Back in December, I looked at how many votes it takes to become a Democratic Party Committeeperson. Philadelphia's Committeepeople are the foot soldiers of the Party, responsible for getting out the vote and organizing the party in the 1,686 Divisions. Each Division has 2 committeepeople, so every four years a potential 3,372 Philadelphians are elected to the post (I focus on Democrats here, though the same is true for Republicans). In 2014, 348 (10%) of those positions went completely unfilled, while another 275 of the positions were won by Write-In candidates, usually in districts with less than two candidates on the ballot.
An open question for the upcoming May Primary is whether Democrats' newfound energy will translate to the rank-and-file positions of local the local Party. Well, applications have been filed and the Commissioner's office released the official slate of candidates.. How do the numbers bode for that trickle-down energy?
The hypothetical surge in Committeeperson candidates definitely did not materialize.
The surge in candidates didn't happen
In total, there are currently 3,204 candidates on the Democratic ballot, after a number of applications were contested and rejected. That compares to 3,098 that survived to the election in 2014. The counts are from slightly different points in the process. The 2014 data uses election results of non-write-in candidates, while the 2018 uses the recently released Commissioner's data on candidates who survived potential challenges.
There are currently a total of 558 seats that have no candidate on the ballot, 61 fewer than four years ago.
Some 1,615 of those candidates are incumbents. To calculate incumbent candidates, I use fuzzy text matching on candidate names between 2014 and 2018. This tests whether two names are the same based on the fraction of characters that are different. Matching is harder than it may seem because of variability of how candidates write out their names: spellings may change, a candidate may identify as Junior in one but not another, Elizabeth may change her listed name to Betsy. Rather than manually assign incumbency, I automate the process; 've spot checked the fuzzy matching on 40 borderline matches and think I've got a good first-order approximation to incumbency assignments.
The wards with the highest number of candidates per division are in Wards 1 and 2 in Queens Village, 55 in the lower Northeast, and 46 in West Philly. The wards with the lowest include 27 and 20, which include Penn and Temple, respectively.
The most astonishing increase is in the 58th Ward in the Northeast, which has 66 more candidates in 2018 than it did in 2014. Ward 42 saw the the greatest decrease
There has not been an obvious surge in energy across the city. 34 of the 66 wards saw increases in the total number of candidates, while 29 saw a decrease.
Which Wards have the energy?
Maybe to see the energy, we need to look in specific places in the city. I often find two useful ways to break up the city: by race, and by vote in the 2016 primary. Race often captures an important axis for identity and experience in the city, while vote in the 2016 primary does two things: differentiates White wards between more establishment (Clinton voters) and less establishment voters (Sanders), and differentiates predominantly Black wards that nonetheless are in the process of gentrifying. Wards 46 and 47 neighbor Penn and Temple, respectively, and are predominantly Black Wards that voted relatively strongly for Sanders, largely because of the sizeable young White population.
There is one dimension that is not captured by the Race x 2016 primary distinction, and that is the Trumpiness of White voters. For example, many White Northeast Wards voted for Sanders, but then also swung towards Trump in the general election. This suggests that their Sanders votes may not have been a declaration of progressivism, but a vote against Clinton. Looking at Sanders-voting White wards will conflate the young progressives in the center of the city with the anti-Clinton voters of the Northeast.
For reference in the upcoming discussion, here is a map of wards' predominant race and ethnicity, calculated using the 2012-2016 American Community Survey.
Below is a plot of the average number of 2018 committeeperson candidates per division, plotted by predominant race and 2016 Primary vote. For the most part, White wards have the most candidates, followed by Black wards and then last Hispanic wards. The Black ward with the most candidates is ward 46, which is actually a rapidly gentrifying ward that Bernie almost won.
The most interesting trend is within Hispanic wards, where the trend in White and Black wards is reversed: the number of candidates on the ballot increases with vote for Clinton. Wards 7, 19, and 43 voted strongest for Clinton in the city, and have around 2 candidates per Division. I read this reversal as demonstrating that political organization is different within Hispanic wards from the others. In Hispanic wards, party organization is correlated with establishment votes, while the connection is less clear in other types of wards.
So how about the change in the number of candidates? Did this newfound energy make Bernie-loving wards mobilize committeepeople en masse?
Finally, those changes in candidates running also mean that White wards have the most non-incumbents running. Some 42% of candidates in White wards are incumbents, compared to 53% in Hispanic wards and 57% in Black wards.
What to look for in the Primary
The May 15th primary will see many new Committeepeople be seated, and decide the which Democrats run for all of the important (newly-redistricted) U.S. House and the PA State House and Senate races. The surge in energy that many predicted didn't seem to materialize in residents running for committeeperson, but the primary will give us a much better sense of who is energized where, ahead of the national November midterms (and race for governor).
I've got some exciting news planned for the primary. Stay tuned!
I've been profiling each of the new Congressional Districts created when the state Supreme Court declared the prior boundaries unconstitutionally gerrymandered. Today I'm profiling the last of the Congressional Districts in the Philadelphia area, the new District 01.
District 01 mostly aligns with Bucks County, to the Northeast and North of the city. To accomodate the equal population requirement, it adds on Montgomeryville and Hatfield in Montgomery County.
The district is the most evenly split in the Philadelphia region. It voted narrowly for Clinton in 2016, by a slim 50.7 - 49.3 margin. This was gap was two percentage points more Democratic than the state as a whole, though the District was 5.5 point *less* Democratic than the state in 2014. Bucks County provides the prime example of a suburban swing district, with traditional Republicans who swung against Trump. (Of course, the swing did not include all Republican voters by any means, but in this district a few percentage points matters.)
The district is predominantly White, and there is not a single State House District within it that is not at least a plurality White. Within that White population, there are demographic differences. The region immediately outside of Philadelphia looks a lot like an extension of the Northeast: it is the densest part of the County, and less wealthy than the County's center, around Doylestown. The lowest five statehouse districts, including Newtown, Churchville, and everything below, constitutes a whopping 46% of the population.
That 46% of the population turns out at lower rates than the rest of the District, and only represents 42% of the votes. But in a district so evely divided, subtle swings in any region with 42% of the vote (and especially a turnout increase, which is plausible in district with such low baseline turnout) can determine the election.
Despite the low turnout South of the district, the District as a whole votes at much higher rates than the state. Measured as votes per population over 18, the district voted at a rate nine percentage points more than the state in 2016, and six points more in 2014, the last race for Governor.
The 2016 Democratic Primary illustrates some interesting splits. Consider the wealthy region around Newtown and Lambertville. It has very high turnout, and was evenly split between Clinton and Trump. However, voters there *strongly* supported Clinton over Sanders. In other districts, we've seen a correlation between support for Sanders and support for Trump, which I've interpreted as an anti-establishment (or anti-Clinton, depending on your reading) sentiment. However, these wealthy voters appear to be legitimate centrists: with a slight overall Republican lean, who voted against Sanders, while also swinging slightly against Trump.
Below are the racial splits for the District, though they deserve a strong word of caution. The calculation below assigns races the weighted average of the vote in the State House districts that residents live in. In a District so heavily White, the Black, Hispanic, and Asian residents will still live in a predominantly White district, so the differences between races presented will be understated.
This wraps up the Philadelphia District Profiles. The redistricting removed the gerrymandering that was fabricating Republican Districts out of a broadly Democratic region. The result is that every one of the five compact districts in the region would have voted for Clinton in 2016, ranging from narrow victories (today's CD 01) to the Democratic strongholds in the state (CDs 02, 03). While the state as a whole still represents a disproportionate Republican overrepresentation--Republicans would have won 56% of these districts in 2016, when they won only 50% of the vote--they are dramatically closer to matching the popular vote.
Tomorrow is the special election to replace Tim Murphy in the House of Representatives. Since I've got the machinery to analyze districts, I thought I'd prep some maps to see what to expect. The election will be held using the old districts, not the Supreme Court's new districts, and in any other year the Republican would almost certainly win. Donald Trump carried it by 19.5% just 20 months ago. The district ran 18.8 percentage points more Republican than the state in 2016 and 18.3 in 2014. But recent polls imply that this race is close. I'm not going to narrate, but thought I'd share the plots I made for myself.
I'm profiling each of the State Supreme Court's new Congressional Districts in the Philadelphia area, looking at their voting behavior and their demographics. Today, the new District 04.
District 04 covers Montgomery county, in Philadelphia's suburbs. This county had been among the most gerrymandered in the state, and saw the biggest changes under the Supreme Court's map. It's a politically diverse county, and chopping it up provided a huge boon to the Republicans. It's a swing-y county, and gets national attention as a pivotal suburb that seems to be trending Democratic.
The county combines Democratic neighborhoods in the southeast with Republican neighborhoods in the northwest. However, that doesn't end up being the relevant distinction to make. The northwest neighborhoods are sparsely populated, and represent very few votes. Instead, the most important distinction is between the heavily Democratic suburbs just outside of Philadelphia--Elkins Park, Glenside, Abington--and the marginally Democratic suburbs in the center. The GOP strategy had been to waste the votes of the former by lumping them in with all-Democrat Philadelphia, while distributing the latter with Republican districts to create safe-but-not-too-safe Republican districts.
Here's how the county used to be divided. It includes Goofy's head of the famed former District 7.
The new district is reliably Democratic.
The county is predominately White and higher income. The racial exception is Norristown, and the wealth exception is the more rural area in the northwest.
Turnout in 2016 came disproportionately from the inner suburbs. That's where the population is, but also has the highest turnout per resident.
This November is a Gubernatorial election. The turnout falls, but proportionately less than in the rest of the state. It also falls less in the southeast, so those neighborhoods are *even more* important in elections for Governor.
As I've pointed out in every one of these profiles, the Trump vote closely matches the Sanders vote. The district went 59-41 for Clinton over Sanders, a bigger Clinton win than the state overall. That was largely driven by the southeast.
The racial cross-tabs are less interesting for this district than others, mostly because it's so White. Perhaps most interesting is the stability of Hillary's primary numbers across races; she doesn't seem to have done quite so well in Black neighborhoods in the county as she did in Philadelphia.
This week, I'm profiling each of the State Supreme Court's new Congressional Districts, looking at their voting behavior and their demographics. Today, the new District 05.
District 05 is the first district we're looking at that stretches outside of Philadelphia. In total, 80% of its population comees from Delaware County, 16% from Philadelphia, and 4% from Montgomery. (That area in South Philly is deceiving; much of it is industrial and has no population).
The district contains portions of Bob Brady's old District 1, which used to stretch out to Chester in order to gerrymander Democratic votes together. It is much less gerrymandered now, though still doesn't have any Republican strongholds.
Turnout for the district is high, running six percentage points higher than the state as a whole. That largely is due to the wealthiest suburbs, where 70-80% of the over-18 population votes.
They also fall off less than the rest of the state between Presidential and Gubernatorial elections.
Again, much of the interesting story of the district is in the 2016 Democratic Primary. The district voted largely for Clinton, with a pattern that we saw in other Districts: Black neighborhoods overwhelmingly supported Clinton, wealthier White neighborhoods still supported her by around 20 percentage points, and middle income White neighborhoods and students swung the hardest towards Bernie (though still ended up at close to an even split).
This district displays the largest over-representation of White voters that we've seen so far; they represent 64% of the population, but 69% of the vote in 2014. We will see if that continues in this high-attention Gubernatorial race this November.
This week, I'm profiling each of the State Supreme Court's new Congressional Districts, looking at their voting behavior and their demographics. Today, the new District 03.
The district is the most diverse of Philadelphia's, and perhaps of the state. It combines the affluent neighborhoods of Center City and Fairmount with West Philly, and then reaches up to Germantown, Chestnut Hill and Manayunk.
The demographic hodge podge of neighborhoods has one thing in common: all are Democratic strongholds. District 3 becomes the most Democratic in the state, and would have been won by Clinton in 2016 by 92-8 (yesterday's District 02 would have been second, at 75-25). It isn't just liberal, but also a Party district: Hillary beat Bernie by 64-36, also the largest margin in the state).
The only neighborhoods in which Clinton didn't beat Trump by more than 50 points were Manayunk and the northern parts of South Philly; middle income predominately White neighborhoods that share traits with Trump's base nationwide.
The votes are not evenly distributed with the population. Interestingly, the Black neighborhoods in Southwest Philly, Overbrook, and North Philly turned out strong in 2016, voting in numbers similar to their wealthier counterparts in Center City.
Those neighborhoods also fall off less between Presidential and Gubernatorial elections. The neighborhoods that vote for the President but don't for the Governor are the young, new-to-the-city neighborhoods: University City, Manayunk, and Penn's Landing/Northern Liberties. Chestnut Hill, Mount Airy, and Cedarbrook by far do the best in maintaining their voting through Gubernatorial years.
The diversity of the district played out in the 2016 primary. Manayunk, Queens Village, and University City all voted for Hillary. There's a clear racial divide, though not a complete one: all of the Black neighborhoods voted strongly for Hillary, while the White neighborhoods appear to be split, with gentrifying White neighborhoods swinging towards Bernie (thought Hillary still eked those out) and wealthier, longer-White neighborhoods voting decisively for Clinton.
Black residents are the majority of the residents of the district, and they are a similar majority of the voters. They vote the most Democratic (though everyone in the neighborhood votes D at over 87%), and supported Hillary strongly over Bernie. White, non-Hispanic residents are disproportionately more likely to vote, and thus make up more of the electorate than they do of the population, though that's mostly true in Presidential elections, when the younger neighborhoods turn out.
This week, I'm profiling each of the State Supreme Court's new Congressional Districts, looking at their voting behavior and their demographics. Today, the new District 02.
The new District 02 covers Northeast and North Philly; basically the entire city above Race/Spring Garden and East of Broad. This is a diverse swath of the City, combining some of the poorest sections of North Philly with gentrifying Fishtown, with the Trumpy "Middle Neighborhoods" in the Northeast.
Overall, the district is decisively Democratic. It voted 75-25 for Clinton in 2016, and 80-20 for Wolf in 2014. It also voted for Clinton over Sanders in the 2016 primary, 62-38, by more than the state as a whole.
That decisive Democratic 2016 victory was the function of a Democratic sweep of North Philly, combined with basically a even split between Clinton and Trump in the Northeast.
The Democratic map almost perfectly lines up with the racial Demographics. Those Trumpy neighborhoods were also the White neighborhoods (with the only exception of Northern Liberties at the bottom), while the Black and Hispanic neighborhoods voted decisively for Clinton.
The areal maps can mislead about proportionality; North Philly is *much* denser than the Northeast. Those votes carried the day. Notice that even though the Hispanic section around Erie Ave have the population density, their low voting rates mean that their votes per mile is lower than their neighboring Black neighborhoods.
Of course, 2018 is a Gubernatorial election, not a presidential election. Turnout is much lower in these elections, and different people vote. This district sees its votes fall by half, in line with the state overall.
And neighborhoods fall disproportionately too.
Among the Democrats, which neighborhoods are the Berniest? Which are the Hillary-est? While Hillary swept the District, she decisively won in the Black and Hispanic neighborhoods. This matching between Sanders strongholds and Trump strongholds plays out all over the city, and across the country.
Finally, we can cross-tabulate votes by race. We don't have voter-level results by race, so I approximate it by aggregating votes to Census Block Groups, and allocating votes within them. This isn't perfect (see Ecological Fallacy), but block groups are small enough and Philadelphia segregated enough to make this a very good proxy for how different racial groups voted. (Note, these percentages are the two-candidate vote. This mostly effects the Primary results, if Clinton won 45% to Sanders' 40%, she would have won 45 / (45 + 40) = 53% of the two-candidate vote).
White Non-Hispanic residents in the district are slightly over-represented among voters (43% of votes versus 40% of the population), and voted the least Democratic (though still being far from Republican).
Last weekend, the State Supreme Court announced the new Congressional boundaries for the 2018 election. Even though the GOP immediately challenged them in federal court, these boundaries appear fairer than any of the other maps proposed--by Republicans or Democrats. (NB: I purely define "fairness" as producing districts with partisanship close to the popular vote. I think compactness and county alignment are well-meaning but bad standards).
This week, I'll be digging into each of the districts in the Philadelphia area, looking at their map, their voting behavior, and their demographics. But first, here are some high-level summaries of the Court's districts. I'm not going to narrate, but mostly planting the images here for posterity. (Note, these were tweeted out by the @sixtysixwards twitter account. Follow that for the hottest real-time analysis.)
Governor Wolf has responded to the GOP's proposed congressional districts by proposing a map of his own. How does it compare?
The districts are compact (as were the GOP districts), but treat Philadelphia and suburbs very differently from the GOP's map, and slightly reduces the wasted vote gap between parties.
To see how Wolf's districts would change congressional voting, below is a plot of the current districts' results in the 2016 Presidential Election, and what it would have been under the proposed districts.
Similar to the GOP's map, Wolf's largely preserves districts' current partisanship. But there are notable exceptions.
District 6, in Delaware and Chester county voted barely for Clinton in 2016, 48.1% to 47.6%. Under the GOP's districts, it would have been a Trump 52-48 win (I do all of my projections using only the two-party vote). Under Wolf's districts, it would have been a Clinton 56-44 win.
Wolf's plan also changes District 15, which covers Reading and Allentown, from Republican to Democratic. In doing so, it makes Bucks County's District 8 more Republican; the district narrowly crosses from Blue to Red in the 2016 vote tally.
District 7, Patrick Meehan's district that the GOP plan sacrifices, similarly becomes a Democratic stronghold under Wolf's plan. That's the comically gerrymandered "Goofy kicking Donald" district, and any redistricting that values compactness will almost certainly swing it hard to the left.
Wolf's map also makes a number of Republican districts much safer. Districts 12 and 16 move from 10-point Republican wins to over 20-point wins, with only District 18 swinging from a 27-point Republican win to a 14-point win.
Overall, Wolf's map brings districts closer to 50-50 splits. And in doing so, it moves one district from Republican to Democratic. The current map has 12 districts that voted for Trump, 6 that voted for Clinton. The GOP's maintains the exact same split. Wolf's map would shrink that slightly to 11-7, or 61% Republican. This in a state that voted 50-50, with Donald Trump winning by less than a percentage point.
So what are we to do? Wolf's map may be as fair as we can expect while being tied to outdated notions of geographical representation and compactness. Maybe, some day, proportional representation.
Pennsylvania Republicans submitted a new map of proposed Congressional Districts to Governor Wolf on Friday. He has until Thursday to approve it and send it to the State Supreme Court.
I've downloaded the boundaries from pubintlaw, and created an interactive map. In order to project how each district would perform, I've aggregated the results of the races for President in 2016 and Governor in 2014. Let's dig in.
You can visit the full-scale interactive maps here.
The GOP's proposal clearly creates compact boundaries that align with county boundaries much more often. While this is what most people focus on with gerrymandering, I think the compactness standard is nonsense: it is completely possible to waste a party's votes with compact boundaries if perniciously drawn. In fact, the concentration of Democrats in cities means that even naive compact districts will almost certainly favor Republicans.
The new districts maintain the exact same Republican advantage as the prior ones. To assess this, let's look at the outcome of the 2016 Presidential election. Donald Trump narrowly won Pennsylvania, with 48.2% of the vote to Hillary Clinton's 47.5%. However, he won 12 of the Congressional Districts to Clinton's 6 (and in total 13 Republican House members won to Democrats' 5). This imbalance between topline vote and district count was achieved by packing Democrats all into a few districts, to waste their votes in landslide elections, leaving comfortable but not wasteful Repubican wins in the rest of the state.
With respect to the 2016 Presidential election, the new boundaries look a lot like the old ones:
Before we look at the district, notice the asymmetric skew between Republicans and Democrats. Republicans don't have a single district where they won by more than 50 points (thereby wasting their votes); Democrats have two. Given this, Trump would still have won 12 of the 18 districts under the proposed boundaries. The Democrats are still given the two most wasteful districts: PA-01 and PA-02, both in Philadelphia. They would continue to comfortably win PA-14, Pittsburgh, and PA-13, in Northeast Philadelphia.
District PA-07 swings hard to the Democrats. That district, famously gerrymandered as "Goofy kicking Donald," is a convenient sacrifice for Republicans as Representative Pat Meehan has already stepped down from the race amidst sexual misconduct allegations.
By sacrificing PA-07, Republicans make PA-06 a more likely Republican seat. The district, covering the farther-West Philadelphia suburbs, had been narrowly won by Clinton, but would now be a 4.4% Trump win.
PA-08 remains the most evenly split district. It covers the suburbs to Philadelphia's Northeast: Doylestown, Newtown, et al. It was and would remain essentially 50-50. Clinton would have won it by the slimmest of margins in 2016.
A strong Democratic 2018 could still swing seats. Districts 12 and 17 would have been Trump wins by 10 percentage points under these boundaries. These are the types of seats that we would expect to see competitive in a Democratic wave election. In fact, the logic of gerrymandering may mean that wave elections have more power: gerrymandered seats should be safe but not too safe, to avoid wasting votes, which may put a lot of them in play in a 10-20% Democratic swing.
But we shouldn't lose sight of just how troubling the baseline assumption in that logic is: Democrats basically need a wave election just to break even. In the dead-even state-wide election of 2016, Republicans won 13 seats to Democrats' 5 (Trump won only 12; another district split). Just because Democrats may be able to overcome the disadvantage to barely break even doesn't mean that the districts are fair.
Just to check that 2016 wasn't a fluke, here is the same plot for the 2014 Governor's race.
The Governor results are all shifted more Democratic; Wolf won the state with 54.9% of the vote to Corbett's 45.1%. Despite the rout, Corbett *won more* congressional districts: he won more than half the vote in 10 of 18 districts. The proposed boundaries do nothing to change that. PA-15, representing Allentown, becomes much more Democratic while PA-06 again becomes much more Republican.
The wasted votes are particularly breathtaking here: Corbett wins 10 of the 18 seats in both scenarios despite losing by 10% overall. And his largest win in a single district is by 18% in the new PA-04; Democrats would win by that much in *four* districts. Their votes are being concentrated, and wasted.
A note about my methodology:
To predict results within the new boundaries, I need to rely on data calculated from previous boundaries.
I am using election data from the amazing folks at openelections.org. I begin with election results at the smallest available unit of geography, the State House Districts. When a district is entirely contained within one of the new Congressional Districts, I simply add the votes. When the state house district is split between two or more of the congressional districts, I allocate its votes based on the 2010 census population-over-age-18 of the overlapping areas. Often, analyses apportion these voters based on area, but I expect using population-weighted measures to be much more accurate. Code available upon request (or once I organize my github repository).