sometimes be exceptions to this, although even they have supported Trump’s position in five of six votes to date.) The regression model, therefore, estimates that a senator from a state that Trump won by 30 points “should” have voted with Trump 98 percent of the time so far. Instead, Paul voted against Trump twice — first on a bill to allow Republicans to repeal certain provisions of the Affordable Care Act without having to overcome a filibuster and secondly on Pompeo. In both cases, Paul was the only Republican “no” vote.

MEASURETRUMP’S POSITIONVOTED WITH TRUMP?LIKELIHOOD OF TAKING TRUMP’S POSITION BASED ON TRUMP’S 2016 MARGINPLUS-MINUSAllow reconciliation on Affordable Care ActSupportNo92%-92%Waiver to allow Mattis as defense secretarySupportYes99%+1%Confirmation of Mattis as defense secretarySupportYes100%+0%Confirmation of Kelly as HS secretarySupportYes100%+0%Confirmation of Pompeo as CIA directorSupportNo97%-97%Confirmation of Haley as U.N. ambassadorSupportYes100%+0%Average67%98%-31%Rand Paul’s plus-minus calculation

Thus, Paul has supported Trump only 67 percent of the time, instead of the 98 percent of the time you’d expect based on Trump’s margin of victory in Kentucky. In our parlance, that means Paul has a substantially negative (-31) plus-minus score — he’s supported Trump less often than you’d expect. If Paul keeps that up, he could be a real thorn in the side of the Trump administration. Still, the score is based on just six votes for now.

A contrasting case is Democratic Sen. Dianne Feinstein of California. After missing the vote on the Affordable Care Act to have pacemaker surgery, she has so far voted with Trump five of five times despite hailing from one of the nation’s bluest states:

MEASURETRUMP’S POSITIONVOTED WITH TRUMP?LIKELIHOOD OF TAKING TRUMP’S POSITION BASED ON TRUMP’S 2016 MARGINPLUS-MINUSWaiver to allow Mattis as defense secretarySupportYes37%+63%Confirmation of Mattis as defense secretarySupportYes92%+8%Confirmation of Kelly as HS secretarySupportYes52%+48%Confirmation of Pompeo as CIA directorSupportYes13%+87%Confirmation of Haley as U.N. ambassadorSupportYes84%+16%Average100%56%+44%Dianne Feinstein’s plus-minus calculation

Some of these “yes” votes were to be expected. All but one Democrat voted to confirm James Mattis as secretary of defense, and all but three Democrats (and independent Bernie Sanders) voted to confirm Nikki Haley as U.N. ambassador. However, most Democrats voted against Pompeo as CIA director, when Feinstein voted for him. The regression model would especially expect a Democrat from a state as blue as California — which went for Clinton by 30 percentage points — to have voted against Pompeo. It also gave Feinstein about a 50-50 chance of voting against John Kelly as secretary of homeland security, since support for Kelly was spotty among senators from states as blue as California, but Feinstein voted to confirm him.

Overall, Feinstein has voted with Trump 100 percent of the time, compared with the 56 percent of the time the model expected. That means she has a highly positive (+44) plus-minus score — that is to say, more pro-Trump than you’d assume given that she comes from a state where Trump is so unpopular.

Feinstein’s score is still based on just five votes, however, so you probably want to see how she votes on a few more issues before calling her office. Her score is also somewhat affected by having missed the Obamacare vote, although — especially after a technical change we made — that matters less than you might think. Feinstein would presumably have voted “no” on the Obamacare measure, as every other Democrat did. However, the regression analysis would have assumed that she’d almost certainly have voted no, so it wouldn’t have affected her plus-minus score all that much. Under the plus-minus system, the votes that matter are the ones that defy expectations, such as Paul’s vote against Pompeo or Feinstein’s in favor of him.

Over the next few weeks, we’ll be adding some new features to the dashboard — for instance, pages allowing you to see a detailed list of votes for and against Trump for all members of Congress, as in the examples for Paul and Feinstein above. And by later this year, after we’ve collected several dozen votes, we may place them into different categories. Do some members of Congress support Trump on key votes but oppose him in cases when their votes don’t matter much — or vice versa? Do some agree with him on economic policy but oppose him on expanding the federal government’s powers? Without any exaggeration, this year should be among the most important in the history of the U.S. Congress, and we’ll be covering what they do closely.

VIDEO: Nate Silver on Trump’s immigration order

Politics Podcast: Chaos At The White House

 Subscribe: iTunes |ESPN App |Download |RSS |New to podcasts?

President Trump’s first week in office proved chaotic. It started with false claims of mass voter fraud and ended with his signing an executive order temporarily banning all refugees, as well as immigrants from seven majority-Muslim countries. The FiveThirtyEight Politics podcast team looks for a strategy behind the chaos and questions how popular the president’s executive order will be. The crew also talks to Meenekshi Bose, executive dean of public policy at Hofstra University, about a shakeup within the National Security Council. Trump demoted the director of national intelligence and the chairman of the Joint Chiefs of Staff and gave a seat to his chief strategist, Steve Bannon.

You can listen to the episode by clicking the “play” button above or by downloading it in iTunes, the ESPN App or your favorite podcast platform. If you are new to podcasts, learn how to listen.

The FiveThirtyEight Politics podcast publishes Monday evenings, with occasional special episodes throughout the week. Help new listeners discover the show by leaving us a rating and review on iTunes. Have a comment, question or suggestion for “good polling vs. bad polling”? Get in touch by email, on Twitter or in the comments.

Trump Is Doing What He Said He’d Do

It’s up against some stiff competition, but there’s a runaway front-runner in the “wrongest idea of 2016” derby. It’s the aphorism, once fashionable on the morning-talk show circuit, that the media mistakenly took Donald Trump “literally but not seriously,” when they should have taken him “seriously but not literally,” as Trump’s supporters did.

If the idea is that the media should have taken Trump more seriously, then I’d emphatically agree. But it turns out that they probably ought to have taken him literally too. It’s been an exceptionally busy first 10 days in office for President Trump, culminating in an executive order on Friday that banned immigrants from seven predominantly Muslim countries from entering the United States for 90 days and banned all new refugees from entering the U.S. for 120 days. (Over the weekend, several courts issued rulings temporarily blocking parts of Trump’s order.)

Almost all of the actions that Trump has undertaken, however, are consistent with statements and policy positions he issued repeatedly on the campaign trail and during the presidential transition. It was more than a year ago that Trump called for a “total and complete shutdown of Muslims entering the United States,” for instance. (Friday’s executive order stops short of that, but Trump allies such as Rudy Giuliani have spoken of the order as a legal workaround that seeks to accomplish the same objectives as a Muslim immigration ban.) Another executive order called for building a border wall with Mexico, which was perhaps the signature policy position of Trump’s campaign. And Trump might even try to “make Mexico pay for it” by imposing a tariff on Mexican imports — although most economists argue such a tariff would really make American consumers pay for the wall, via higher prices.

Trump and Congress have taken initial steps toward dismantling Obamacare. He promised that too, although he also promised to replace the Affordable Care Act with “something terrific,” which should give pause to Republicans hoping to repeal the plan without a replacement in place. Investigating (highly dubious accounts of) voter fraud? Trump talked about that plenty of times on the campaign trail.

There’s been no “pivot,” and there have been no half-measures. Trump is doing pretty much what he said he’d do. Literally.

Why, then, does Trump’s first week and a half in office seem so surprising, even to those of us who weren’t expecting a kindler, gentler Trump? One could wryly remark that it’s a surprise whenever presidents actually keep their promises. But a longstanding body of research from political scientists suggests that this shouldn’t be a surprise. Presidents actually do make a good-faith effort to keep most of their promises.

Instead, the sense of surprise may reflect the dissonance between the sweeping nature of the changes Trump has brought about so far and his narrow and tenuous mandate from American voters. Trump lost the popular vote to Hillary Clinton, of course, in what turned out to be the biggest discrepancy between the popular vote and the Electoral College since 1876. The 46 percent of the popular vote he received was on the low end also, ranking 23rd of the past 25 election winners, ahead of only Richard Nixon in 1968 and Bill Clinton in 1992. His electoral vote total was slightly more impressive, but also well below average for a winning candidate, ranking 20th out of the past 25 elections. So by pretty much any measure, Trump entered office with one of the three narrowest mandates of the past century, along with Nixon in 1968 and George W. Bush in 2000.

ELECTORAL COLLEGE SHAREPOPULAR VOTE SHAREPOPULAR VOTE MARGINOVERALLYEARPRESIDENTSHARERANKSHARERANKMARGINRANKAVERAGE RANK1936Roosevelt98.5160.82+24.332.01972Nixon96.7360.73+23.243.31964Johnson90.3561.11+22.653.71984Reagan97.6258.85+18.264.31920Harding76.11360.44+26.216.01932Roosevelt88.9657.47+17.876.71928Hoover83.6958.26+17.487.71956Eisenhower86.1757.48+15.498.01924Coolidge71.91454.011+25.229.01940Roosevelt84.6854.710+10.0119.71952Eisenhower83.21055.29+10.9109.71980Reagan90.9450.816+9.71210.71944Roosevelt81.41153.412+7.51512.71988GHW Bush79.21253.413+7.71413.02008Obama67.81752.914+7.31615.71996Clinton70.41549.321+8.61316.32012Obama61.71851.015+3.91917.31948Truman57.11949.620+4.51819.01992Clinton68.81643.025+5.61719.32004GW Bush53.22450.717+2.52020.31976Carter55.22350.118+2.12120.71960Kennedy56.42149.719+0.22321.01968Nixon55.92243.424+0.72222.72016Trump56.52045.923-2.12522.72000GW Bush50.42547.922-0.52423.7By most measures, Trump’s victory was modest

Sources: Dave Leip, Statistical Abstract of the United States, David Wasserman, Wikipedia

Both Nixon and Bush, however — although they’d later become polarizing presidents — adopted conciliatory tones during their transitions into office. Hardly a partisan word can be found in Nixon’s 1969 inaugural address or Bush’s in 2001. They began their presidencies as relatively popular presidents, therefore. Gallup’s first approval rating poll on Nixon had 59 percent of the public approving of him, against just 5 percent disapproving. For Bush, the numbers were 57 percent approving and 25 percent disapproving. Trump? He started out with 45 percent approving and 45 percent disapproving in the Gallup poll, and his numbers have already gotten worse since last week (although we’ll need more data to confirm whether that’s a meaningful trend).

So Trump’s governing like he’s Franklin D. Roosevelt in 1937 or Ronald Reagan in 1985, presidents who won via record-breaking landslides. But Trump’s popularity measures are more like those of an embattled president a couple of years into his tenure — think Bill Clinton in 1995, for example. Those low moments don’t necessarily doom a presidency; they didn’t doom Clinton’s, and Reagan and Barack Obama also endured bouts of unpopularity before being re-elected. But we’re in uncharted waters to see a president who is so unpopular so early in his term — and yet who is plowing ahead so stubbornly (or so resolutely, if you prefer) with his agenda.

Then again, this was the agenda Trump promised the country, more or less. So here’s my question: Was Trump elected because of his agenda, or despite it?

That is to say, were his supporters taking him literally, or not?

I don’t have a good answer to this question yet, but it could be the one that Trump’s presidency turns upon. If his supporters took him literally, they’ll presumably see a lot to like so far. But many of these policies have tenuous public support beyond Trump’s base. If this is the framework, then Trump is just continuing with the strategy he’s bet upon all along — doubling down on support from his base — and his approval ratings will probably oscillate within a relatively narrow band of 40 percent to 45 percent support. With Republicans controlling both chambers of Congress and having a geographic advantage in the way their votes are distributed, that mediocre rating wouldn’t necessarily do much to constrain Trump in the near term, although ratings toward the lower end of that range might be enough to make the House of Representatives competitive in 2018.

If Trump’s supporters didn’t take him literally, however, the downside might be greater. There are quite a few Trump policies, including greater restrictions on immigration, that are fairly popular in spirit but became unpopular when taken to the extreme that Trump takes them. Other voters may have felt they were in on the joke when Trump was running against the staid, politically correct establishment, but will hold him to a higher standard of responsibility now that he is implementing policies rather than just talking about them. Perhaps they’ll give Trump some credit for keeping his promises, but those promises weren’t very popular ones.

If nothing else, the few naive elites who expected Trump to turn into some sort of moderate, Arnold Schwarzenegger clone are likely to be disappointed. They should have taken Trump at his word — literally.

Why Early Voting Was Overhyped

This is the fifth article in a series that reviews news coverage of the 2016 general election, explores how Donald Trump won and why his chances were underrated by the most of the American media.

Some statistical indicators are more useful than others. Data on early voting, for instance, usually doesn’t provide much predictive insight. Historically, the relationship between early voting in a state and the final voting totals there has been weak, and attempts to make inferences from early voting data have made fools of otherwise smart people. In the 2014 midterms, Democrats used early-vote numbers to claim that the polls were underrating their chances. Instead, it was Republicans who substantially beat the polls.

None of this deterred reporters and analysts from frequently citing early vote data in the closing weeks of last year’s presidential campaign, very often taking it to be a favorable indicator for Hillary Clinton. On Oct. 23, for instance, The New York Times argued that because Clinton had banked votes in North Carolina and Florida, it might already be too late for Donald Trump to come back in those states:

Hillary Clinton moved aggressively on Sunday to press her advantage in the presidential race, urging black voters in North Carolina to vote early and punish Republican officeholders for supporting Donald J. Trump, even as Mr. Trump’s party increasingly concedes he is unlikely to recover in the polls.

Aiming to turn her edge over Mr. Trump into an unbreakable lead, Mrs. Clinton has been pleading with core Democratic constituencies to get out and vote in states where balloting has already begun. By running up a lead well in advance of the Nov. 8 election in states like North Carolina and Florida, she could virtually eliminate Mr. Trump’s ability to make a late comeback.

Initially, these reports on early voting were at least consistent with the polls: Clinton had led in most polls of North Carolina and Florida in mid-October, for instance. But when the race tightened after James B. Comey’s letter went to Congress on Oct. 28, early voting data was increasingly cited in opposition to the polls, with pundits and reporters criticizing sites such as FiveThirtyEight and RealClearPolitics for not incorporating early voting data into their forecasts. (It can be easy to forget now, but we spent a lot of time arguing with people who thought our forecast was too generous to Trump.)

So what happened? In North Carolina, Clinton won the early vote by 2.5 percentage points, or about 78,000 votes. Furthermore, about two-thirds of votes were cast early. But Trump won the Election Day vote by almost 16 percentage points. That was enough to bring him a relatively healthy, 3.6-point margin of victory over Clinton overall.

TRUMPCLINTONMETHODVOTESSHAREVOTESSHAREEarly (mail or in-person)1,474,29647.1%1,552,20349.6%Election day888,33555.1637,11339.5Total2,362,63149.82,189,31646.2Clinton won early voting, but Trump won North Carolina

Election day votes include provisional ballots. Includes third-party candidates.

Source: North Carolina State Board OF Elections

The Election Day surge for the GOP wasn’t anything new in the Tar Heel State, however. In 2012, President Obama had built a 129,000 early vote lead over Mitt Romney — substantially larger than Clinton’s over Trump — but had lost the Election Day vote by a huge margin, costing him the state:

ROMNEYOBAMAMETHODVOTESSHAREVOTESSHAREEarly (mail or in-person)1,297,06747.2%1,426,12951.9%Election day973,32855.3752,26242.8Total2,270,39550.42,178,39148.4Obama won early voting, but Romney won North Carolina

Election day votes include provisional ballots. Includes third-party candidates.

Source: North Carolina State Board OF Elections

So Clinton was running behind Obama’s early voting pace in North Carolina — which obviously wasn’t a good sign, given that Obama had lost the state. Why, then, had people taken the North Carolina numbers as good news for her? Actually, not everybody did. A few news outlets had pointed out that Clinton was running behind Obama’s pace there, and the Clinton campaign itself was worried about its North Carolina numbers.

Still, early voting data can be easy to misinterpret. Early voting is a relatively new innovation. Traditions and turnout patterns vary from state to state, and they can change whenever new laws are passed, or depending on how much the campaigns emphasize early voting. Meanwhile, early voting numbers are reported from lots of different states at once. Many news outlets focused on a supposed turnout surge for Clinton among Hispanic voters while giving less attention to signs of decline in African-American turnout. The latter was actually more important than the former because blacks are more likely than Hispanics to be concentrated in swing states.

Furthermore, early voting data doesn’t necessarily provide reason to doubt the polls, because early voting is already accounted for by the polls. For instance, some North Carolina polls had shown Clinton losing the state despite winning among early voters, just as actually occurred.

So there are multiple interpretations of the data, but there’s not much empirical guidance on which one works best … that makes for a recipe for confirmation bias. The Times, for instance, was exceptionally confident in Clinton’s chances from the start of the campaign onward, and early voting tended to reinforce its pre-existing views of the race.

There’s also a broader point to be made about the use and abuse of data in campaign coverage. After the election, some of the pundits who had touted Clinton’s early voting numbers as an alternative to polls claimed that “the data” was wrong and had led them astray. And the Times, which had spent a lot of time reassuring its readers that Clinton would win, wrote an article entitled “How Data Failed Us in Calling an Election.”

Whenever I see phrasing like this, I mentally substitute the near-synonym “information” for “data” and reconsider the sentence. Would the Times have published a headline that read “How Information Failed Us in Calling an Election”? Probably not, because that sounds like the ultimate dog-ate-my-homework excuse. Isn’t it the job of journalists to sort through information and uncover the real story behind it?

But the thing is, blaming “the data” usually is a dog-ate-my-homework excuse. The problem is often in assuming that because you’ve cited a number, you’ve relieved yourself of the burden of interpreting the evidence. And as we’ve described in the first few installments of this series, news outlets referenced lots of data during the general election but often misinterpreted it, almost always reading it as good news for Clinton even when there were conflicting signals. They touted early voting as favorable for Clinton, even though it hadn’t been very predictive in the past and showed problems for her in states such as North Carolina. They asserted that the Electoral College was a boon for her, even though the data showed it was Trump’s voters and not Clinton’s who were overrepresented in swing states. They highlighted Clinton’s numbers in Arizona, but downplayed data showing Clinton struggling in Ohio and Iowa, which had traditionally been bellwether states. They mostly ignored data showing an unusually high number of undecided voters, which made Clinton’s polling lead much less secure.

I don’t mean to suggest that one should have gone to the other extreme and confidently predicted a Trump victory. Nor do I mean to imply that interpreting election data correctly is easy; it usually isn’t. (This goes for us too: FiveThirtyEight got itself in one heck of a mess in assessing Trump’s chances in the Republican primary.) But political journalism circa 2016 was in a place where there was a lot of fetishization of “data,” but not a lot of experience with or appreciation for the tools needed to interpret it — namely, probability, statistics and the empirical method. That made for a high risk of overconfidence in extracting meaning from the data.

Ohio Was A Bellwether After All

This is the fourth article in a series that reviews news coverage of the 2016 general election, explores how Donald Trump won and why his chances were underrated by the most of the American media.

I’ve contended in this series that national news outlets haven’t candidly explored the reasons they were so sure Hillary Clinton would become president. Blaming polls or “data” is something of a red herring given that the data told a complicated story. Perhaps the closest thing they’ve offered to an actual explanation is that the failure reflected a lack of shoe-leather reporting. One day after the election, for instance, New York Times Executive Editor Dean Baquet said that the biggest flaw in his paper’s 2016 coverage was in not having enough reporters “on the road, out in the country, talking to different kinds of people than the people” they usually talked to.

There are versions of Baquet’s idea that I agree with. The Times and other outlets would have been better off if they’d put less emphasis on the insider’s view of the race, as articulated by campaign consultants in New York and Washington. Better yet would be if local and regional news outlets, which face increasingly difficult economics, had more of a place in the national conversation, serving as a potential check against groupthink in the Northeast Corridor. The voters who proved decisive in the Electoral College were mostly in “flyover country” instead of on the coasts.

But if the idea is that reporters should have spent more time talking to people in the field as opposed to looking at the polling, then I’m wary — and I don’t think it goes very far in explaining why reporters failed to foresee a Trump presidency. Partly this is because it can be easy to misread the vibrations on the ground, as the Times did in 2012 when it unironically cited “yard signs on the expansive lawns of homes in the well-heeled suburbs, and … the excited voices of Republican mothers” as reasons to think Mitt Romney would win Pennsylvania. But more importantly, polling and ground reporting ought to be compatible. Reporting can provide context and depth and nuance, and we’ve done more and more field reporting ourselves at FiveThirtyEight, having sent reporters to such places as Ashtabula County, Ohio, and Presque Isle, Maine. But polls are also a way of “talking to human beings,” only in a relatively unbiased fashion that potentially reaches a more representative sample of voters than a reporter probably could.

Instead the problem was in a failure to draw a connection between Clinton’s problems in the heartland — which were evident both from polling and from reporting — and her vulnerable position in the Electoral College overall. Take, for example, this Sept. 29 Times article, which correctly noted that Trump was running strongly in Ohio. Shouldn’t it have been a bad sign for Clinton that she was faring so poorly in such a traditionally important state? Not really, the article asserted, instead reassuring readers that Clinton’s more diverse coalition give her a greater number of paths to 270 electoral votes:

And the two parties have made strikingly different wagers about how to win the White House in this election: Mr. Trump, the Republican nominee, is relying on a demographic coalition that, while well tailored for Ohio even in the state’s Democratic strongholds, leaves him vulnerable in the more diverse parts of the country, where Mrs. Clinton is spending most of her time.

It is a jarring change for political veterans here, who relish being at the center of the country’s presidential races: Because of newer battleground states, Mrs. Clinton can amass the 270 electoral votes required to win even if she loses Ohio.

It was fine to point out that Ohio, which is generally somewhat Republican-leaning relative to the country as a whole, wasn’t a must-win state for Clinton. But the article didn’t contemplate the possibility that Clinton’s poor position in Ohio could also portend problems in Michigan, Wisconsin and Pennsylvania, which probably were must-wins for her and which, like Ohio, had plenty of white voters without college degrees. In that sense, Ohio could still be a bellwether — a leading indicator of trends elsewhere in the country and the region — even if it wasn’t likely to be the decisive state.

Instead, the Times went out of its way to assert that Ohio had lost its bellwether status, describing it as a bygone curiosity “decreasingly representative of contemporary America” whose days at the forefront of presidential politics were behind it. The Times’s deeply held conviction that the electoral map favored Clinton was impervious to whatever evidence its reporters were picking from the Buckeye State.

However, the Times’s error paralleled a major mistake made by some of the statistical models of the campaign. That’s in the tendency to treat states as being independent from one another when in fact their outcomes are highly correlated. You can make a lot of inferences about how people might vote in Michigan and Pennsylvania based on the polls in Ohio, for instance. Moreover, when the polls are in error in one state, they tend to miss in the same direction in similar states. Clinton would have to be awfully unlucky to lose Ohio and Pennsylvania and Michigan and Wisconsin, the models were saying, not recognizing that problems in any one of these states probably implied she was having problems with them across the board. Get that one assumption wrong, and you could mistakenly calculate that Clinton’s win probability was in the high 90s instead of the 70 percent range, where FiveThirtyEight’s forecast had it.

Furthermore, like their more traditional counterparts, data-friendly journalists were sometimes too quick to dismiss the implications of Clinton’s awful polling numbers in states such as and Ohio and Iowa. If Clinton was really trailing Trump by 7 percentage points in Iowa, as the final (usually highly accurate) Des Moines Register poll had said, how safe could her position be in nearby states like Wisconsin?

It would have helped to have more high-quality polls in other swing states such as Wisconsin and Michigan. (Traditional telephone polls commissioned by local newspapers have dwindled because of budget cuts.) But based on the data the public did have available, there were a lot of Electoral College warning signs for Clinton, especially after FBI Director James B. Comey’s letter to Congress on Oct. 28 — and people mostly ignored them. Clinton might have been able to win the Electoral College without Ohio, but not without the Midwest.

Chat: How’s Our Democracy Doing?

In this week’s politics chat, we check in on the health of our democracy. The transcript below has been lightly edited.

 

micah (Micah Cohen, politics editor): After Donald Trump won the election, a lot of people — journalists, academics, regular folks — raised concerns about the future of our democracy. Would Trump upend democratic norms and violate core principles? The Trump administration is only in its fifth day, so it’s way too soon to know. But we don’t want to lose sight of those bigger questions. So today we’re going to go through a checklist put together by Harvard’s Stephen M. Walt for Foreign Policy magazine in late November, offering “10 warning signs that democracy is at risk.” (Walt saw Trump as a risk on all 10.)

Again, it’s early in the Trump era — though we’ve already learned a lot about how he intends to govern from his transition, inauguration and first few days in office — but we’ll return to these questions periodically.

So, everyone on the same page? This is basically an oil check for U.S. democracy — you buy a used car and the service department takes a look before you take it home.

natesilver (Nate Silver, editor in chief): I just wanna say I took this guy’s class in college and I think I got an A-minus, so take that into account when you review my answers.

clare.malone (Clare Malone, senior political writer): A-minus? I expected more from you, Nate.

harry (Harry Enten, senior political writer): I got an A-minus once … it was an overrated experience.

clare.malone: Know what’s a failure of democracy? Annette Bening not being nominated for an Oscar this year.

micah: And to be clear, this isn’t FiveThirtyEight saying Trump will ruin American democracy — we just take a “better safe than sorry” attitude here.

natesilver: I think we’re just saying, “Is this normal?”

clare.malone: OK, let’s talk about stuff.

micah: First up, No. 1: Has Trump undertaken “systematic efforts to intimidate the media”?

natesilver: No. Period.

clare.malone: Yes!

What do you call having your press secretary at your first press conference telling a reporter to behave or else he’d revoke his press pass?

What do you call keeping reporters in pens and physically preventing them from talking to people at rallies?

natesilver: I was being sarcastic.

clare.malone: Text has no nuance. Sarcasm not detected.

micah: Oh, I actually don’t think this is clear cut.

natesilver: Really? He’s called out reporters by name, revoked and threatened to revoke access….

harry: Trump rewards good press coverage. Like he did at his first news conference. He also calls out reporters, such as Katy Tur, when they report on news he doesn’t like.

micah: All those examples are definitely bad. I’m not sure they rise to “systematic,” though.

natesilver: #slatepitches

clare.malone: What, you want him to have a handbook, Micah? “The Trump White House’s Guide to Sowing Distrust in the Press?”

natesilver: That’s not to say Trump can never, ever use carrots as well as sticks or threats. He gives a comparatively high amount of access to certain outlets.

micah: They seem more like Trump and his people have very low regard for the media and act accordingly. And they definitely try to undermine public trust in the press. But it’s harder to point to a recurring effort to intimate reporters.

natesilver: But calling out reporters on stage at rallies? That’s the very definition of intimidation.

micah: Walt gives examples like using the FCC to harass media companies and opening up libel laws.

clare.malone: Micah, someone is now using the White House platform and the seal of the president to lend credibility to their attacks on the press. You should be alarmed by that.

micah: I’m 100 percent alarmed!

Politics Podcast: The Beginning Of The Trump Presidency

 Subscribe: iTunes |ESPN App |Download |RSS |New to podcasts?

Donald Trump’s first few days as president were marked by executive orders, “alternative facts” and mass protests around the country. This week, the FiveThirtyEight politics podcast crew breaks down Trump’s inauguration speech and chats with contributor Julia Azari about what presidents can accomplish in their first 100 days. Plus, University of Denver professor Erica Chenoweth discusses the Women’s Marches, which drew more than 3 million people across the United States, and her research on the hallmarks of successful protest movements.

In other news: We’ve scheduled our first live show of 2017! Join us at the Treefort Music Festival in Boise, Idaho, on Friday, March 24th. Get your tickets here.

You can listen to the episode by clicking the “play” button above or by downloading it in iTunes, the ESPN App or your favorite podcast platform. If you are new to podcasts, learn how to listen.

The FiveThirtyEight Politics podcast publishes Monday evenings, with occasional special episodes throughout the week. Help new listeners discover the show by leaving us a rating and review on iTunes. Have a comment, question or suggestion for “good polling vs. bad polling”? Get in touch by email, on Twitter or in the comments.

The Long March Ahead For Democrats

Saturday’s Women’s Marches, which rebuked President Trump on the day after his inauguration, probably drew more than 3 million participants between hundreds of locations across the United States, making them among the largest mass protests in American history. The marches recalled the tea party protests of April 15, 2009, an event that helped to mark the beginnings of a backlash to former President Obama — but overall attendance at the Women’s Marches was about 10 times higher than at the tea party rallies, according to our estimates.

But the geographic distribution of the marches also echoed November’s election results, in which Hillary Clinton lost the Electoral College despite receiving almost 3 million more votes than Trump nationwide. About 80 percent of march attendees were in states that Clinton won, and a disproportionate number were in major cities. So if the marches were a reminder of the depth of opposition to Trump — unprecedented for a president so early in his term — they also reflected Democrats’ need to expand the breadth of their coalition if they are to make a comeback in 2018 and 2020.

Counting crowds is an inexact science, but the numbers were impressive

As FiveThirtyEight did for the tea party protests in April 2009 and for the Occupy Wall Street protests in 2011, we sought to collect credible estimates of crowd sizes at the Women’s Marches based on local news accounts. (You can find a complete accounting of our estimates and sources here.) We wanted to avoid estimates given by march participants or organizers, since these often exaggerate attendance compared with estimates by public officials such as local police and fire departments. In St. Louis, for example, police estimated the crowd at 13,000 participants, while a march organizer said 20,000 people had come.

Overall, we found 11 cities where there were separate estimates of crowd sizes given by organizers and local officials. They followed a remarkably consistent pattern: In all cases, the estimate by local officials was 50 to 70 percent as high as the one given by march organizers. Or put another way, the estimates produced by organizers probably exaggerated crowd sizes by 40 percent to 100 percent, depending on the city.

CITYESTIMATE FROM LAW ENFORCEMENT OR PUBLIC OFFICIALSESTIMATE FROM ORGANIZERSRATIONew York400,000600,0000.67Seattle120,000175,0000.69Portland, OR70,000100,0000.70St. Louis13,00020,0000.65Raleigh, NC10,00017,0000.59San Luis Obispo, CA7,00010,0000.70Sarasota, FL5,50010,0000.55Kansas City, MO5,00010,0000.50Asheville, NC6,50010,0000.65Augusta, ME5,0008,5000.59Frederick, MD5001,0000.50Women’s March organizers claimed bigger crowds than public officals

Nonetheless, it’s clear that the Women’s Marches drew huge numbers of people. For most of the largest marches, we were able to identify a crowd-size estimate from public agencies, such as a police department or a mayor’s office, or which was provided by nonpartisan experts who sought to estimate crowd sizes using photography or other techniques. Where we weren’t able to find such sources, we discounted the reported march sizes by 40 percent if they were based on estimates given by organizers or by 20 percent if a news account’s sourcing was ambiguous.

Even with this relatively cautious approach, we estimated the aggregate crowd size at 3.2 million people among the roughly 300 U.S. march sites for which we were able to find data. Our estimate of 3.2 million marchers is lower than other estimates that take organizer-provided estimates at face value, but is nonetheless an impressive figure. By comparison, using a similar technique, we estimated the tea party rallies on April 15, 2009, drew around 310,000 participants among about 350 cities. Here are what we estimate to be the largest marches:

CITYESTIMATED CROWDSOURCENOTESWashington, D.C.485,000City officials, crowd countersAverage of two sourcesLos Angeles450,000OrganizersDiscounted by 40%New York400,000City officialsBoston175,000City officialsChicago150,000OrganizersDiscounted by 40%Seattle120,000Law enforcementSt. Paul, MN95,000Law enforcementDenver90,000OrganizersAverage of two sources; discounted by 40%Madison, WI87,500Law enforcementSan Francisco80,000Unofficial law-enforcement source, media accountAverage of two soucres; discounted by 20%Portland, OR70,000City officialsOakland, CA60,000Law enforcementAtlanta60,000Law enforcementPhiladelphia50,000City officialsAustin, TX45,000Law enforcementSan Diego37,500Law enforcementAverage of two sourcesSan Jose, CA25,000Law enforcementPittsburgh25,000City officialsHouston21,000Law enforcementAverage of two sourcesSacramento, California20,000Law enforcementPhoenix18,750Law enforcement, public officialsMontpelier, VT17,500Law enforcementSaint Petersburg, FL16,000Media accountDiscounted by 20%Des Moines15,600OrganizersDiscounted by 40%Tucson, AZ15,000Law enforcementCleveland15,000Law enforcementAshland, OR15,000Law enforcementTallahassee, FL14,000Law enforcementSt. Louis13,000Law enforcementOmaha, NE13,000Law enforcementNew Orleans12,500Law enforcementSanta Ana, CA12,000OrganizersDiscounted by 40%Nashville, TN12,000Media accountsDiscounted by 20%Santa Fe, NM11,000Law enforcementHartford, CT10,000Law enforcementMiami10,000Media using crowd-counting techniquesPortland, ME10,000Law enforcementReno10,000Law enforcementIthaca, NY10,000Law enforcementCharlotte10,000Law enforcementRaleigh, NC10,000Law enforcementOlympia, WA10,000Law enforcementWhere were the biggest women’s marches?

The largest march was probably on the Capitol Mall in Washington, which was estimated at 500,000 by local officials and at 470,000 by crowd scientists contacted by The New York Times. (By a variety of metrics, attendance at the Women’s March on Saturday exceeded that at Trump’s inauguration on Friday.) But there’s some ambiguity about this. In Los Angeles, organizers claimed to turn out 750,000 people, while police and public officials didn’t put out a precise estimate. Using our 40 percent discount rate yields an estimate of 450,000 people. In New York, meanwhile, the Mayor’s Office estimated the crowd size at 400,000, while organizers put the number at 600,000. (We used the Mayor’s Office estimate.) It’s possible that any of Washington, New York and Los Angeles actually had the largest march.

In addition to L.A., there were several other major cities, such as Denver and Chicago, for which we had to rely on (discounted) estimates put forward by organizers. In some cases, we contacted officials in these cities, but they declined to provide further on-the-record guidance.

And even when there are official crowd-size estimates put forward by local governments, they are often imprecise, particularly for events like the Women’s Marches, which weren’t held in confined locations and which lasted for hours, with not all participants remaining from beginning to end. It wouldn’t greatly surprise us to learn that as few as 2 million or 2.5 million Americans participated in the Women’s Marches on Saturday or that as many as 5 million did. Either way, those are impressive numbers compared with similar events in the past.

Geographically, the marchers looked a lot like Clinton’s coalition

One of the odder sentiments we heard on Saturday was from journalists wondering aloud why all the enthusiasm they were seeing at the marches hadn’t translated into a win for Clinton. While 3 million (or so) marchers is a lot, almost 66 million Americans supported Clinton in defeating Trump in the popular vote last November. Like Clinton’s voters, however, the marchers were mostly concentrated in big cities in blue states.

Specifically, about 80 percent of march attendance came in states that Clinton won. By comparison, only slightly more than half of Clinton’s voters were in these states.

GROUPWOMEN’S MARCHES, 1/21/17TEA PARTY PROTESTS, 4/15/09Obama/Clinton states2,572,00080%102,00033%Obama/Trump states344,0001179,00025McCain/Trump states318,00010131,00042Women’s march crowds came overwhelmingly in Clinton states

Only 11 percent of marchers, by contrast, were in a key group of swing states — those that Obama won in 2008 or 2012 but which Clinton lost in 2016. (These states are Florida, North Carolina, Ohio, Pennsylvania, Michigan, Wisconsin, Iowa and Indiana.) Some 25 percent of tea party protesters on April 15, 2009, were in these swing states, by contrast.

We should be careful not to lose the context here. While a higher share of tea party participants were in swing states, a higher raw number of Women’s March participants were, because Women’s March participation was much higher overall. Nonetheless, the largest rallies were generally not in swing states (with some exceptions: about 87,500 people in Madison, Wisconsin; 50,000 in Philadelphia; and 25,000 in Pittsburgh).

Instead, participation in the rallies skewed to the West. Some 37 percent of marchers were in the Western Census Bureau Region, even though it makes up only 23 percent of the U.S. population:

REGIONWOMEN’S MARCHES, 1/21/17TEA PARTY PROTESTS, 4/15/09Northeast767,00024%24,0008South802,00025143,00046Midwest466,0001464,00021West1,199,0003781,00026Women’s marches showed Democrats’ western shift

In races for Congress, there are potential opportunities out West for Democrats. There are 23 congressional districts where Clinton defeated Trump but which elected a Republican to Congress. Of these, 10 are in the West, mostly in California. But this is not necessarily a great development for Democrats as far as presidential races go, because they already have more voters than they need in California, Oregon, Washington and Hawaii — and increasingly in Colorado and New Mexico — whereas the other states in the region are either still too red or don’t have enough electoral votes to really move the needle. Nevada is something of an exception to this, as is Arizona, although they don’t have all that many electoral votes either.

Another weakness in the Democratic coalition, as pointed out by Sean Trende and David Byler at RealClearPolitics, is that it’s increasingly concentrated in cities, a problem given that the U.S. Senate to a large degree, the Electoral College to a small degree, and the U.S. House to a greater or lesser degree (depending on how districts are drawn), all tend to give an advantage to rural areas. While marches perhaps aren’t the best way to measure the urban/rural balance in your coalition — it’s inherently easier to gather large masses in more densely populated areas — the contrast between the Women’s Marches and the tea party is nevertheless striking. Some 85 percent of the attendance at the Women’s Marches came in what Trende and Byler call large cities — those located in metro areas with populations of at least 1 million — or mega cities — metro populations of at least 5 million. By contrast, only 44 percent of tea party participants were in large cities or mega cities, as the tea party had a “long tail” of attendance in small-to-medium-sized towns, suburbs and exurbs (this would portend Trump’s strength in those areas eight years later). About 56 percent of the U.S. population is located in large cities or mega cities, so somewhere in between the Women’s March and tea party, although closer to the tea party end of the spectrum.

METRO AREA TYPEWOMEN’S MARCHES, 1/21/17TEA PARTY PROTESTS, 4/15/09Mega cities1,671,00052%46,00015Large cities1,068,0003391,00029Small and medium cities495,00015176,00056Women’s marchers were mostly in big cities, while the tea party protests were more in small towns

To be clear, it’s not a bad thing for Democrats that huge numbers of people turned out in cities to participate in these rallies. There were, for instance, many reports of people from suburban, exurban and rural areas traveling to the nearest big city to participate in a Women’s March. In many cases, moreover, the Women’s March also had strong numbers in medium-sized cities, especially in college towns, state capitals and in the West. And overall, the Women’s Marches turned out about 500,000 people outside of large cities and mega cities — more than the tea party rallies turned out in total on April 15, 2009. Democrats need to consider where their supporters are located and not just how many of them there are, and the Women’s Marches skewed toward cities overall. But they were big enough to contain hopeful signs for a Democratic resurgence in small and medium towns.

Losing an election is never a good thing, but …

At a macro level, Democrats have every right to be encouraged about the Women’s Marches. That’s because the day the presidency changes parties is often a turning point — but it can be a turning point against the incoming president’s party if the opposition plays its cards right. If history is a guide, it will suddenly become a lot easier for Democrats to win elections to Congress, statewide and local offices as voters seek to balance against Trump. The more policies Republicans enact, or threaten to enact, and the balancing instinct will become stronger. The risks are probably greater if the president is unpopular, as Trump is for the time being, although presidents who assume the office with high approval ratings aren’t immune from this phenomenon, as Obama and Democrats learned the hard way.

But this balancing doesn’t happen automatically; it requires organization and effort. In that sense, the tea party — which, like the Women’s March, had a somewhat inchoate set of policy positions and principles when it first formed — can serve as a model for Democrats. The Republicans’ huge gains in the 2010 midterms were partly the result of a massive “enthusiasm gap” in the GOP’s favor but partly also because of organization. Republicans raised a lot of money and fielded competitive House candidates in almost every swing district, even if the tea party also produced a few oddballs in Senate and gubernatorial races. Like the early tea partiers, some of the people who turned out on Saturday will turn into organizers, fundraisers and influential voices in their communities, and some of them will even become candidates for office. The Democratic Party needs broader geographic appeal than what it has right now. But turning out 3 million people one day after the new president is inaugurated is a pretty good start.

Kathryn Casteel, Ben Casselman, Blythe Terrell, Harry Enten and Micah Cohen contributed to this article.

VIDEO: The long, storied history of Inauguration Day weather