andreas baumann, numbers guy.

statistics, religion, game theory, sociology.

The end of liberal religion?

A classical theme in the sociology of religion is secularisation: the disappearance of religion as such in the modern world, the disintegration of the “sacred canopy” (Berger) or the “disenchantment of the world” (Weber). The secularisation thesis was pretty uncontested until ca. the 1970s, where the New Religious Movements drawing adherents from the counterculture of the 60s and the Iranian Revolution led scholars to question the dogma of disappearing religion.

However, even though religion might be returning, maybe we need to think about what forms of religion are disappearing and what forms remain. The characteristic forms of NRMs in the 60s were rather obscure religions such as the ISKCON (probably better known as the Hare Krishna movement), Transcendental Meditation or something like that. The Iranian revolution marked the upsurge of a more literalist Shia Islam. The Moral Majority of the 1980s wasn’t built on Episcopalianism or Presbyterianism, classic mainline American Protestant denominations; rather, it relied heavily on Evangelicals and Baptists.

Looking at the American or European religious landscapes of today, you notice something odd; the liberal religion of yesterday, the faiths of Tillich or Bultmann seem to be on the wane. The world of the future may be the world of Dawkins and Khomeini, not Tillich or Eisenhower.

How do we measure religiosity?

I’ve recently been thinking about how to accurately measure religiosity. Of course, this depends heavily on what your idea about religiosity is (what “religiosity” really means in your theoretical framework).

Say religion is a good, and religiosity is a measure of preference for spending ressources – time, money, devotion (an intensely scarce good) – on this good versus other goods or services. This is consistent with some of the common items used to measure religiosity, such as church attendance or incidence of prayer. This works both for an exogenous and endogenous conceptions of religiosity.

Your problem then lies in defining spending on religious goods and services. Is yoga religion? Is astrology? Imagine a situation where you want to measure consumption of soft drinks. “Soft drink” is a pretty stable and uncontested concept, so you don’t really have a problem in defining this. Measuring religiosity by measuring participation in traditional church activities correspondends to measuring soft drink consumption by Coke sales, because you miss a lot of substitution effects (what if people start drinking 7-Up instead of Coke?).

Another way to do it is to ask respondents to rate themselves on, say, a ten-point scale. This leads to two problems:

  • People might rate themselves compared to their friends, not the population as a whole. This is a problem exactly because people select into social groups consisting of people like themselves. If you’re very religious, it is much more likely that you’ll have a friend that is even more religious than you than it is to know such a person if you’re practically areligious.
  • Religion is a contested contest. When studying religion, you very often run into groups who claim not to be religious, but clearly seem to be religion in some sense. Maybe this problem can be alleviated by terming it “spirituality”.

Yet another way of thinking about measuring it is in terms of cognitive activation. One should expect that very religious persons activate the cognitive religion domain more often, and that it is more salient in their world-interpretation. One would have to measure this in asking questions the explore, say, the religious connotations of ill health or related measures.

 

What’s your implicit model?

I recently read this article (nb: in Danish), where the pediatrician Morten Staberg argues against the legality of circumcision from a medical perspective. I’m not going to address his points, because I doubt that I’ll be able to offer valid points on the medical aspects per se.

Rather, I’d like to focus on one point, where I’m disagreeing with him: what’s the comparison model? He is (implicitly) comparing the current practice of circumcision in Denmark with a state of no circumcision – which is wrong! If you criminalize circumcision, you’ll reduce the number of circumcisions, but you won’t eradicate it. And those who illegally continue to perform circumcision on children will do so in worse sanitary conditions for being forced underground and will be more reluctant to seek out medical advice if adverse effects arise.

In this aspect, it ties in with the prostitution debate: making prostitution illegal won’t eradicate it, but it will lead to some bad effects for the persons involved. We shouldn’t compare the current legal state of prostitution with a state wherein nobody is a prostitute, because that’s not what will result from a ban. The same goes for circumcision.

It’s all about living in the real world.

What we should teach and you should learn.

Normally, the stats curriculum taught to social scientists tend to emphasize inferential techniques such as analysis of variance and regression over descriptive and dimensionality-reducing techniques such as factor analysis or cluster analysis.

Sooner or later, we’re going to have to change this.

The future of data analysis – whether in the natural sciences, computer science or social science – is dealing with “Big Data” (or – as I’ve heard it called – organic data, as opposed to the designed data of a RCT). Normally, when we deal with these complex sets, we have a very large (both in terms of data points and dimensionality) set of informations, and most of the measures contained in this set are very bad measures of the latent traits we’re really interested in. For this reason exactly, it’s going to be more and more important for us to be able to extract the latent traits from the data.

For this reason, I think that majors in sociology, political science, etc. should move towards emphasizing

  • Data harvesting in real life: how to extract the information you’re interested in from a social media or a database,
  • Data processing: How to adapt the data set for use in an investigation.
  • Dimensionality reduction: How to get from the manifest variables in the data set to the latent variables you’re interested in.

Most of this should come as an “add-on” for the regression courses currently offered, not as a substitution. Indeed, maybe a shared foundation in introductory linear algebra is the way to tie these two sets of statistics courses together.

 

Cui bono? Or: context matters.

The non-steroidal anti-inflammatory drug (NSAID) diclofenac has come under some flak recently, since a recent paper showed that it has a risk profile similar to the NSAID rofecoxib (brand name Vioxx), which was withdrawn from circulation for this reason exactly.

NSAIDs function by inhibiting two enzymes, COX-1 and COX-2. Inhibition of COX-1 is typically correlated with stomach complaints, and for this reason, research into selective COX-2 inhibitors have been conducted. However, research findings such as the ones revealed in the paper referenced seem to indicate that selective COX-2 inhibitors is related to increased risk of cardiovascular events. For this reason, the authors recommend that doctors should prescribe non-selective COX inhibitors, and that countries should consider banning diclofenac.

The problem with the paper referenced is that it fails to consider differential applications of NSAIDS. The two major user groups of these drugs are people engaging in sports (and suffering related injuries) and people suffering from arthritis.

Many studies – including the meta-analysis in the paper referenced above – indicate an increased risk of ca. 40% of cardiovascular events when using selective COX inhibitors. For this reason, the authors recommend banning drugs such as diclofenac.

However, while I applaud the authors’ commitment to revealing this increased risk, it is only a problem for one of the user groups, namely, the arthritis sufferers, where increased cardiovascular risk is very prevalent. For the user group consisting of athletes and athletic people – a group with very low levels of cardiovascular risk – the impact of a 40% increase in cardiovascular risk is very low. On the other hand, the adverse effects relating to stomach complaints affects this group as well, and banning selective inhibitors would therefore lead this group to suffer increased adverse effects without a practically significant reduction in risk.

Summa summarum: the adverse effects of drugs cannot be evaluated without considering differential impacts on different user groups. For this reason, the selection of non-selective COX inhibitors for the elderly and selective inhibitors for otherwise healthy people with low cardiovascular risk is – in my opinion – better administered in the dispensation part of the system instead of the regulation part. Physicians can – and should – make contextual decisions which perform better than catch-all decisions in terms of individual welfare.

A sociological defence of the free market.

In my opinion, there are two streaks of defence for the free market: an economical approach that tends to emphasize the optimal allocation of ressources and a philosophical approach emphasizing the emergence of the market from the natural rights of people.

But what are the sociological arguments in favor of the free market? Some of the classical sociologists were not terribly fond of modernity and capitalism: think of Weber’s famous work on the relation between Protestantism (Puritanism) and the rise of capitalism:

Denn indem die Askese aus den Mönchszellen heraus in das Berufsleben übertragen wurde und die innerweltliche Sittlichkeit zu beherrschen begann, half sie an ihrem Teile mit daran, jenen mächtigen Kosmos der modernen, an die technischen und ökonomischen Voraussetzungen mechanisch-maschineller Produktion gebundenen, Wirtschaftsordnung erbauen, der heute den Lebensstil aller einzelnen, die in dies Triebwerk hineingeboren werden – nicht nur der direkt ökonomisch Erwerbstätigen –, mit überwältigendem Zwange bestimmt und vielleicht bestimmen wird, bis der letzte Zentner fossilen Brennstoffs verglüht ist. Nur wie »ein dünner Mantel, den man jederzeit abwerfen könnte«, sollte nach Baxters Ansicht die Sorge um die äußeren Güter um die Schultern seiner Heiligen liegen389. Aber aus dem Mantel ließ das Verhängnis ein stahlhartes Gehäuse werden. Indem die Askese die Welt umzubauen und in der Welt sich auszuwirken unternahm, gewannen die äußeren Güter dieser Welt zunehmende und schließlich unentrinnbare Macht über den Menschen, wie niemals zuvor in der Geschichte. Heute ist ihr Geist – ob endgültig, wer weiß es? – aus diesem Gehäuse entwichen. Der siegreiche Kapitalismus jedenfalls bedarf, seit er auf mechanischer Grundlage ruht, dieser Stütze nicht mehr. (Weber, “Die Protestantische und der Geist des Kapitalismus”, Mohr-Verlag, 203-4).

Likewise, Durkheim was famously cautious about how society was meant to stick together in the modern, industrialised world – the question of social solidarity.

This is also why some conservatives are inherently sceptical towards the market; capitalism is inherently anomic. But this is also what we should emphasize in evaluating capitalism – it has an enormous power in empowering the actor.

Most human societies were massively dominated by the structures they contained. This is what we typically think about as when we adress the lack of social mobility in pre-modern societies. Some vocations were only open to some persons, and people could do very little to amend their situations. Furthermore, due to the level of development in society, most societies had very little variation in professions: most people lived off the land in some way or the other.

Capitalism, the division of labour and the market changed this fundamentally, by bringing about differentiation and growth; less people had to work to produce the most basic of goods, such as foodstuffs. The combination of the disjuncture between heritage and personal career (personified in the idea of the nouveau riche) and the freedom for creative work created by a more effective division of labour meant that an enourmous amount of people were empowered to create their own lives.

In my view, that is the basis of the sociological defence of the market.

Who are “the people”?

In Denmark, the debate is currently raging over whether to reintroduce fixed book prices for the first twelve months on the market; this would allow book sellers and the traditional publishing houses better conditions. On the other hand, it shrinks the availability of cheap crime novels and cookbooks available in supermarket stores – very possibly to the dismay of the ordinary consumer.

This led the Consumers’ Council (Forbrugerrådet) to argue against the regulation of the book market from a consumer’s point of view (nb: link is in Danish). It’s rather rare to see the Consumers’ Council argue against regulation, so that alone makes the topic interesting.

There is some evidence pointing to the Council being justified in it’s arguments; market constraints tend to lead to less adaptability between the demand and supply sides of the market. In that sense, regulation can harm consumers, because it reduces the necessity of publishers to adjust production to the market demand.

However, what is misguided in this consideration is the fact that it only considers current consumers. One thing that is remarkable about books in contrast to almost any other product is that they tend to last forever – not the physical copies, but the content. Right besides my computer I have the collected works of Shakespeare, who died almost 400 years ago – and yet his work lives on.

Considerations involving future generations are not uncommon in politics; for example, they’re very common in considering environmental impact. When we perform cost-benefit analyses of long-run impacts, we typically introduce an intertemporal discount rate – how much weight should we place on events in the future versus effects now? This has a lot of reasons, one of the main reasons being uncertainty, that is, we weigh events taking place in a thousand years less than those that would take place tomorrow, ceteris paribus, because our uncertainty is necessarily greater for the more distant events ^1.

In the above case, the book market was analysed under complete discounting; that is, that no future benefits could be considered. However, I believe that this is wrong. Books are culture, that is, there should a concern for the eternal, not the temporal, when regulating the market.

This also explains why the Danish Conservatives are for this regulation: a central idea in conservative ideology is the idea of the generational contract. This is the idea that since we received this society from our parents, we too have a duty to surrender to our children in good condition. This is a common argument behind conservative conservationism.

I’d argue that this idea can be extended to the cultural domain: we need to support books that aren’t necessarily profitable, but might have lasting cultural impacts. And actually, I’d argue that the fixed book prices are a good way to do this: based on historical evidence, they should increase the willingness to take risks by publishers, without political “winner-picking” in the production of cultural goods.

^1) One of the main criticisms against Bjørn Lomborg was that he set the intertemporal discount rate much higher than others working within environmental economics.

Statisticians a…

Statisticians and Computer Scientists have done a pretty poor job of thinking of names for procedures. Names are important. No one is going to use a method called “the Stalin-Mussolini Matrix Completion Algorithm.” But who would pass up the opportunity to use the “Schwarzenegger-Shatner Statistic.” (Larry Wasserman)

Sampling frames matter.

Sampling is the basis for all survey research, and correspondingly, for a lot of research in the social and biomedical sciences. However, how to sample is not necessarily pondered at the level necessitated by the research question. In the below post, I illustrate this problem.

A suggested sampling frame.Let’s say we want to investigate some quantity X in the population – we’re interested in the entire population. We want a representative sample for a number of reasons (hint: CLT), and therefore we adopt the sampling frame suggested below:

Assumptions:

  • Every household has one and only one landline telephone.
  • All landline telephone numbers are listed in the phone registry.

Procedure

  • Pick a number at random from the phone registry.
  • Dial that number, and if the phone is picked up, ask to talk to the person in the household, whose birthday is up next.
  • Repeat until desired sample size is achieved.

Sounds pretty random, doesn’t it – at least under the assumptions mentioned? Take a moment to think about it.

The point is, of course, that this frame isn’t random. You’re sampling every person with a probability inversely proportional to the number of persons in their household. But bad can that be?

A simulation
Let’s say that we’re hired by a municipality interested in knowing to what degree people use the public pools. In a municipality of 120,000 people, the household distribution is that 57% of households contain one person, 29% two persons and 14% four persons ^1.

Persons living in single-persons households tend to be students, young adults and the elderly. They don’t frequent the pools that much: 50% of them don’t visit the pool at all, while the other half only visit the pools once a year.

Persons in two-person households are young pairs and pairs, where the children have moved out. While the first category don’t really go to the pool, the other category tends to be heavy users. 25% never go to the pool, 25% go to the pool once a year, 25% go five times a year and 25% go eight times.

Persons in the four-person household categories are families; they use the public pools extensively. 25% of them go there five times a year, 25% of them go there six times a year and 50% go there eight times a year.

This of course gives us a mean of 3.58 with a standard deviation of 3.25.

Let’s draw a simple random sample of these people (n = 1000) and look at the results. We find a mean of 3.53 and a 95% CI of [3.33;3.73] – not bad.

However, if we sample according to the scheme above, we would have found a mean of 2.24 and a 95% CI of [2.06;2.42] – rather far from the true mean, which isn’t contained within the CI.

In sum: sampling frames matter. And they matter more than you think.

^1) I’m making all these numbers up.

The US economy is both overregulated and underregulated at the same time.

The US economy is both overregulated and underregulated at the same time.

Nothing is ever simple.

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