North Carolina

How do we get rid of gerrymandering?

pnrj public policy, statistics , , , , , ,

Nov 18 JDN 2458441

I don’t mean in a technical sense; there is a large literature in political science on better voting mechanisms, and this is basically a solved problem. Proportional representation, algorithmic redistricting, or (my personal favorite) reweighted range voting would eradicate gerrymandering forever.

No, I mean strategically and politically—how do we actually make this happen?

Let’s set aside the Senate. (No, really. Set it aside. Get rid of it. “Take my wife… please.”) The Senate should not exist. It is fundamentally anathema to the most basic principle of democracy, “one person, one vote”; and even its most ardent supporters at the time admitted it had absolutely no principled justification for existing. Smaller states are wildly overrepresented (Wyoming, 580,000 people, gets the same number of Senators as California, 39 million), and non-states are not represented (DC has more people than Wyoming, and Puerto Rico has more people than Iowa). The “Senate popular vote” thus doesn’t really make sense as a concept. But this is not “gerrymandering”, as there is no redistricting process that can be used strategically to tilt voting results in favor of one party or another.

It is in the House of Representatives that gerrymandering is a problem.
North Carolina is a particularly extreme example. Republicans won 50.3% of the popular vote in this year’s House election; North Carolina has 13 seats; so, any reasonable person would think that the Republicans should get 7 of the 13 seats. Under algorithmic redistricting, they would have received 8 of 13 seats. Under proportional representation, they would have received, you guessed it, exactly 7. And under reweighted range voting? Well, that depends on how much people like each party. Assuming that Democrats and Republicans are about equally strong in their preferences, we would also expect the Republicans to win about 7. They in fact received 10 of 13 seats.

Indeed, as FiveThirtyEight found, this is almost the best the Republicans could possibly have done, if they had applied the optimal gerrymandering configuration. There are a couple of districts on the real map that occasionally swing which wouldn’t under the truly optimal gerrymandering; but none of these would flip Democrat more than 20% of the time.

Most states are not as gerrymandered as North Carolina. But there is a pattern you’ll notice among the highly-gerrymandered states.

Alabama is close to optimally gerrymandered for Republicans.

Arkansas is close to optimally gerrymandered for Republicans.

Idaho is close to optimally gerrymandered for Republicans.

Mississippi is close to optimally gerrymandered for Republicans.

As discussed, North Carolina is close to optimally gerrymandered for Republicans.
South Carolina is close to optimally gerrymandered for Republicans.

Texas is close to optimally gerrymandered for Republicans.

Wisconsin is close to optimally gerrymandered for Republicans.

Tennessee is close to optimally gerrymandered for Democrats.

Arizona is close to algorithmic redistricting.

California is close to algorithmic redistricting.

Connecticut is close to algorithmic redistricting.

Michigan is close to algorithmic redistricting.

Missouri is close to algorithmic redistricting.

Ohio is close to algorithmic redistricting.

Oregon is close to algorithmic redistricting.

Illinois is close to algorithmic redistricting, with some bias toward Democrats.

Kentucky is close to algorithmic redistricting, with some bias toward Democrats.

Louisiana is close to algorithmic redistricting, with some bias toward Democrats.

Maryland is close to algorithmic redistricting, with some bias toward Democrats.

Minnesota is close to algorithmic redistricting, with some bias toward Republicans.

New Jersey is close to algorithmic redistricting, with some bias toward Republicans.

Pennsylvania is close to algorithmic redistricting, with some bias toward Republicans.

Colorado is close to proportional representation.

Florida is close to proportional representation.

Iowa is close to proportional representation.

Maine is close to proportional representation.

Nebraska is close to proportional representation.

Nevada is close to proportional representation.

New Hampshire is close to proportional representation.

New Mexico is close to proportional representation.

Washington is close to proportional representation.

Georgia is somewhere between proportional representation and algorithmic redistricting.

Indiana is somewhere between proportional representation and algorithmic redistricting.

New York is somewhere between proportional representation and algorithmic redistricting.

Virginia is somewhere between proportional representation and algorithmic redistricting.

Hawaii is so overwhelmingly Democrat it’s impossible to gerrymander.

Rhode Island is so overwhelmingly Democrat it’s impossible to gerrymander.

Kansas is so overwhelmingly Republican it’s impossible to gerrymander.

Oklahoma is so overwhelmingly Republican it’s impossible to gerrymander.

Utah is so overwhelmingly Republican it’s impossible to gerrymander.

West Virginia is so overwhelmingly Republican it’s impossible to gerrymander.

You may have noticed the pattern. Most states are either close to algorithmic redistricting (14), close to proportional representation (9), or somewhere in between those (4). Of these, 4 are slightly biased toward Democrats and 3 are slightly biased toward Republicans.

6 states are so partisan that gerrymandering isn’t really possible there.

6 states are missing from the FiveThirtyEight analysis; I think they couldn’t get good data on them.

Of the remaining 9 states, 1 is strongly gerrymandered toward Democrats (gaining a whopping 1 seat, by the way), and 8 are strongly gerrymandered toward Republicans.

If we look at the nation as a whole, switching from the current system to proportional representation would increase the number of Democrat seats from 168 to 174 (+6), decrease the number of Republican seats from 195 to 179 (-16), and increase the number of competitive seats from 72 to 82 (+10).

Going to algorithmic redistricting instead would reduce the number of Democrat seats from 168 to 151 (-17), decrease the number of Republican seats from 195 to 180 (-15), and increase the number of competitive seats from 72 to a whopping 104 (+32).

Proportional representation minimizes wasted votes and best represents public opinion (with the possible exception of reweighted range voting, which we can’t really forecast because it uses more expressive information than what polls currently provide). It is thus to be preferred. Relative to the current system, proportional representation would decrease the representation of Republicans relative to Democrats by 24 seats—over 5% of the entire House.

Thus, let us not speak of gerrymandering as a “both sides” sort of problem. There is a very clear pattern here: Gerrymandering systematically favors Republicans.

Yet this does not answer the question I posed: How do we actually fix this?

The answer is going to sound a bit paradoxical: We must motivate voters to vote more so that voters will be better represented.

I have an acquaintance who has complained about this apparently paradoxical assertion: How can we vote to make our votes matter? (He advocates using violence instead.)

But the key thing to understand here is that it isn’t that our votes don’t matter at all—it is merely that they don’t matter enough.

If we were living in an authoritarian regime with sham elections (as some far-left people I’ve spoken to actually seem to believe), then indeed voting would be pointless. You couldn’t vote out Saddam Hussein or Benito Mussolini, even though they both did hold “elections” to make you think you had some voice. At that point, yes, obviously the only remaining choices are revolution or foreign invasion. (It does seem worth noting that both regimes fell by the latter, not the former.)

The US has not fallen that far just yet.

Votes in the US do not count evenly—but they do still count.

We have to work harder than our opponents for the same level of success, but we can still succeed.

Our legs may be shackled to weights, but they are not yet chained to posts in the ground.

Indeed, several states in this very election passed referenda to create independent redistricting commissions, and Democrats have gained at least 32 seats in the House—“at least” because some states are still counting mail-in ballots or undergoing recounts.

The one that has me on the edge of my seat is right here in Orange County, which several outlets (including the New York Times) have made preliminary projections in favor of Mimi Walters (R) but Nate Silver is forecasting higher probability for Katie Porter (D). It says “100% of precincts reporting”, but there are still as many ballots uncounted as there are counted, because California now has almost twice as many voters who vote by mail than in person.

Unfortunately, some of the states that are most highly gerrymandered don’t allow citizen-sponsored ballot initiatives (North Carolina, for instance). This is likely no coincidence. But this still doesn’t make us powerless. If your state is highly gerrymandered, make noise about it. Join or even organize protests. Write letters to legislators. Post on social media. Create memes.
Even most Republican voters don’t believe in gerrymandering. They want to win fair and square. Even if you can’t get them to vote for the candidates you want, reach out to them to get them to complain to their legislators about the injustice of the gerrymandering itself. Appeal to their patriotic values; election manipulation is clearly not what America stands for.

If your state is not highly gerrymandered, think bigger. We should be pushing for a Constitutional amendment implementing either proportional representation or algorithmic redistricting. The majority of states already have reasonably fair districts; if we can get 2/3 of the House and 2/3 of the Senate to agree on such an amendment, we don’t need to win North Carolina or Mississippi.

The powerful persistence of bigotry

pnrj cognitive science, critique of neoclassical economics, current events, ethics, heuristics and biases, public policy , , , , , , , , , ,

JDN 2457527

Bigotry has been a part of human society since the beginning—people have been hating people they perceive as different since as long as there have been people, and maybe even before that. I wouldn’t be surprised to find that different tribes of chimpanzees or even elephants hold bigoted beliefs about each other.

Yet it may surprise you that neoclassical economics has basically no explanation for this. There is a long-standing famous argument that bigotry is inherently irrational: If you hire based on anything aside from actual qualifications, you are leaving money on the table for your company. Because women CEOs are paid less and perform better, simply ending discrimination against women in top executive positions could save any typical large multinational corporation tens of millions of dollars a year. And yet, they don’t! Fancy that.

More recently there has been work on the concept of statistical discrimination, under which it is rational (in the sense of narrowly-defined economic self-interest) to discriminate because categories like race and gender may provide some statistically valid stereotype information. For example, “Black people are poor” is obviously not true across the board, but race is strongly correlated with wealth in the US; “Asians are smart” is not a universal truth, but Asian-Americans do have very high educational attainment. In the absence of more reliable information that might be your best option for making good decisions. Of course, this creates a vicious cycle where people in the positive stereotype group are better off and have more incentive to improve their skills than people in the negative stereotype group, thus perpetuating the statistical validity of the stereotype.

But of course that assumes that the stereotypes are statistically valid, and that employers don’t have more reliable information. Yet many stereotypes aren’t even true statistically: If “women are bad drivers”, then why do men cause 75% of traffic fatalities? Furthermore, in most cases employers have more reliable information—resumes with education and employment records. Asian-Americans are indeed more likely to have bachelor’s degrees than Latino Americans, but when it say right on Mr. Lorenzo’s resume that he has a B.A. and on Mr. Suzuki’s resume that he doesn’t, that racial stereotype no longer provides you with any further information. Yet even if the resumes are identical, employers will be more likely to hire a White applicant than a Black applicant, and more likely to hire a male applicant than a female applicant—we have directly tested this in experiments. In an experiment where employers had direct performance figures in front of them, they were still more likely to choose the man when they had the same scores—and sometimes even when the woman had a higher score!

Even our assessments of competence are often biased, probably subconsciously; given the same essay to review, most reviewers find more spelling errors and are more concerned about those errors if they are told that the author is Black. If they thought the author was White, they thought of the errors as “minor mistakes” by a student with “otherwise good potential”; but if they thought the author was Black, they “can’t believe he got into this school in the first place”. These reviewers were reading the same essay. The alleged author’s race was decided randomly. Most if not all of these reviewers were not consciously racist. Subconscious racial biases are all over the place; almost everyone exhibits some subconscious racial bias.

No, discrimination isn’t just rational inference based on valid (if unfortunate and self-reinforcing) statistical trends. There is a significant component of just outright irrational bigotry.

We’re seeing this play out in North Carolina; due to their arbitrary discrimination against lesbian, gay, bisexual and especially transgender people, they are now hemorrhaging jobs as employers pull out, and their federal funding for student loans is now in jeopardy due to the obvious Title IX violation. This is obviously not in the best interest of the people of North Carolina (even the ones who aren’t LGBT!); and it’s all being justified on the grounds of an epidemic of sexual assaults by people pretending to be trans that doesn’t even exist. It turns out that more Republican Senators have been arrested for sexual misconduct in bathrooms than transgender people—and while the number of transgender people in the US is surprisingly hard to measure, it’s clearly a lot larger than the number of Republican Senators!

In fact, discrimination is even more irrational than it may seem, because empirically the benefits of discrimination (such as they are—short-term narrow economic self-interest) fall almost entirely on the rich while the harms fall mainly on the poor, yet poor people are much more likely to be racist! Since income and education are highly correlated, education accounts for some of this effect. This is reason to be hopeful, for as educational attainment has soared, we have found that racism has decreased.

But education doesn’t seem to explain the full effect. One theory to account this is what’s called last-place aversion—a highly pernicious heuristic where people are less concerned about their own absolute status than they are about not having the worst status. In economic experiments, people are usually more willing to give money to people worse off than them than to those better off than them—unless giving it to the worse-off would make those people better off than they themselves are. I think we actually need to do further study to see what happens if it would make those other people exactly as well-off as they are, because that turns out to be absolutely critical to whether people would be willing to support a basic income. In other words, do people count “tied for last”? Would they rather play a game where everyone gets $100, or one where they get $50 but everyone else only gets $10?

I would hope that humanity is better than that—that we would want to play the $100 game, which is analogous to a basic income. But when I look at the extreme and persistent inequality that has plagued human society for millennia, I begin to wonder if perhaps there really are a lot of people who think of the world in such zero-sum, purely relative terms, and care more about being better than others than they do about doing well themselves. Perhaps the horrific poverty of Sub-Saharan Africa and Southeast Asia is, for many First World people, not a bug but a feature; we feel richer when we know they are poorer. Scarcity seems to amplify this zero-sum thinking; racism gets worse whenever we have economic downturns. Precisely because discrimination is economically inefficient, this can create a vicious cycle where poverty causes bigotry which worsens poverty.

There is also something deeper going on, something evolutionary; bigotry is part of what I call the tribal paradigm, the core aspect of human psychology that defines identity in terms of in-groups which are good and out-groups which are bad. We will probably never fully escape the tribal paradigm, but this is not a reason to give up hope; we have made substantial progress in reducing bigotry in many places. What seems to happen is that people learn to expand their mental tribe, so that it encompasses larger and larger groups—not just White Americans but all Americans, or not just Americans but all human beings. Peter Singer calls this the Expanding Circle (also the title of his book on it). We may one day be able to make our tribe large enough to encompass all sentient beings in the universe; at that point, it’s just fine if we are only interested in advancing the interests of those in our tribe, because our tribe would include everyone. Yet I don’t think any of us are quite there yet, and some people have a really long way to go.

But with these expanding tribes in mind, perhaps I can leave you with a fact that is as counter-intuitive as it is encouraging, and even easier still to take out of context: Racism was better than what came before it. What I mean by this is not that racism is good—of course it’s terrible—but that in order to be racism, to define the whole world into a small number of “racial groups”, people already had to enormously expand their mental tribe from where it started. When we evolved on the African savannah millions of years ago, our tribe was 150 people; to this day, that’s about the number of people we actually feel close to and interact with on a personal level. We could have stopped there, and for millennia we did. But over time we managed to expand beyond that number, to a village of 1,000, a town of 10,000, a city of 100,000. More recently we attained mental tribes of whole nations, in some case hundreds of millions of people. Racism is about that same scale, if not a bit larger; what most people (rather arbitrarily, and in a way that changes over time) call “White” constitutes about a billion people. “Asian” (including South Asian) is almost four billion. These are astonishingly huge figures, some seven orders of magnitude larger than what we originally evolved to handle. The ability to feel empathy for all “White” people is just a little bit smaller than the ability to feel empathy for all people period. Similarly, while today the gender in “all men are created equal” is jarring to us, the idea at the time really was an incredibly radical broadening of the moral horizon—Half the world? Are you mad?

Therefore I am confident that one day, not too far from now, the world will take that next step, that next order of magnitude, which many of us already have (or try to), and we will at last conquer bigotry, and if not eradicate it entirely then force it completely into the most distant shadows and deny it its power over our society.