Members of Congress nowadays use numerous tools to inform the voting public about their opinions and activities. They tweet, post on Facebook, and send email updates. And they also use GovTrack, in a variety of ways.

Some Members take advantage of the feeds our site offers, and embed them as a widget on their webpage. Reps. Adam Kinzinger (R-IL) and Marcia Fudge (D-OH), for example, display their voting record using GovTrack’s feed of role call votes.

Many representatives provide links to GovTrack for bills they have introduced or cosponsored. Thus, Rep. Janice Hahn (D-CA) and Rep. Kevin Yoder (R-KS) have linked to GovTrack in their press releases, while Rep. Charles Boustany (R-LA) and Rep. Tim Ryan (D-OH) have linked to the site in online summaries of their legislative work.

However, what Members of Congress use GovTrack for more than anything else is our district maps. These zoomable maps, based on data from the U.S. Census and reflecting the most recent round of redistricting, are featured on more than 70 official websites of Members of Congress, such as Reps. Michael Capuano (D-MA) and Blake Farenthold (R-TX). The maps allow voters to verify that they belong to a particular lawmaker’s district and see what else the Congressional district includes at an unparalleled level of detail.

We tend to think of ordinary citizens as the primary target audience of GovTrack, whose goal is to enable them to find out and understand what their representatives are up to. But by using the site’s tools, Members of Congress are also helping us achieve this goal.

We’ve added historical information on bills from 1951-1978 and made some other improvements to the site recently. Here are the details:

• Using the Statutes at Large, the compilation of laws enacted by Congress, we’ve added enacted bills from 1951-1972 into GovTrack. For example, here’s Civil Rights Act of 1964 (H.R. 7151 in the 88th Congress). You can search and browse them on the advanced search page.
• We also added bills and resolutions from the 93-95th Congresses (1973-1978). Previously we only went back to the 96th Congress (1979-1980).
• To explain the new data, we added a new coverage table to the About page.
• When you share a bill or vote page on Facebook, it’ll now include a thumbnail image.
• We improved the account settings page. That’s the page when you click your email address at the top of the page, if you’re logged in.
• On pages for Members of Congress, there’s now a link to their page on the C-SPAN website, where you can see videos of their floor speeches. Try with Sen. Mary Landrieu. (Thanks to The New York Times for contributing the data.)
• Fixed bill search so you can search by bill number without having to type periods and spaces, like “hr1234.”
• You can now also track the changes we make to GovTrack on github.

UPDATE: See how this issue resolved.

Rep. Ander Crenshaw (FL4) and the House subcommittee he chairs decided this week that the American public can’t be trusted with more thorough records about what Congress is doing.

/// Take Action: Write your rep to oppose Crenshaw’s report.
/// Start a Letter >

Read it all..

Bill prognosis has gotten an upgrade. A few weeks ago I wrote about a new addition to GovTrack, the bill prognosis, and because it proved to be useful I expanded on it to provide a more detailed and numerical assessment of the future of each bill. For an example, check out H.R. 4323, which we’re currently listing as having a 2% chance of being enacted.

If you missed the first post, here’s an overview: Only a small fraction of the bills and resolutions introduced will ever be voted on. How do you know which bills to pay attention to? We can’t predict the future, but we can highlight factors that favor a bill’s progress and use statistics from past years to assess the likelihood that a bill will be enacted.

In the first version of bill prognosis, we listed whether the bill’s sponsor is the chair of the committee considering the bill and whether any cosponsors of the bill are on the committee. Now, we use factors like these and more to compute an actual probability that the bill will be enacted (or for resolutions that they will be passed).

For H.R. 4323: Consumer Mortgage Choice Act, we are currently listing a 2% chance of the bill being enacted and we show that the factors used in the computation are:

• 3-5 cosponsors serve on a committee to which the bill has been referred.
• There is at least one cosponsor from the majority party and one cosponsor outside of the majority party.
• The sponsor is a member of the majority party.

I unfortunately confused things a bit by running a separate experiment recently. We were listing a probability that each bill would be enacted and were asking whether you thought the number was too low or too high. That wasn’t based on the bill prognosis — I’ll write about where that number was coming from another time. But I saw that GovTrack users were finding it useful, and so I knew enhancing the bill prognosis with a rigorously computed probability would be a good idea.

For the data wonks out there, the new prognosis is based on a logistic regression model. The model predicts a bill’s success based on the following binary factors:

• the title of the bill (such as if it is a bill to name a post office)
• whether the sponsor is a member of the majority party (in the House or Senate as appropriate)
• whether the sponsor is the chair, ranking member (most senior minority party member), or a majority-party member of a committee that the bill has been referred to
• if any cosponsor is the chair or ranking member of a committee the bill has been referred to
• if there are 3-5 cosponsors of the bill serving on a committee the bill has been referred to
• if the bill has a cosponsor from both parties
• if the bill’s sponsor is in the majority party and at least 1/3rd of the cosponsors are from the minority party
• if the bill was a reintroduction of a bill from the previous Congress (same sponsor and title, ignoring any year found in the title) and, separately, if the previous bill had been reported by committee (suggested by Tom Lee and Daniel Schuman shortly after this post was first published)
• if the bill’s sponsor or cosponsors have a high leadership score based on GovTrack’s analysis of bill sponsorship (based on a suggestion from Mackenzie Morgan shortly after this post was first published)
• and if any of these factors are true of a companion (identical) bill introduced in the other house of Congress

Success is for bills if they are enacted and for resolutions if they successfully reach the end of their life cycle (simple resolutions passed, concurrent resolutions passed by both chambers, joint resolutions enacted). A separate model was constructed for each of the eight bill types (H.R., S., S.Res., etc.). Additional models were created for bills that were at least reported by committee, and the prognosis for such bills is based on those separate models. The models were trained on bills and resolutions from 2009-2010 (the previous session of Congress).

Here are some results of the model. Of Senate bills in 2009-2010, only 2.8% were enacted. The regression coefficients for the model for Senate bills are listed below, in order from most indicative of a successful bill to least indicative. Also listed with each is the percentage of bills with that attribute that were enacted, to compare against the 2.8%.

• 2.7 — the bill’s title starts with “A bill to designate the” (usually naming a post office) (24% enacted)
• 2.1 — a companion bill has a cosponsor that is the ranking member of a relevant committee (22% enacted)
• 2.0 — a companion bill’s sponsor is the chair of a relevant committee (29% enacted)
• 1.7 — the bill’s title starts with “A bill to authorize” (10% enacted)
• 1.0 — a cosponsor is the ranking member of a relevant committee (13% enacted)
• 0.94 — a cosponsor is the chair of a relevant committee (9.4% enacted)
• 0.76 — there are cosponsors from both parties (5.2% enacted)
• 0.63 — the sponsor is from the majority party and at least 1/3rd of the cosponsors are from the minority party (6.8% enacted)
• 0.47 — the bill was a re-introduction of a bill that was reported by committee in the previous session of Congress (7.6% enacted)
• 0.37 — the sponsor is the chair of a committee to which the bill was referred (7.7% enacted)
• 0.27 — a companion bill has a cosponsor from the majority party and a cosponsor from the minority party (6.3% enacted)
• 0.12 — a companion bill is a reintroduction of a bill that was reported by committee in a previous session of Congress (11% enacted)
• 0.080 — a companion bill has 6 or more cosponsors on a relevant committee (4.9% enacted)
• 0.013 — a cosponsor in the majority party has a high leadership score (7.4% enacted)
• -0.032 — a companion bill’s sponsor is in the majority party (5.4% enacted)
• -0.13 — a companion bill’s cosponsor is the chair of a relevant committee (8% enacted)
• -0.14 — 3-5 cosponsors are members of a relevant committee (4.7% enacted)
• -0.85 — the sponsor is in the minority party (1.2% enacted)
• -1.5 — the bill was a re-introduction of a bill from the previous session of Congress that had no major action (<1% enacted)
• -34 — the bill’s title starts with “A bill to extend the temporary suspension of duty” (0% enacted)

The regression coefficients are not easily interpretable on their own, except that higher numbers mean that they more importantly indicate they help a bill get enacted. The largest negative numbers indicate those bills pretty much never get enacted. Small negative numbers don’t necessarily mean that the factor hurts a bill’s chances

(Before using the regression model I tested that each factor taken independently was statistically significant, but in a way that in retrospect was not a particularly good way to do it. My intuition is that the regression model factors are probably all statistically significant anyway. Based on that initial test of significance I excluded some of these factors from some of the models. For instance, no factors were statistically significant for the model for Senate bills reported by committee, in part because the sample of 523 bills is so much smaller. No regression model is used in that case, and the overall probability of 21% for all such bills is used as the prognosis for all bills in this category. Note how much larger 21% is than the overall success rate for all Senate bills, 2.8%.)

UPDATES: After folks suggested new factors to consider, I re-created the models and the regression coefficients above were updated.

Numbers confirm what we already pretty much know: Congress this year isn’t getting much done. The number of bills enacted this year is lower than it has ever been in at least 30 years. If you think Congress should be passing fewer laws, then you got your wish this year.

An analysis of GovTrack data shows only 66 bills and joint resolutions were enacted this year. The last time the number was even close to this low was in 1995, the year Republicans took Congress under the Democratic administration of President Clinton, when 88 bills were enacted. Then, like now, the Congress and the Presidency were split between the parties.

But that wasn’t a barrier to lawmaking in other years. An average of 167 bills were enacted in the first year of the two subsequent Congresses after 1995 (that is, 1997 and 1999), during which Republicans retained control of Congress under a Democratic president, and about the same were enacted in 2007, 175 in all, when Democrats controlled Congress and the President was still Republican. (Congress operates in two-year sessions each called a Congress. I’m looking at the first year of each Congress.)

Since 1995, the most comparable year to this year was 2001, when Congress was divided for part of the year after Sen. Jeffords left the Republican party. Only 110 bills were enacted that year.

In 2003 and 2005, when Republicans controlled Congress and the Presidency during the middle of President Bush’s terms, the average number of bills enacted was 191. In 2009, when Democrats controlled Congress and the Presidency, President Obama’s first year, the number of bills enacted was 125 — ironically less than the Republicans who these days tend to believe Congress should be doing less.

Edit: Derek Willis points out that the number of bills passed isn’t necessarily a measure of productivity. Procedures have changed over the years that make comparisons across years difficult. For instance, he wrote, more bills are passed under special rules that makes widely-supported bills go through faster.

I’ll be on the Kojo Nnamdi show at noon today, which is on WAMU 88.5 in the DC area, and I think you can also listen online.

Hey, we need some cool GovTrack apparel, right? Design a GovTrack t-shirt or send me a funny expression related to GovTrack to put on a t-shirt, and if I get some good responses I’ll pick a winner and send back a $100 gift certificate to somewhere. Email your submissions to operations@govtrack.us.

GovTrack has taken the plunge to Twitter. I’ll be tweeting from time to time as . Also, I’ve put up recommended hashtags  on the pages for bills so we can more easily track the chatter on legislation happening in the twitterverse. (It’s in the blue box on the right side.)

You might have noticed the last blog post was a bit out of the ordinary here. It wasn’t written by me, and it’s coverage of a recent congressional hearing. I’m starting up a new experiment, a citizen reporters team to cover the goings on in congress that the mainstream press doesn’t. Stay tuned!