Let he who is without Science Denial cast the first stone

The Washington Post recently ran an article on how political affiliation and level of religious belief affect support for, or suspicion of, the scientific consensus on various subjects. In it they refer to research by Dale Kahan to argue/imply that opposition to science is primarily driven by conservative ideology.

For example, they have these three very attractive charts, showing that the difference between people of high and low religiosity is small compared to the difference between conservatives and liberals when it comes to global warming,




and Stem Cell research:

However, as so often happens, their article on causes of political bias ends up displaying some pretty impressive political bias. Unsurprisingly, this bias tends to be flattering towards those who share their political beliefs, and damning of those who don’t.

Firstly, look at those charts again. When looking at on the left-right axis, your eye is naturally drawn to compare the two extremes – to compare the most right wing to the most left wing (especially as the line is monotonic). You note the large difference in height between the leftmost data points and the rightmost, compare it to the relatively small difference between the high and low religiosity lines. The former difference is bigger than the latter difference, so political opinions must be more important than religious ones.

… or so the chart leads us to believe. However, this is hugely deceptive. As you can see, there are 5 tick marks on the horizontal axis, the measure was created from questions using 5 and 7 options, and there are a very large number of little vertical lines. This means they’re using a relatively fine measure of political ideology: they differentiate moderate conservatives from ordinary conservatives from highly conservative people. By doing this, they increase how extreme the extremes are, which increases that vertical difference our eye is naturally drawn to. With religion, however, they only admit of two categories, high and low. Perhaps if they had disambiguated more, so the categories ranged from “More religious than the Hasidim” to “More atheist than Dawkins”, we would have seen more spread between those two lines. As it is, the charts suppress these differences, reducing the apparent effect of religiosity.

That’s not the only problem with the article. The climate change and evolution questions seem pretty good, but the stem cell question does not show what they think it does.

“All in all, do you favor or oppose federal funding for embryonic stem cell research”

Now, in general opposing research for science does seem like prima facie evidence that you’re in some sense anti-science. But not here! There are two other factors at play which conflate the issue.

The first is that this is as much a moral issue as a scientific one. Thinking that stem cell research is immoral doesn’t necessarily mean you disagree with any of the scientific findings, due to the is-ought gap. In the same way that opposing nazi research on cancer (which used a variety of immoral techniques) doesn’t mean you think their conclusions were factually wrong, you can think stem cell research is morally wrong but the conclusions factually correct. Or, to use a clarifying contemporary example, suppose the question instead asked,

“All in all, do you favor or oppose federal funding for methods of treating homosexuality”

My intuition, which I suspect you share, is that the line would slope in the opposite direction – lefties would be more opposed than righties. This isn’t necessarily be because they are anti-science – maybe they simply think we are better off not knowing how to treat homosexuality, or better off not even thinking about the possibility. This moral belief doesn’t, however, mean they disagree with conservatives and scientists on any factual issue.

But there is another, even bigger, problem with this question. It doesn’t just ask about the morality of stem cell research – it asks about federal funding for that research. Conservatives are well known for opposing federal funding of things in general. Yet this research suggests that consistently applying the conservative rule “oppose federal funding of things in general” is suddenly evidence of being anti-science. You would be branded anti-science by this question even if your thought process was

“I think the federal government is very bad at research – it will be inefficiently run, overly politicized, and poorly directed – so I don’t want it to mess up stem cell research. Stem cell research is far too useful and exciting to trust to the government.”

Yet surely such a person should be considered pro-science, not anti-science!

Indeed, it seems that overlooking this issue, and conflating opposition to the state with opposition to science, is a clear sign of political bias on the part of the author. They choose a question which almost by design proved conservatives were anti-science, not by actually measuring the truth, but by simply re-defining opposition to science to include the political opinions they oppose. David Friedman once wrote about something similar – a study which, while claiming to prove that right-wing people were authoritarians, really just defined authoritarianism as ‘respects right-wing authorities’.

Ok, so their choice of data visualization technique was perhaps misleading, and the stem cell funding question was awful. But the other two questions look pretty solid, right?

Perhaps not. It’s well known – or at least widely believed – that conservatives disproportionately disbelieve in evolution and global warming. So if you wanted to prove that conservatives were anti-science, you’d pick those two questions, confident that your prejudices would be confirmed.

Yet there is much more to science than evolution and global warming. There many issues where there’s a scientific consensus at least as strong as that on global warming, yet some people still disagree. For example,

  1. Astrology is nonsense
  2. Lasers are **not** condensed sound waves
  3. The earth orbits the sun

In fact, I would say that science is far more unequivocal on these issues than on global warming – probably around as certain as that evolution is true.

Yet on all these issues, Republicans are more likely to hold the scientific view that Democrats. And there are many more similar examples. If I wanted to make the same charts, but make Democrats look bad, I could easily “prove” that Democrats are morons who believe the sun orbits the earth.

The Washington Post article does contains a homage to data:

But why opine on all this an un-grounded way — we need data.

Unfortunately we need more than data – we also need rigorous statistical techniques.

It would be unfair to blame the original researcher. In his article, he also includes a chart on nuclear power, where conservatives have the more scientific view. Mysteriously, the chart that was flattering to conservatives doesn’t make it into the Washington Post article. Ironically, it turns out the Washington Post article was right – politics really is the mindkiller. It’s just hard to spot when you’re the one getting killed.


China promises to pollute as much as possible

Obama has just signed a climate change deal with China. Essentially,

  • The US agrees to cut its emissions by 30% by 2030 from the 2005 baseline.
  • China agrees to have its emissions peak in 2030, and to have 20% of energy come from non-fossil fuels.

The US target is basically just what the EPA is mandating anyway under the Clean Air Act. US emissions have fallen substantially since 2005, largely because unconventional natural gas has lead to massive coal-to-gas switching, which is a much cleaner fuel. There would be even more switching if states didn’t impose such restrictions on fracking. Ironically, many environmentalists oppose the technologies that have done the most to reduce US emissions: nuclear and fracking.

But what’s strange here is the Chinese side of the deal. This seems spectacularly badly designed. It’s basically a cap on all post-2030 emissions at the 2030 level. Which means they’re incentivised to pollute as much as possible in 2030, to give themselves a more generous cap. It literally encourages them to stockpile coal so they can burn many years worth of production in 2030. No need to build coal plants – you don’t need to generate electricity with this burning – this is just pollution for the sake of pollution.

Now, probably China won’t just pile up resources and destroy them for the sake of destruction. But there are many more subtle ways they could take advantage of this, like bringing forward any planned coal plants, so ones scheduled to start in 2031 instead start in 2029, or delaying the implementation of emissions-reducing technologies till 2031.

Given the potential for this agreement to be actively harmful, maybe we should be grateful it’s probably purely symbolic.

How Politics Makes Vox Stupid

Vox had an excellent article a while ago on how politics makes us stupid. It describes a number of ways in which people behave systematically irrationally about politics.

For example, there is research suggesting that showing people more evidence makes them hold their existing beliefs more firmly – regardless of whether the evidence supported or contradicted their beliefs. It talks about how people avoid evidence that threatens their self-identity.

But Vox made one big mistake with the article. When writing apolitical pieces, designed to reach across party lines and improve the state of political rationality, there is one rule you must always obey. Failing to observe this rule will lead to one side rejecting you and the other side failing to learn the lesson at hand. Failure to observe this rule leads to mindkilling, and Moloch.

The rule is:

If you use a political example from one side, you must use an equal and opposite example from the other side.

If you’re writing an article on irrationality in politics, and you have an example of republicans being irrational, you need to have an equally important example of democrats being irrational, with the same emotional salience, and the same amount of pagespace dedicated to it.

Vox totally violates this rule. And it does it in the predictable direction. It’s a left-wing site in general, and it’s specific examples of irrational behaviour (apart from those lifted from papers):

  • Climate change ‘denialists’
  • Sean Hannity (a conservative commentator)
  • Fox News
  • Antonin Scalia

Every single example of a person or a group they used were right-wing. Did they notice this? If not, then they need to do some serious work on their own bias. If they did, they have done their left-wing readers a great disservice.

The point of learning about biases isn’t to gain a new weapon with which to attack others. The point is to turn the knife upon yourself and cut the cancer from your own mind.

Castle Consolidation as a raison d’être for the EU

People have given many (usually quite poor) arguments in defense of the EU. Perhaps this is because the EU is actually a quite poor quality institution. However, there is one argument for it that I have never seen considered in the literature: the argument from Castle Consolidation.

Castles are an excellent example of an industry fallen on bad times. Huge amounts of investment were poured into them a long time ago, but demand for their services fell over the centuries, as they were rendered obsolete in their primary market by new market entrants, like gunpowder and compacted earth forts. Regulatory change (the decline of feudalism) also hurt their profits. It’s safe to say that castles are no longer a worthwhile investment. Returns on invested capital1 are low, which is why few private equity funds are building new castles.

There are a great many castles in Europe, all in competition with each other for tourists and film production. What the industry needs to do is consolidate; if it could get down to a smaller number of firms, they could collude to raise prices. Import threat is limited, because although there are some nice ones in the Middle East like Krak des Chevaliers, shipping costs are prohibitively high. Returns are currently so low that they have room to rise substantially before new entrants are attracted to the market. There is little room for substitution because castles are awesome.

English Heritage has already successfully consolidate most of the castles in the UK; what remains is cross-boarder consolidation. That, presumably, is where the EU comes in: as a castle cartel.

  1. If you’d like to learn more, I recommend Damodaran

Average Utilitarianism and Agriculture

This post makes an argument that, if you believe A, you have some reason to believe B. I don’t believe A, but hopefully I have done a good job of mentally modelling the concerns of those who do. Please note that “but A is false” is not a valid response to this post (ex falso quodlibet notwithstanding).

On Agricultural Matters

Suppose you are an average utilitarian, who only cares about the average level of human happiness.1 Suppose further that all crops (wheat, rice, soybeans etc.) are used for human consumption – there are no ethanol or biodiesel industries, for example.

In the short-run, the supply of crops is mainly dependant on the weather. 2014 is looking like a good year for the US crop, as was 2013, while 2012 was bad. US corn production was 29% higher in 2013 than 2012, which was itself 13% lower than 2011. Short-term variations in crop supply are mainly due to weather, but the long run average volume comes down to the acreage planted and the amount farmers invest in raising yields (tractors, GM seeds, fertilisers, etc).

In order to prevent occasional famines, where insufficient crops are produced to feed people, you need to make sure farmers plant and invest enough to ensure that even in bad weather years, there will be enough harvested to feed everyone. Unfortunately this means that in most years, where the weather is not awful, there will be significantly more harvested than is required. Demand for bread is quite inelastic: we need a certain amount to live, but we’re not interested in eating very much more than that. So in years of good harvests, supply would massively exceed demand, and the price of crops would plummet to a low level, as happened this year. As most years do not have exceptionally bad weather, in most years prices will be very low – which will not encourage farmers to plant enough. As such, farmers are likely to under-plant so as to keep expected (average) profitability reasonable, which will ensure famines in years with bad harvests.

One solution is to stockpile grains between years. This is so straightforward it doesn’t warrant further comment.

Another is to make the demand for crops more elastic, so that even in good harvest years there will be sufficient demand. Setting aside moral qualms, in theory the government could do this, for example by buying excess crops to turn into ethanol. However, it is important not to confuse the omniscient, benevolent government planner of economists’ models with actually existing governments. The real-world implementations of such policies, like the US ethanol mandate or the Common Agricultural Policy, have been awful.

Fortuitously, there is a natural mechanism in place that makes the demand for crops elastic; meat consumption. As meat is a luxury on the margin (though some level of consumption seems to have substantial health benefits), demand for meat is significantly more sensitive to price than food in general. And it requires a large amount of grain to make a relatively small amount of meat. So farmers plant and invest enough to supply the demand from both humans and cattle herds in good times; then in years of exceptionally bad harvests, the price of grain rises, so animal husbandry is no longer economic. Farmers slaughter their herds, and the grain they were consuming is now available for human consumption. Even better, there is a short-term massive supply of beef, which can also help make up for the poor harvest. (I guess this is basically a way of storing grain inside cows.)

This reasoning is significantly more persuasive to average utilitarians than total utilitarians. By supporting agricultural investment this system helps prevents famines, which presumably lower average happiness. But it keeps the overall human population lower than it could be. In years of good harvest, the grain that is slowly wasting in storage, or being turned to Ethanol, or being fed to livestock, could instead by directly feeding people, and supporting a higher population, albeit one prone to periodic famines. The total utilitarian would also have to take into account how much pleasure people get from meat consumption, how much displeasure is caused by famines, and how many additional people could be supported on a more vegetarian diet.

  1. I think this is a silly view: it might commit your ethics to massive dependence on unknowable alien populations; it might require you to murder millions or billions of people for being insufficiently happy; it might force you to create really miserable people to ‘dilute’ the effect of sufficiently many even more unhappy people. And perhaps we should be concerned about the welfare of animals too. But suppose. 

RCT as I say, not as I do

Randomized Controlled Trials (RCTs) are the gold standard in policy evaluation.

Say you’re investigating a third world development policy, like building schools, or installing water pumps, or distributing malaria-resistant bednets. A random sample of the villages in an area are selected to receive the policy. The other villages form the control group, and receive no special treatment. Metrics on various desiderata are recorded for each village, like income, lifespan and school attendance. By comparing these outcomes between villages with and without the intervention, we can judge whether it made a statistically significant difference.

RCTs give us strong evidence of a causal link between the intervention and the result – we assume there were no other systematic differences between the treatment and control villages, so we have good grounds for thinking the differences in outcome were due to the intervention.

This is a marked improvement over typical methods of evaluation. One such method is simply to not investigate results at all, because it seems obvious that the intervention is beneficial. But people’s intuitions are not very good at judging which interventions work. When Michael Kremer and Rachel Glennerster did a series of education RCTs in Kenya, all their best ideas turned out to be totally ineffective – plausible ideas like providing textbooks or teachers to schools had little impact. The one thing that did make a difference – deworming the children of intestinal worms – was not something you’d necessarily have expected to have the biggest impact on education. Our intuitions are not magic – there’s no clear reason to expect our to have evolved good intuitions into the effectiveness of developmental policies.

A common alternative is to give everyone the intervention, and see if outcomes improve. This doesn’t work either – outcomes might have improved for other reasons. Or, if outcomes deteriorated, maybe they would have been even worse without the intervention. Without RCTs, it’s very difficult to tell. Another alternative to RCTs is to compare outcomes for villages which had schools in the first place to those which didn’t, before you intervene at all, and see if the former have better outcomes. But then you can’t tell if there was a third factor that causes both schools and outcomes – maybe the richer villages could afford to build more schools.

The other main use of RCTs is in pharmaceuticals – companies that develop a new drug have to go through years of testing where they randomly assign the drug to some patients but not others, so we can be reasonably confident that the drug both achieves its aims and doesn’t cause harmful side effects.

One of the major criticisms of RCTs is that they are unfair, because you’re denying the benefits of the intervention to those in the control group. You could have given vaccinations to everyone, but instead you only gave them to half the people, thereby depriving the second half of the benefits. That’s horrible, so you should give everyone the treatment instead. This is a reasonably intelligent discussion of the issue.

But this is probably a mistake. Leaving aside the issue that it’s more expensive to give everyone the treatment than a subset (though RCTs do cost money to run), it’s a very static analysis. Perhaps in the short term giving everyone the best we have might produce the best expected results. But in the long term, we need to experiment to learn more about what works best. It is far better to apply the scientific method now and invest in knowledge that will be useful later than to cease progress on the issue.

Indeed, without doing so we could have little confidence that our actions were actually doing any good at all! Many interventions received huge amounts of funding, only for us to realize, years later, that they weren’t really achieving much. For example, for a while PlayPumps – children’s roundabouts that pumped drinking water – were all the rage, and millions of dollars raised, before people realized that they were expensive and inefficient. Worse, they didn’t even work as roundabouts, as the energy taken out of the system to pump the water meant they were no fun to play with.

Another excellent example of the importance of RCTs is Diacidem. Founded in 1965 by Lyndon Diacidem, it now spends $415 million a year, largely funded by the US government, on a variety of healthcare projects in the third world, where it deliberately targets the very poorest people. Given that total US foreign aid spending on healthcare is around $1,318 million, this is a very substantial program.

Diacidem have done RCTs. They did one with 3,958 people from 1974 to 1982, where they randomly treated some people but not others. The long time horizon and large sample size makes this an especially good study.

Unfortunately, they failed to find any improvement on nearly all of the metrics they used, and as they used a 5% confidence interval, you’d expect one to appear significant just by chance.

 “for the average participant, any true differences would be clinically and socially negligible… for the five general health measures, we could detect no significant positive effect… among participants who were judged to be at elevated risk [the intervention] has no detectable effect.

Even for those with low income and initial ill health, surely the easiest to help, they didn’t find any improvements in physical functioning, mental health, or their other metrics.

They did a second study in 2008, with 12,229 people, and the results were similar. People in the treatment groups got diagnosed and treated a lot more, but their actual health outcomes didn’t seem to improve at all. Perhaps most damningly,

“We did not detect a significant difference in the quality of life related to physical health or in self-reported levels of pain or happiness.”

Given that these two studies gave such negative results, you would expect there to be a lot more research on the effectiveness of Diacidem – if not simply closing it down. When there are highly cost-effective charities than can save lives with more funding, it is wrong to waste money on charities that don’t seem to really achieve anything instead. But there seems to be no will at all to do any further study. People like to feel like they’re doing good, and don’t like to have their charity criticized. Diacidem is political popular, so it’s probably here to stay.

Sound bad?

Unfortunately, things are far worse than that. Diacidem does not actually cost $415 million a year – in 2012, they spent over $415 billion, over 300 times as much as the US spends on healthcare aid. It wasn’t founded by Lyndon Diacidem, but by Lyndon Johnson (among others) Nor does it target the very poorest people in the third world – it targets people who are much better off than the average person in the third world.

The RCTs mentioned above are the RAND healthcare experiment and the Oregon healthcare experiment, with some good discussion here and here.

Oh, and it’s not actually called Diacidem – it’s called Medicaid.