joshhansen.net

Category: politics

  • A Nerdly, Software-Engineering-ish, Computer-Sciencey Approach to the Gay Marriage Debate

    Gay marriage is a proposed change that’s hoped to be an optimization. Advocates say that the current system (society) is sub-optimal in that a particular sub-system (marriage) is not sufficiently general (same-sex couples aren’t allowed to participate). Let’s say marriage is a function by which a man and a woman are combined to create an object conforming to the Family interface:

    marriage(Man,Woman) : Family

    The proposed optimization generalizes this function:

    marriage(Person,Person) : Family

    A general rule in software engineering is to maximize the generality of the input parameters (Person instead of Man or Woman). In this light, the second marriage function represents an improvement because it makes the marriage function applicable to more people.

    However, this focus on the function signature obscures some important issues. For one thing, the marriage function does not stand in isolation, but is embedded at the core of an extremely complex network of functions. In software this is known as the call graph. For example, the network of function calls in one relatively small piece of software looks like this:

    seL4 microkernel call graph

    Each node (circle) represents a function, and each edge (line between circles) represents one function calling (using) another. Now imagine the complexity of such a graph for our entire society, in which marriage constitutes only a single (though essential) node, connected to things like employment relationships, governmental functions, child-rearing, religious organizations, and so on. A key function like marriage would be at the center of the graph, like the large green dot in the middle of the picture. Messing with that node can affect not only it and its immediate neighbors, but actually every other node in the graph.

    It should also be noted that the proposed optimization not only redefines the function signature (who can participate in marriage) but actually provides a new implementation for the function:h

    class GayFamily implements Family {
    // a bunch of experimental code...
    }

    In software, the new implementing class could be automatically tested to make sure it meets the requirements of the Family interface. In society, such automated tests are unavailable, and the impacts of this new implementation may not be fully known within the natural lifetime of anyone now living.

    In fact, it’s essentially impossible to conduct the sort of experiment needed to assess whether gay marriage is a good idea. We’re not just interested in effects on individuals or families (important as they are) but on entire societies. It would require many societies under many circumstances randomly assigned to either implement or not implement the change, and for sufficient time to pass for the network effects to work themselves out.

    Obviously this line of reasoning could be applied to various types of radical social change, and I’m certainly not saying that such change is never justified. But I am saying we need humility and caution when hacking a key function like marriage that the entire system is built around. In the end, this isn’t software. This is society. It’s parents, it’s children, it’s lives.

    Because an robust empirical evaluation of this change at the civilizational level will not be soon forthcoming, anyone with an opinion must come to it by non-empirical means. And my opinion is that this change isn’t worth the risk.

  • A Picture’s Worth A Thousand Senators: Staring Into The Gaping Ideological Chasm That Divides Congress

    In this post, I’m going to introduce you to a cool-looking graph, tell you what it means, and give the technical details of its generation—all because I think America might care. Here we go.

    Introduction

    Politics in America are hopelessly partisan, and all of the bickering serves only to cripple our nation at a moment of crisis when decisive action is called for. You know it. I know it. Barack Obama and John Boehner know it. Your grandma knows it.

    Or do we know it? The belief that American politics has become more polarized in recent decades is widespread. But is there any evidence for it? While I make no attempt to provide a complete explanation for this disturbing trend in our nation’s governance, in this post I present some work that I believe provides an answer—a resounding confirmation that, according to at least one view of the situation, the politics of the United States are now more deeply divided than ever.

    Though this work was done in collaboration with Michael Dimond as part of an advanced data mining course (CS676) at BYU, I believe I am the sole author of the portions of our report excerpted below.

    The Cool-Looking Graph

    Here’s the pretty picture:

    United States Senate Legislator Similarity Network 1789-2011.

    Bask in its glory—and be grateful, because that thing took a lot of work! Make sure to click on the image to see the full-sized version. (It will open in a new window/tab.)

    What It Means

    The above graph is a visual representation of the United States Senate across 222 years of legislative history. It is, in essence, a social network of senators across time—who voted like whom, what cliques and factions formed, etc. In other words, retroactive Facebook for America’s past politicians? No, that’s going too far….

    Anyway, here’s how to interpret the graph. Each node (circle) represents a senator. An arc is drawn between two nodes if the two senators at the endpoints voted on the same bill at least once and voted the same way on bills more than 75% of the time. Size and color of nodes indicate their centrality (a measure of importance) in the network. Scanning from left (1789) to right (2011), a few trends emerge:

    1. The height of the graph increases. Much of this can be attributed to the increase in the number of states, from 13 to 50, meaning the number of senators serving simultaneously increased by 74.
    2. The graph alternates between unity and polarization. Visually, unity looks like a single “stream” of nodes, whereas polarization is the graph splitting into two components that move in slightly different directions.
    3. In recent decades, the height of the graph has continued to increase in spite of the number of senators being fixed at 100 since 1959. I assert that this corresponds to the phenomenon of increased polarization between the two parties.

    I am interested in whether the flow of the graph can be correlated with developments in the American two-party system. Feel free to let me know your thoughts on that. For those wishing to play with the graph data, it’s available here.

    Technical Details

    This stuff gets pretty computer sciencey, so only read on if you really want to nerd out.

    Data

    The graph is generated using an aggregated and sanitized version of the THOMAS congressional data from govtrack.us. This yields 2.1 GiB of primarily XML-encoded congressional data from the 1st to the 112th congress. The data includes a record of votes by all legislators on all roll calls since the 1st congress, as well as party affiliation.

    Social Graph Inference

    Let $latex L$ be the set of all legislators and $latex S$ be the set of all sessions of congress. We define a legislator-to-legislator similarity function $latex \sigma : L \times L \rightarrow [0,1]$ that returns a similarity score for all pairs of legislators that ever voted on the same roll call:

    [latex size=3]
    \sigma(l_{1},l_{2})=\frac{SameVotes(l_{1},l_{2})}{PossibleVotes(l_{1},l_{2})} \\
    \\
    \phantom{\sigma(l_{1},l_{2})}=\frac{\sum_{s \in S : l_{1} \in s \wedge l_{2} \in s} \sum_{r\in Rolls(s)} \beta\left [vote(l_{1},r)=vote(l_{2},r) \right ]}{\sum_{s \in S : l_{1} \in s \wedge l_{2} \in s} |Rolls(s)|}
    [/latex]

    where

    • $latex Rolls(s)$ returns the set of all roll calls (votes) occurring in session $latex s$;
    • $latex \beta[x]$ is an indicator function returning 1 when $latex x$ is true, 0 otherwise;
    • $latex vote(l,r)$ returns the vote cast by legislator $latex l$ on roll $latex r$; and
    • $latex l \in s$ is true iff legislator $latex l$ served in congressional session $latex s$.

    We use this similarity measure to construct a legislator affinity graph as follows:

    Let $latex G=(V,E)$ be an undirected graph with a set of vertices $latex V$ and a set of weighted edges $latex E$, such that

    • $latex V=\{Vertex(l) : l \in L\}$ and
    • $latex E=\{Edge(l_{1}, l_{2}, \sigma(l_{1},l_{2})) : (l_{1},l_{2}) \in L \times L \wedge \sigma(l_{1},l_{2}) > \theta\}$

    where

    • $latex Vertex(l)$ yields the vertex associated with a given legislator $latex l$;
    • $latex Edge(l_{1},l_{2},w)$ yields an undirected edge with weight $latex w$ and endpoints $latex Vertex(l_{1})$ and $latex Vertex(l_{2})$,
    • and $latex \theta \in [0,1]$ is a minimum similarity threshold.

    Rendering

    In practice, the above $latex \theta$ must be set high (I used 0.75) to prevent the number of edges from being excessively large. Once the graph was constructed, it was loaded into Gephi, a graph visualization tool. Betweenness centralities were computed, nodes were sized and colored, and a force-directed layout algorithm was applied. I then manually rotated the graph so that earlier senators are located on the left and more recent senators on the right, to give the effect of a rough historical timeline. I exported this as an SVG file, then loaded it in the Inkscape vector graphics program. With the benefit of 16GB of RAM, I coaxed Inkscape into rendering a 20,000 pixel width PNG image of the graph. This was finally scaled to 10,000 pixels wide for web distribution using GIMP.

    Acknowledgements

    Thanks to Christophe Giraud-Carrier for teaching the class for which this graph was generated, and to Michael Dimond who, though not directly working on this portion of our project, was nevertheless an excellent collaborator. And to my friend who convinced me to finally finish this post.

  • If You’re A Member of Congress, Vote ‘No’ on Health Care Reform!

    To quote one of my favorite economists, Gary Becker:

    Despite the long debate, many provisions of both the House and Senate bills remain highly controversial. These include, among many others, the way the uninsured would get coverage, the de-emphasis on health savings accounts, the postponement until 2018 of the elimination of the tax advantages from expensive employer-based health plans, no increase in the ability of persons and companies in one state to contract with insurance companies located in other states, and especially the minor efforts to raise out of pocket expenses by consumers of health care in order to reduce their overuse of doctors, drugs, and even hospitals. Such a badly designed health care bill would on the whole worsen rather than improve the American health care system…. [link]

    And, from his fellow-blogger, Richard Posner:

    Because [the health care reform bill currently in congress] is unpopular among the general public, its enactment by a simple majority in both Houses would raise a valid question about the representative character of Congress…. [T]he health care program has been kicking around in Congress for a year, and the inability of its supporters to convince the public of the program’s wisdom, coupled with the program’s enormous cost and its potentially disruptive consequences for the health care industry…and indeed the entire economy, may make people question the democratic legitimacy of enacting the program with just a simple majority in the House and Senate. [link]

    I oppose the health care reform bill because our government’s fiscal health is already in dire shape, and this bill will turn a dangerous fiscal disease into a terminal one. The Democrats’ push to pass this bill is a face-saving sellout of the welfare of the American people who, as I understand it, largely oppose the legislation. If you are a member of congress or perhaps an intern or electronic aggregator doing the bidding of one, be aware that this man wants you to vote ‘no’! Think of the future—not just this fall’s elections.