Religious nones vote overwhelmingly for Obama in 2012 presidential election

A number of commentators have pointed out the advantage for President Obama among the religious “nones,” people who have no religious affiliation who now make up almost 20% of the US population, in the 2012 election. Here is another look at the voting gap:

— In Ohio, Obama lost the Protestant vote by 3 points and the Catholic vote by 11, but he won the “nones” — 12 percent of the state’s electorate — by 47 points.— In Virginia, Obama lost Protestants by 9 points and Catholics by 10 points, but won 76 percent of the “nones,” who were 10 percent of the electorate.

— In Florida, Obama lost Protestants by 16 points and Catholics by 5 points, but captured 72 percent of the “nones.” They were 15 percent of the electorate.

Similar results were seen in states including Michigan, New Hampshire and Pennsylvania…

Nationally, Obama lost the Protestant vote by 15 points, won the Catholic vote by 2 points, and captured 70 percent of the “nones.”

If the late 1970s and 1980s were about the rise of conservative religious voters, the Moral Majority and all that, are the 2010s going to be about the rise of the “nones”? While the article cautions at the end that religious switching is common in the United States, I haven’t seen commentators or political types address this question: how could Republicans change their pitch to attract more of the “nones”?

Argument: individualistic political arguments don’t work in cities since they require contributing to the “public good”

After looking at the Democratic vote advantage in cities for the 2012 election, here is an argument about why individualistic political arguments don’t work in cities:

If Republicans are ever going to earn real votes in cities in the future, though, they’ll have to do more than just talk about them differently. The real problem seeps much deeper. As the Republican Party has moved further to the right, it has increasingly become the party of fierce individualism, of “I built that” and you take care of yourself. Cities, on the other hand, are fundamentally about the shared commons. If you live in a city and you think government – and other people – should stay out of your life, how will you get to work in the morning? Who will police your neighborhood? Where will you find a public park when your building has no back yard?

In a good piece on the GOP’s problem with geography earlier this week, The New Republic’s Lydia DePillis interviewed Princeton Historian Kevin Kruse, who made this point succinctly: “There are certain things in which the physical nature of a city, the fact the people are piled on top of each other, requires some notion of the public good,” he said. “Conservative ideology works beautifully in the suburbs, because it makes sense spatially.”

The real urban challenge for conservatives going forward will be to pull back from an ideology that leaves little room for the concept of “public good,” and that treats all public spending as if it were equally wasteful. Cities do demand, by definition, a greater role for government than a small rural town on the prairie. But the return on investment can also be much higher (in jobs created through transportation spending, in the number of citizens touched by public expenditures, in patents per capita, in the sheer share of economic growth driven by our metropolises).

Density makes all of these things possible, and it requires its own kind of politics. There’s no reason why the Democratic Party should have an exclusive lock on this idea. Investing government money efficiently – as Republicans want to do – is also about focusing on how it’s spent in cities. While Republicans are mulling this over in the next four years, it may help to look at Howard’s map. What is going on in those dark blue dots? What does it mean to live in those places – and to live there and hear from politicians that “government should get out of the way?”

This reminds me of some of the observations of early sociologists about the transition from more rural village and farm life to urban life in the late 1800s and early 1900s. Cities aren’t just different because there are more people who are living and working closer together; this changes the social interactions (think of Simmel’s talk of the blase attitude in cities) as well as the social interdependence (think of Durkheim’s discussion of the division of labor).

One way Republicans could positively argue about cities: along with their surrounding metropolitan regions, cities are economic engines. A thriving economy needs thriving firms in these regions that encourage innovation, provide jobs, and interact with and operate in nearby communities.

Are there cities that are more individualistic than others? Can you have a global city that has a more individualistic ethos?

The real question after the 2012 presidential election: who gets Obama’s database?

President Obama has plenty to deal with in his second term but plenty of people want an answer to this question: who will be given access to the campaign’s database?

Democrats are now pressing to expand and redeploy the most sophisticated voter list in American political history, beginning with next year’s gubernatorial races in Virginia and New Jersey and extending to campaigns for years to come. The prospect already has some Republicans worried…

The database consists of voting records and political donation histories bolstered by vast amounts of personal but publicly available consumer data, say campaign officials and others familiar with the operation, which was capable of recording hundreds of fields for each voter.

Campaign workers added far more detail through a broad range of voter contacts — in person, on the phone, over e-mail or through visits to the campaign’s Web site. Those who used its Facebook app, for example, had their files updated with lists of their Facebook friends along with scores measuring the intensity of those relationships and whether they lived in swing states. If their last names seemed Hispanic, a key target group for the campaign, the database recorded that, too…

To maintain their advantage, Democrats say they must guard against the propensity of political data to deteriorate in off years, when funding and attention dwindles, while navigating the inevitable intra-party squabbles over who gets access now that the unifying forces of a billion-dollar presidential campaign are gone.

The Obama campaign spent countless hours developing this database and will not let it go lightly. I imagine this could become a more common legacy for winning politicians than getting things done while in office: passing on valuable data about voters and supporters to other candidates. If a winning candidate had good information, others will want to build on the same information. I don’t see much mention of one way to solve this issue: let political candidates or campaigns pay for the information!

What about the flip side: will anyone use or want the information collected by the Romney campaign? Would new candidates prefer to start over or are there important pieces of data that can be salvaged from a losing campaign?

Mapping secessionist petitions by county as well as looking at gender

A sociologist and a graduate seminar took data from petitions for secession from the United States as listed on whitehouse.gov and mapped the patterns. Here is the map and some of the results:

While petitions are focused on particular states, signers can be from anywhere. In order to show where support for these secession was the strongest, a graduate seminar on collecting and analyzing and data from the web in the UNC Sociology Department downloaded the names and cities of each of the petition signers from the White House website, geocoded each of the locations, and plotted the results.

In total, we collected data on 862,914 signatures. Of these, we identified 304,787 unique combinations of names, places and dates, suggesting that a large number of people were signing more than one petition. Approximately 90%, or 275,731, of these individuals provided valid city locations that we could locate with a US county.

The above graphic shows the distribution of these petition signers across the US. Colors are based proportion of people in each county who signed, and the total number of signers is displayed when you click or hover over a county.

We also looked at the distribution of petition signers by gender. While petition signers did not list their gender, we attempted to match first names with Social Security data on the relative frequency of names by sex. Of the 302,502 respondents with gendered names, 63% had male names and 38% had female names. This 26 point gender gap is twice the size of the gender gap for voters in the 2012 Presidential election. For signatures in the last 24 hours, the gender gap has risen to 34 points.

So it looks like the petition signers are more likely to be men from red states and more rural counties. On one hand, this is not too surprising. On the other hand, it is an interesting example of combining publicly available data and looking for patterns.

Three changes that come with “The Rise of Poll Quants”

Nate Silver isn’t the only one making election predictions based on poll data; there are now a number of “poll quants” who are using similar techniques.

So what exactly do these guys do? Basically, they take polls, aggregate the results, and make predictions. They each do it somewhat differently. Silver factors in state polls and national polls, along with other indicators, like monthly job numbers. Wang focuses on state polls exclusively. Linzer’s model looks at historical factors several months before the election but, as voting draws nearer, weights polls more heavily.

At the heart of all their models, though, are the state polls. That makes sense because, thanks to the Electoral College system, it’s the state outcomes that matter. It’s possible to win the national vote and still end up as the head of a cable-television channel rather than the leader of the free world. But also, as Wang explains, it’s easier for pollsters to find representative samples in a particular state. Figuring out which way Arizona or even Florida might go isn’t as tough as sizing up a country as big and diverse as the United States.”The race is so close that, at a national level, it’s easy to make a small error and be a little off,” Wang says. “So it’s easier to call states. They give us a sharper, more accurate picture.”

But the forecasters don’t just look at one state poll. While most news organizations trot out the latest, freshest poll and discuss it in isolation, these guys plug it into their models. One poll might be an outlier; a whole bunch of polls are likely to get closer to the truth. Or so the idea goes. Wang uses all the state polls, but gives more weight to those that survey likely voters, as opposed to those who are just registered to vote. Silver has his own special sauce that he doesn’t entirely divulge.

Both Wang and Linzer find it annoying that individual polls are hyped to make it seem as if the race is closer than it is, or to create the illusion that Romney and Obama are trading the lead from day to day. They’re not. According to the state polls, when taken together, the race has been fairly stable for weeks, and Obama has remained well ahead and, going into Election Day, is a strong favorite. “The best information comes from combining all the polls together,” says Linzer, who projects that Obama will get 326 electoral votes, well over the 270 required to win. “I want to give readers the right information, even if it’s more boring.”

While it may not seem likely, poll aggregation is a threat to the supremacy of the punditocracy. In the past week, you could sense that some high-profile media types were being made slightly uncomfortable by the bespectacled quants, with their confusing mathematical models and zippy computer programs. The New York Times columnist David Brooks said pollsters who offered projections were citizens of “sillyland.”

Three things strike me from reading these “poll quants” leading up to the election:

1. This is what is possible when data is widely available: these pundits use different methods for their models but it wouldn’t be possible without accessible data, consistent and regular polling (at the state and national level), and relatively easy to use statistical programs. In other words, could this scenario have taken place even 20 years ago?

2. It will be fascinating to watch how the media deals with these predictive models. Can they incorporate these predictions into their typical entertainment presentation? Will we have a new kind of pundit in the next few years? The article still noted the need for these quantitative pundits to have personality and style so it their results are not too dry for the larger public. Could we end up in a world where CNN has the exclusive rights to Silver’s model, Fox News has rights to another model, and so on?

3. All of this conversation about statistics, predictions, and modeling has the potential to really show where the American public and elite stands in terms of statistical knowledge. Can people understand the basics of these models? Do they simply blindly trust the models because they are “scientific proof” or do they automatically reject them because all numbers can be manipulated? Do some pundits know just enough to be dangerous and ask endless numbers of questions about the assumptions of different models? There is a lot of potential here to push quantitative literacy as a key part of living in the 21st century world. And it is only going to get more statistical as more organizations collect more data and new research and prediction opportunities arise.

Correlation and not causation: Redskins games predict results of presidential election

Big events like presidential elections tend to bring out some crazy data patterns. Here is my nomination for the oddest one of this election season: how the Washington Redskins do in their final game before the election predicts the presidential election.

Since 1940 — when the Redskins moved to D.C. — the team’s outcome in its final game before the presidential election has predicted which party would win the White House each time but once.

When the Redskins win their game before the election, the incumbent party wins the presidential vote. If the Redskins lose, the non-incumbent wins.

The only exception was in 2004, when Washington fell to Green Bay, but George W. Bush still went on to win the election over John Kerry.

This is simply a quirk of data: how the Redskins do should have little to no effect on voting in other states. This is exactly what correlation without causation is about; there may be a clear pattern ut it doesn’t necessarily mean the two related facts cause each other. There may be some spurious association here, some variable that predicts both outcomes, but even that is hard to imagine. Yet, the Redskins Rule has garnered a lot of attention in recent days. Why? A few possible reasons:

1. It connects two American obsessions: presidential elections and the NFL. A sidelight: both may involve a lot of betting.

2. So much reporting has been done on the 2012 elections that this adds a more whimsical and mysterious element.

3. Humans like to find patterns, even if these patterns don’t make much sense.

What’s next, an American octopus who can predict presidential elections?

Sociologist defends statistical predictions for elections and other important information

Political polling has come under a lot of recent fire but a sociologist defends these predictions and reminds us that we rely on many such predictions:

We rely on statistical models for many decisions every single day, including, crucially: weather, medicine, and pretty much any complex system in which there’s an element of uncertainty to the outcome. In fact, these are the same methods by which scientists could tell Hurricane Sandy was about to hit the United States many days in advance…

This isn’t wizardry, this is the sound science of complex systems. Uncertainty is an integral part of it. But that uncertainty shouldn’t suggest that we don’t know anything, that we’re completely in the dark, that everything’s a toss-up.

Polls tell you the likely outcome with some uncertainty and some sources of (both known and unknown) error. Statistical models take a bunch of factors and run lots of simulations of elections by varying those outcomes according to what we know (such as other polls, structural factors like the economy, what we know about turnout, demographics, etc.) and what we can reasonably infer about the range of uncertainty (given historical precedents and our logical models). These models then produce probability distributions…

Refusing to run statistical models simply because they produce probability distributions rather than absolute certainty is irresponsible. For many important issues (climate change!), statistical models are all we have and all we can have. We still need to take them seriously and act on them (well, if you care about life on Earth as we know it, blah, blah, blah).

A key point here: statistical models have uncertainty (we are making inferences about larger populations or systems from samples that we can collect) but that doesn’t necessarily mean they are flawed.

A second key point: because of what I stated above, we should expect that some statistical predictions will be wrong. But this is how science works: you tweak models, take in more information, perhaps change your data collection, perhaps use different methods of analysis, and hope to get better. While it may not be exciting, confirming what we don’t know does help us get to an outcome.

I’ve become more convinced in recent years that one of the reasons polls are not used effectively in reporting is that many in the media don’t know exactly how they work. Journalists need to be trained in how to read, interpret, and report on data. This could also be a time issue; how much time to those in the media have to pore over the details of research findings or do they simply have to scan for new findings? Scientists can pump out study after study but part of the dissemination of this information to the public requires a media who understands how scientific research and the scientific process work. This includes understanding how models are consistently refined, collecting the right data to answer the questions we want to answer, and looking at the accumulated scientific research rather than just grabbing the latest attention-getting finding.

An alternative to this idea about media statistical illiteracy is presented in the article: perhaps the media perhaps knows how polls work but likes a political horse race. This may also be true but there is a lot of reporting on statistics on data outside of political elections that also needs work.