Getting the exact right voters in a District

Information specific to the WA state VRDB

In the WA VRDB, the City column may give the postal office associated with that voter; but if it’s an unincorporated precinct, they may not be able to actually vote in that city’s election. In other words, “City=Renton” gives 79k people, but nearly 25k are unincorporated and can’t actually vote.

In addition, individuals may provide the wrong value for City, which could be wrong.

Fortunately, the VRDB has a separate table, DistrictLookup, that specifies exactly the precincts for a given (DistrictType,DistrictName) pair.

So (DistrictType=”City/Town” and DistrictName=”City of Renton”) would give you the actual precincts for Renton City Council, which you can then join and compare with the VRDB to get the list of voters … which is around 50k voters. However, that query is much cumbersome to provide!

When using the query portal, Use the “DistrictTypeCity” field to select just voters in a city.

(DistrictTypeCity == XXX) corresponds to a join with the DistrictLookup table and (DistrictType== “City/Town” and DistrictName ==XXX)

There are similar new fields for supporting other DistrictTypes, such as School, Fire, Port, Other, etc.

 

Some Examples

1 City of Renton

When queried, this gives 79k voters as a result, which includes unincorporated areas that can’t vote in a Renton City Council race, but are still categorized under Renton for mailing purposes.

 

2 DistrictType Renton

This query will give just the Renton voters, and results in a list of 53k voters.

 

3 Renton Mailing Area

This  query shows you the voters in the Renton mailing area, but can’t vote in a Renton City Council race (which results in a list of roughly 26k voters).

 

Other trivia:

  1. Some voters may match multiple “DistrictType=City/Town”. For example, Tacoma is split into multiple districts, so a voter in Tacoma district 2 would match “CITY OF TACOMA” and “CITY TAC-2”.
  2. Some cities put their districts in “DistrictType=Other” instead of City/Town. It’s arbitrary.
  3. DistrictNames in the VRDB are not normalized. This isn’t really an issue for cities, but can be an issue for other districts. Each county can report it their own way. Sometimes that just means a capitalization difference, but here the different ways that CD 5 shows up:
    • Congressional District 5
    • CONG 05
    • Congressional District – 05
    • CONGRESSIONAL DISTRICT – 005
    • CONGRESSIONAL DISTRICT – 5
    • CONGRESSIONAL 5

Partisan divide widening dramatically in Olympia

For the past few years I’ve posted on our interactive online tool that analyzes the partisan distribution of our state legislature.  The goal is to call out members with the courage to vote independently of their caucus.  Often candidates will run as moderate or independent during the campaign, but we find that their floor votes in Olympia are right down party lines.  This tool provides some transparency into their actions, versus their intent.

http://www.whipstat.com/Projects/Records

If you recall, the methodology is simple:  The partisanship score for each floor vote is calculated as the percentage of Republican supporters minus the percentage of Democrat supporters, giving each a range from 100 (exclusively Republican) to -100 (exclusively Democrat) with unanimous votes scoring zero.  The member’s aggregate score is just the average of all the scores of floor votes they supported, minus the scores from those they opposed.

Looking back to 2003, we see a relatively normal distribution curve for both parties.  And while there isn’t as much overlap in the middle as there’s been in generations past, we do see that there are moderates on both sides of the aisle and even some true independents that have represented us in Olympia.

Partisan Leaderboard - All Policy Areas, Both Chambers (2013-2020)

It is interesting to note that during this time period the most independent members have run as Republicans and that Democrats are generally much less likely to vote against their party.  You can also easily identify the three members who have switched caucuses.

So now, consider the 2019 legislative session results:

Partisan Leaderboard - All Policy Areas, Both Chambers (2019-2020)

Notice a problem?

Both parties are now considerably more partisan and there are no independents (or arguably even moderates) left in the state legislature.

So how has this changed over time?  Let’s take a look…

Partisan Distribution by Party (2003-19)

In the above graph, range lines show a standard deviation above and below the mean.  Markers represent the median value.  The bars in the center represent the party balance, which has almost always favored Democrats.

What can we conclude?

  • Both parties have trended more partisan during this time period.
  • The median tends to consistently fall the left of the caucus mean with Democrats.
  • Democrats are now over twice as partisan as they were in 2003-04 under Gov. Gary Locke.
  • The partisan divide is almost twice as wide now as it was in 2007-08, when the Democrats had a 42 seat advantage.

Wrap-Up

This “death of the middle” I see as a unhealthy development for our state (and not just because I was one of the moderates unseated with this wave of political polarization).  Compromise is a necessary part of the political process, and we need moderates on both sides of the aisle willing to bridge the divide to find common ground.  During the 5 years there was divided control of the legislature, it admittedly took much longer to hammer out bipartisan agreements…but the resulting work product was worth it.  Our bipartisan budgets typically passed with 90% support, while only 57% voted for this last biennial budget (including no Republicans and not even every Democrat).

Clearly, changes are needed.

How partisan are WA organizational donors?

In previous posts we’ve looked at how our political system has become increasingly polarized, with our analysis of voting records showing that many self-styled moderates and independents are exhibiting much more partisan behavior when voting on the House or Senate floor.  Having served for a few years now on a PDC open data advisory group, I realized that the same type of analysis could be done for organizational donors.  Despite this being public data, not many people in Washington state know who the biggest political donors are, much less who they support.

So, are many of these “non-partisan” or “bi-partisan” organizational donors more partisan than they let on?

We can figure this out, and the methodology is pretty simple.  The PDC Open Data Portal publishes all contributions to candidates and political committees back to 2008.  For this first analysis, we looked at donations to partisan legislative and statewide candidates from businesses, unions and political action committees.  The partisanship score for each donor is the difference in percentage of donations by party, giving each a range from 100 (exclusively Republican) to -100 (exclusively Democrat).

Most of the effort here is involved with the fuzzy matching algorithm, since candidates are very inconsistent on how they report the names of these organizations to the PDC.  I use a trigram matching method, which isn’t perfect…but it does pretty well.  Currently, contributions are grouped under the same donor if 80% or more of the trigrams match, but this is adjustable.

Here are the results:

Partisan Donors (2008-18)

If you visit WhipStat.com, you’ll now find an interactive and animated version of our organizational donor partisan analysis that allows you to filter by jurisdiction type and date range.

Filters

If you’d like to do further analysis, feel free to hit the Download button for a tab-delimited table of the charted data.  Note that for now we don’t display or download the complete donor dataset, as that includes over 8,000 organizations.

A few things become apparent when reviewing the results:

  • Some of the biggest legislative donors give heavily to candidates from both parties.
  • About 6% more is given to Democrats than Republicans in legislative races, but that increases to 28% when looking at statewide races.

Up next:  We’ll take a close look at hard money vs. soft money contributions.

Why should you save your data back to the cloud

A major benefit of a mobile canvassing app is that your work is automatically recorded. However,  it’s common for people to export their data to another system and work off that; or print out their lists and work off a printed walk list. In those cases, be sure to update your data in TRC afterwards! When using paper lists, here’s why it’s worth the extra effort to save your results back to TRC:

 

1. Ensure your data is saved and secure

Paper can get lost or stolen.  Whereas data in TRC is safe and secure. It’s saved on the cloud and TRC’s sandbox model guarantees that your data will never get accidentally overwritten.

2. Easy sharing with other campaigns

Once your data is in TRC, it’s easy to conditionally share portions of it with other campaigns. For example, suppose you’re running for a city council race which overlaps another schoolboard race. TRC can automatically figure out just the overlapping records and just share those. That analysis is hard to do with paper.

Furthermore, suppose you’re canvassing team is asking three separate questions and you only want to share results from one of the questions. Again, once your data is in TRC, you can easily do that controlled granular sharing.

3. Make sure you don’t double-contact the same people.

Updating the data on the server ensures your campaign doesn’t accidentally contact the same person multiple times, especially when you have multiple canvassers operating independently.  Accidentally contacting the same people multiple times would be wasting resources and could also be perceived as harassment.

4. Enables searching for patterns and identifying new supporters

Knowing your specific supporters lets us run predictive analytics to identify other potential supporters.  For example, suppose your district has 50,000 voters. If your canvassing activity identities 200 supporters and another 100 non-supporters, we can then use analytics to search for patterns. Perhaps you’re doing well among certain issues, we can then use predictive analytics to find new likely supporters that are also interested in those issues. That can further refine your target.

5. Get GOTV reporting

TRC provides campaign-wide reports for Get-out-the-vote and election predictions. In 2016, these reports were frequently 99% accurate for legislative district races. The more data you provide back to TRC, the more accurate predictions and reports it can provide back you.

The TRC Sandbox

The TRC canvassing app is sitting in front of a powerful general-purpose service for sharing tabular data files like CSVs.

This provides:

  1. Integrations – a means to two-way sync that tabular data with external data sources (like NationBuilder, Salesforce, Google sheets, dropbox, etc)
  2. User-management – you can share out a sheet with users, track per-user activity, and revoke permissions.
  3. Source Control – TRC provides both branching and full history tracking. Branching means you can create a “child” sheet that has a subset view of the “parent” sheet. Full history tracking means you can track every change.
  4. A compute engine – TRC has a general compute fabric for process joins, merges, and aggregations on your data.

Sandbox and Isolation

Each campaign gets its own isolated view of the data, which we call a “sandbox”.  This means that two candidates can running against each other for the same position against each other in a primary,

Sandboxes can then be further partitioned among your volunteers.

trc-overview

For example, R1…R5 are individual records.   User U1 is synchronizing the data with some external data source, such as NationBuilder or Salesforce.  S1 refers to U1’s sandbox.

U1 then shares out subsets of the sheet with volunteers on the campaign.  This creates a new sandbox S2 for User U2, which has access to rows R3,R4. And another new sandbox, S3, for users U5,U6,U7 which get access to R1 and R2.  Since U5,U6, U7 are in the same sandbox (S3), they can see each other’s changes.

The system is a distributed hierarchy, so any operation U1 can do in S1; U2 can do in S2. U2 is fully empowered within their sandbox! So U2 can divide their own sandbox and create a new sandbox for U3 and U4 to each edit R4.  Since U3 and U4 each have their own sandbox (in contrast to U5,U6,U7 who all share a sandbox),  U3 and U4 can edit the same record without conflicting with each other.   Their parent (U2) can then resolve any conflict.

This has several benefits:

  1. It allows multiple candidates to run against each other in a primary. They each get their own sandbox.
  2. Within a sandbox, it ensures that your data is never overwritten.
  3. It allows an untrusted people to submit data to your campaign. The data is just quarantined in its own sandbox and not integrated until proven safe.
  4. The full audit log allows purging bad data even after an integration.

Analyzing the WA Political Spectrum

It’s no secret that our political system has become increasingly polarized in recent years.  In fact, Pew Research regularly publishes studies on the topic and the situation is perhaps more grim than you might think.  Looking back over the past 60 years, Congress has never been so politically divided, and the result is D.C. gridlock.

So how bad is the situation here in Washington State?

After serving two terms now in the House of Representatives and being elected to caucus leadership, I have my opinions.  There’s certainly evidence to support the assertion that the Legislature is doing much better than Congress, but the partisan divide is alive and well in Olympia.  Rather than rely on anecdotal evidence, I was inspired by what Pew and others have done and set out to quantify the problem.

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A couple of weeks ago I published my first analysis of the partisan distribution of the Washington State Legislature.  It also included a Partisan Leaderboard, calling out the members who are least and most likely to cross the aisle.

The methodology is simple:  The partisanship score for each floor vote is calculated as the percentage of Republican supporters minus the percentage of Democrat supporters, giving each a range from 100 (exclusively Republican) to -100 (exclusively Democrat) with unanimous votes scoring zero.  The member’s aggregate score is just the average of all the scores of floor votes they supported, minus the scores from those they opposed.

This approach is different than many other studies like the McCarty & Shor (2015) Measuring American Legislatures Project, which use the Political Courage Test (former National Political Awareness Test).  Theirs are based on subjective questionnaires, while our scores are based on recorded floor votes.

Now we’ve taken this analysis to the next level…

Screenshot

If you visit WhipStat.com, you’ll now find an interactive and animated version of our partisan analysis that allows you to filter by policy area, chamber and date range.  Each member is “stacked” in a histogram, allowing you to roll over the chart and see more detailed information in tooltips.  Also, the median Democrat and Republican scores are indicated as vertical lines.  (Technically, the median is more meaningful than the average for these scores, with half the members being above and half below the line.)

And finally, this updated analysis includes floor votes on amendments, so the scores may be slightly different than those previously published.

Capture

If you’d like to do further analysis, feel free to hit the Download button for a tab-delimited table of the charted data.

A few things become apparent when reviewing the results:

  • Democrats are typically over twice as partisan as Republicans, and even more so in years when there was divided control of the House and Senate.
  • The majority party will control the floor agenda, and so will exhibit more “cohesion” and be less likely to allow members to cross the aisle.
  • The Democrat-controlled House was over twice as likely than the Republican-controlled Senate to bring bills to the floor that were rejected by the opposing party.
  • Some members show willingness to regularly cross the aisle for specific policy areas that are important to them or their constituents.  Lobbyists and advocates should take note of these policy areas.

Conclusion

Our goal here is simple:  To provide some transparency into partisan behavior in our state legislature.

There’s nothing inherently wrong with being a partisan voter, and one could argue that a certain degree of caucus cohesion is necessary to be a functioning majority.  However, many constituents elected their representatives with the expectation that they would exercise independent thought and work aggressively across the aisle to get results.  What they may discover looking at this data is that some of their representatives are more loyal to their partisan ideology than they are to a process that involves compromise to find common ground.  Given the example being set in Washington D.C., I also think we should take this moment to recognize those members on both sides of the aisle with the courage to break the partisan gridlock and work in the best interests of our entire state.  If you consider yourself an independent, these members deserve your support.