i. Silk Road.
“The Silk Routes (collectively known as the “Silk Road”) were important trade routes for goods of all kinds between merchants, pilgrims, missionaries, soldiers, nomads and urban dwellers from Ancient China, Ancient India, Ancient Tibet, the Persian Empire and Mediterranean countries for almost 3,000 years. It gets its name from the lucrative Chinese silk trade, which began during the Han Dynasty (206 BCE – 220 CE).
Extending 4,000 miles (6,500 km), the routes enabled traders to transport goods, slaves and luxuries such as silk, satin, hemp and other fine fabrics, musk, other perfumes, spices, medicines, jewels, glassware and even rhubarb, as well as serving as a conduit for the spread of knowledge, ideas, cultures, zoological specimens and some non-indigenous disease conditions between Ancient China, Ancient India, Asia Minor and the Mediterranean. Trade on the Silk Road was a significant factor in the development of the great civilizations of China, India, Egypt, Persia, Arabia, and Rome, and in several respects helped lay the foundations for the modern world. Although the term the Silk Road implies a continuous journey, very few who traveled the route traversed it from end to end. For the most part, goods were transported by a series of agents on varying routes and were traded in the bustling markets of the oasis towns. […]
By the time of Herodotus (c. 475 BCE), the Persian Royal Road ran some 2,857 km from the city of Susa on the Karun (250 km east of the Tigris) to the port of Smyrna (modern İzmir in Turkey) on the Aegean Sea. It was maintained and protected by the Achaemenid Empire (c.500–330 BCE), and had postal stations and relays at regular intervals. By having fresh horses and riders ready at each relay, royal couriers could carry messages the entire distance in nine days, though normal travellers took about three months. […]
The Mongol expansion throughout the Asian continent from around 1207 to 1360 helped bring political stability and re-establish the Silk Road (via Karakorum). It also brought an end to the Islamic Caliphate’s monopoly over world trade. Since the Mongol had dominated the trade routes, it allowed more trade to come in and out of the region. Merchandise that did not seem valuable to the Mongols was often seen as very valuable by the west. As a result, the Mongol received in return a large amount of luxurious goods from the West.”
The mongol? But those were just a small group of nomadic people living around the north-western borders of China, right – how come they had such a huge influence on world trade? Well, perhaps you know but a lot of people don’t: “[The Mongol Empire] is commonly referred to as the largest contiguous empire in the history of the world. At its greatest extent it spanned 9,700 km (6,000 mi), covered an area of 24,000,000 km2 (9,300,000 sq mi), 16% of the Earth’s total land area”.
ii. House of Medici.
iii. Rosetta Stone (this is a featured article).
“The Rosetta Stone is an ancient Egyptian granodiorite stele inscribed with a decree issued at Memphis in 196 BC on behalf of King Ptolemy V. The decree appears in three scripts: the upper text is Ancient Egyptian hieroglyphs, the middle portion Demotic script, and the lowest Ancient Greek. Because it presents essentially the same text in all three scripts (with some minor differences between them), it provided the key to the modern understanding of Egyptian hieroglyphs.”
iv. RNA interference (this is also a featured article).
vi. Blood type.
I decided to start out with this:
…in order to illustrate that you could probably write a not too dissimilar post about other countries as well. Also, it’s a nice image. Image credit: Wikipedia. “Description: Sex ratio total population. Pink = Female higher than male, Green = Equal, Blue = Male higher than female.”
This post will only deal with China. Here’s some related stuff about India.
So anyway, I was skimming a few world bank working papers and I found this one (pdf), which I decided to cover in a bit of detail here. It’s called China’s Marriage Market and Upcoming Challenges for Elderly Men and it’s written by Monica Das Gupta, Avraham Ebenstein & Ethan Jennings Sharygin. Some stuff from the paper:
“The Chinese census in 2005 reflected a staggering sex ratio at birth of 119, implying that each year there are roughly 1 million more boys born than girls.3 For cohorts born between 1985 and 2005, we estimate that there are 27 million more men than women4, implying a large number of men will fail to marry. […]
We demonstrate two key facts regarding the Chinese marriage market using historical census microdata from 1990 and 2000. First, economic status is a crucial predictor of marital probability for men in China. We use years of education as the closest proxy for status, and document that while there is almost universal marriage for highly educated men, lower rates of marriage prevail among men of lower education. By contrast, the marriage market for women cleared: women across the educational distribution enjoy nearly universal marriage, and are able to engage in hypergamy, choosing spouses of higher status and income. Second, since many women migrate for the purpose of marriage, it seems very likely that in the coming decades the collapse of marital prospects for men will occur in poor areas of the country with low educational attainment. […]
The results paint a grim picture for China’s ability to care for these men under the current policy structure of social assistance and social insurance programs that are primarily locally funded (Wang 2006, World Bank 2009). We estimate that in the absence of major redistribution of education and employment opportunities across China, the marriage squeeze will be in China’s poorer regions with large minority populations.7 Thus it will not necessarily be the more prosperous eastern regions of China with the most skewed sex ratio at birth that will experience high marriage failure rates among men. Rather, the poorer provinces ─ with more balanced sex ratios at birth ─ will bear a disproportionate share of the social and economic burden of China’s unmarried and childless men.”
How big is the difference in marriage rates between the successful males and the not quite so successful males, I hear you ask? Well, the paper states that: “over 98% of college graduates successfully marry by age 35 whereas the proportion is under 90% for men with less than a primary education.” One way to look at those numbers is that ‘that’s actually not that big of a difference’ – it’s around 9 out of 10 or more in both cases, right? But who are we actually comparing again? – another way to look at that is that males with less than a primary education are more than 5 times as likely to not succesfully marry by age 35. To me, that sounds like a huge difference, and it’s expected to get even worse over time: “over 10 percent of men with less than primary school education aged 30+ in 2030 are projected never to marry, and this figure increases to almost half in 2050”. Of course one might argue that economic growth increases mobility (so that even poor men might be able to move to find females willing to marry them) and ‘historical data are historical data’ which perhaps shouldn’t be given as much weight, given how much Chinese society has changed over the past decades. But rural China is still very poor and it isn’t growing very much compared to the rest – many of the people who have not left already for the urban provinces are people who can’t afford to, and they can’t really afford to save either so there’s not in my mind any compelling reason to think they will be able to afford to move in the future. Incidentally, it’s not really that hard to set up a model where you have decreased mobility over time even though the poor group has a positive net savings rate. Property prices are functions of local economic conditions, and if an area experiences significant income growth whereas another area does not and the people living in the poorer area are neither able to save enough money over time to at least keep up with the income growth of the richer area nor can afford to move there in the short run, the relative property price differential and the costs of moving will go up over time, even though the poor single guy might have a significant positive net savings rate. A very simplified model illustrating this could go along these lines:
Average income of ‘poor area’ residents: 10.
Average income of ‘rich area’ residents: 100.
Poor area income growth rate: 0%.
Rich area income growth rate: 10%
I shall assume that income growth rates and housing price growth rates are identical. In reality, housing prices are probably growing faster than income for the relevant demographic in the rich area and slower than income in the poor area. Let’s say the poor guy saves 20% of his income/year, i.e. 2 mu (‘monetary units’)/period. Say he invests that money in the rich area, earning 10%/year. After 10 years, he’ll have saved ~35 mu. How much will a house in the rich area that used to cost 100 mu cost after 10 years? 259. At the beginning, the poor guy was 98 mu short of being able to buy a house in the rich area – after ten years he’s now more than 200 mu short, even though he had a very high savings rate given his income and even though he earned a quite nice return on investment during that period. The property price differential was 90 mu to begin with, it’s 249 mu after 10 years. Maybe the effect sizes won’t be as large as assumed in the paper, but some of the dynamics described in the paper will probably play out to some degree.
Some more numbers and stuff related to these remarks from the paper:
“Poverty in China is heavily concentrated in the rural areas. Different measures of poverty all paint the same picture: while nearly 30 percent of the rural population was poor in 2005, this applied to only 5 percent or less of the urban population […] The vast majority of the poor in 2003 lived in rural areas, and poverty is most heavily concentrated in the northwestern and southwestern regions […] Both rural and urban incomes have continued to grow, but the rural-urban gap has continued to widen […]
Significant proportions of urban workers are covered by formal social insurance programs: in 2007, around half of workers had pension coverage, 45 percent had Basic Medical Insurance, and 40 percent had unemployment insurance and work injury insurance […] The rural pension system (funded mainly by personal contributions and collective subsidies) covered only about 10-11% of the rural labor force (World Bank 2009: Table 6.65), and coverage of the farm-based elderly population appeared to be particularly limited. Beneficiaries were highly concentrated in a few (mostly wealthy) provinces. […]
Since men who are not as educated, healthy, and able to earn well tend to fail to attract a bride, they are likely to be heavily represented among those who are unable to save adequately for their old age, or labor heavily into their old age. They are the most vulnerable to income and illness shocks, since they cannot smooth fluctuations in household income by pooling earnings from spouses or children. Unmarried individuals are also more likely to be living without family to serve as caregivers (Table 5). For example, in the 2000 census, 65% of those aged 65-80 who had ever-married were co-residing with younger kin, compared with only 20% of those never-married. Moreover, levels of co-residence have dropped sharply in recent decades (Table 5), and this trend can be expected to continue. The men who fail to marry are among the least likely to be able to save for their old age, to work in their old age, and to have access to old age support from family members.”
Last, a few tables (click to view full size):
Wu Bao, Di Bao and Tekun Hu are various social assistance programs: “The Te Kun program provides cash assistance to very poor and incapacitated residents of less-developed areas, at the discretion of the local officials. The Wu Bao program, dating from the 1950s, sought to ensure that no section of the population remained destitute.11 In 2006, the State Council issued regulations that shift financing responsibility for wubao from village reserves to local fiscal budgets (World Bank 2008:79-80). The Di Bao program, also known as the Minimum Living Standard Scheme, provides subsidies and in-kind transfers to those living below a certain poverty line.”
More than 45 % of the total income of Chinese urban residents above the age of 60 comes from pensions; the number for rural residents in the same age group is about one-tenth of that, 4.6 %. Also take note of the family support numbers.
i. “Trying is the first step toward failure.” Homer Simpson.
ii. “Truth and clarity are complementary.” Niels Bohr.
iii. “If you can’t read and write you can’t think. Your thoughts are dispersed if you don’t know how to read and write. You’ve got to be able to look at your thoughts on paper and discover what a fool you were.” Ray Bradbury. Me: “were”?
iv. “one reason to move to evidence-based practice is that doctors aren’t trained as scientists. If anything, most medicine seems more of a craft than a science. That’s not to say that the practice of medicine doesn’t benefit from science; of course it does. But doctors aren’t trained to evaluate the science behind what they’re told; certainly not as well trained as those who actually do the research.
My father did research biology in a medical school. He tended to regard most doctors as plumbers; admittedly very useful ones to have around. But what they did wasn’t, to his mind, anything akin to scientific research or anything that might lead to the ability to evaluate same.” – Robert Levine. Related link. Also, this.
v. “It is well, when judging a friend, to remember that he is judging you with the same godlike and superior impartiality.” Arnold Bennett.
vi. “The traditional way of thinking about learning at a university is: there’s somebody who’s a teacher, who actually has some amount of knowledge, and their job is figuring out a way of communicating that knowledge. That’s literally a medieval model; it comes from the days when there weren’t a lot of printed books around, so someone read the book and explained it to everybody else. That’s our model for what university education, and for that matter high school education, ought to be like. It’s not a model that anybody’s ever found any independent evidence for.” Alison Gopnik, via John Hawks.
vii. “All opinions are not equal. Some are a very great deal more robust, sophisticated and well supported in logic and argument than others.” Douglas Adams.
viii. “If a little knowledge is dangerous, where is the man who has so much as to be out of danger?” T. H. Huxley. His advice? “Try to learn something about everything and everything about something.”
ix. “For a long time it has seemed to me that life was about to begin – Real Life. But there was always some obstacle in the way, something to be got through first, some unfinished business, time still to be served, a debt to be paid – then life would begin. At last it dawned on me that these obstacles were my life.” Alfred d’Souza.
x. “Power calls to those who are hungry for power, and there are hungry idiots everywhere.” Laura Anne Gilman.
xi. “Few men have virtue to withstand the highest bidder.” George Washington.
xii. “Though familiarity may not breed contempt, it takes off the edge of admiration.” William Hazlitt
xiii. “He will never have true friends who is afraid of making enemies.” -ll-
xiv. “Men of genius do not excel in any profession because they labour in it, but they labour in it because they excel.” -ll-
xv. “Great thoughts reduced to practice become great acts.” -ll-
xvi. “Modesty is the lowest of the virtues, and is a real confession of the deficiency it indicates. He who undervalues himself is justly undervalued by others.” -ll-
xvii. “Life is a sexually transmitted terminal disease.” Lewis Grizzard. The quote isn’t correct but if you add ‘human’ in front of life – which makes sense given the target group – I guess it works. It’s easy to forget but if you look at the entire history of life on Earth, that whole sexual reproduction-thing was really quite late to the party.
Maybe I’ve blogged some of this before (in the comments?) but I couldn’t find the stuff in the archives, so I decided to write this post either way. The post contains a few graphs, click on them to view them in full size.
First, some stuff from Martin Paldam’s Development and foreign debt: The stylized facts 1970-2006 (link). This is about the debt of developing countries. From the abstract:
“The paper uses the data from the incomplete debt cycle for the LDC world from 1970 onwards to tell the typical story of debt. Two debt stories are contrasted: A good debt story: Here countries borrow and invest wisely, so that they grow more. A bad debt story: Here countries borrow when they are in crisis, and the debt grows and generates low growth in the next couple of decades. The analysis concentrates on two relations: (R1) the relation between borrowing and growth, and (R2) the relation between initial debt and growth. Both relations are negative, so essentially the stylized story of debt is a story of bad debt.”
Here’s a figure, each group consists of 15 countries:
The debt of Group 1 didn’t get paid off, in case you were in doubt. They got debt relief and debt ‘restructuring’ (/’managed default’). Over time debt service went down, not up. Here’s a bit on the political economy of the debt accumulation:
“One may also ask the simple question: Why does a country borrow when it has a crisis? Is it to adjust quicker to the crisis or to be able to finance non-adjustment? Our results certainly suggest that the latter possibility dominates the picture.
The analysis has showed that debt accumulation is normally associated with some underlying problem leading to economic crises. Somehow things are going badly, and the political system is unable to handle the crisis. A foreign loan provides some wiggle room, and this is surely used to solve the most pressing problem. The reader may then ask what decision makers are most likely to take this problem to be. Think of the choice between a political stabilization and a balance-of-payments stabilization.
A political stabilization means that the popularity/support of the government is increased. This can be done either by satisfying the demands of the voters or by paying off some pressure group, such as the military, the unions etc. In both cases it costs money. Here the foreign loan comes in handy. It appears that such solutions are of a short-run character.
A balance-of-payments stabilization inevitably means that domestic absorption has to be reduced. It is obvious that this is painful and likely to cost the government some support, thus it is almost the reverse of a political stabilization. Hence, it is likely that the government may fully or partly shy away from solving the balance-of-payments crisis.”
Next, some stuff from The future of public debt: prospects and implications, by Cecchetti, Mohanty and Zampolli (link). I’ll quote from it below, but really you should read it all:
“Since the start of the financial crisis, industrial country public debt levels have increased dramatically. And they are set to continue rising for the foreseeable future. A number of countries face the prospect of large and rising future costs related to the ageing of their populations. In this paper, we examine what current fiscal policy and expected future age-related spending imply for the path of debt/GDP ratios over the next several decades. Our projections of public debt ratios lead us to conclude that the path pursued by fiscal authorities in a number of industrial countries is unsustainable. Drastic measures are necessary to check the rapid growth of current and future liabilities of governments and reduce their adverse consequences for long-term growth and monetary stability. […]
The financial crisis that erupted in mid-2008 led to an explosion of public debt in many advanced economies. Governments were forced to recapitalise banks, take over a large part of the debts of failing financial institutions, and introduce large stimulus programmes to revive demand. According to the OECD, total industrialised country public sector debt is now expected to exceed 100% of GDP in 2011 – something that has never happened before in peacetime.2 As bad as these fiscal problems may appear, relying solely on these official figures is almost certainly very misleading. Rapidly ageing populations present a number of countries with the prospect of enormous future costs that are not wholly recognised in current budget projections. The size of these future obligations is anybody’s guess. As far as we know, there is no definite and comprehensive account of the unfunded, contingent liabilities that governments currently have accumulated.”
“existing studies report that the magnitude of the long-term fiscal imbalance – the present value of unfunded liabilities arising from ageing – is very large. Hauner et al (2007) estimate the change in the primary balance required to equate the net present discounted value of all future revenues and non-interest expenditures to the debt levels prevailing at the end of 2005 for seven major industrial countries (Canada, France, Germany, Italy, Japan, the United Kingdom and the United States). The authors report that in order for these countries to pay off all their financial liabilities, they would require an average improvement in their budget balance excluding interest payments of 4.5% of GDP. For the United States and Japan, the estimate is 6.9% and 6.2%, respectively.
Other estimates are similar in magnitude. For example, Gokhale (2009) presents a measure of the long-term fiscal imbalance faced by 23 industrial countries. His estimates suggest that, for financing future benefits without future tax increases, the United States and major European countries would be required to generate an annual present value surplus of the order of 8–10% of 2005 GDP over the period to 2050.”
You can quibble over the details in the following, and I’m not a big fan of the ‘government total revenue and non-age-related primary spending remain a constant percentage of GDP at the 2011 level’-assumption, because that’s just not going to work out. But then again, that’s part of the whole point of the exercise, realizing that fact. An important point I forgot to include/remark upon in the first version of the post is that a big chunk of the projected deficits below are structural.
“We now turn to a set of 30-year projections for the path of the debt/GDP ratio in a dozen major industrial economies (Austria, France, Germany, Greece, Ireland, Italy, Japan, the Netherlands, Portugal, Spain, the United Kingdom and the United States). We choose a 30-year horizon with a view to capturing the large unfunded liabilities stemming from future age-related expenditure without making overly strong assumptions about the future path of fiscal policy (which is unlikely to be constant). In our baseline case, we assume that government total revenue and non-age-related primary spending remain a constant percentage of GDP at the 2011 level as projected by the OECD. Using the CBO and European Commission projections for age-related spending, we then proceed to generate a path for total primary government spending and the primary balance over the next 30 years.12 Throughout the projection period, the real interest rate that determines the cost of funding is assumed to remain constant at its 1998–2007 average, and potential real GDP growth is set to the OECD-estimated post-crisis rate.13
From this exercise, we are able to come to a number of conclusions. First, in our baseline scenario, conventionally computed deficits will rise precipitously. Unless the stance of fiscal policy changes, or age-related spending is cut, by 2020 the primary deficit/GDP ratio will rise to 13% in Ireland; 8–10% in Japan, Spain, the United Kingdom and the United States; and 3–7% in Austria, Germany, Greece, the Netherlands and Portugal. [remarks about Italy that are actually quite fun to read now…] in the baseline scenario, debt/GDP ratios rise rapidly in the next decade, exceeding 300% of GDP in Japan; 200% in the United Kingdom; and 150% in Belgium, France, Ireland, Greece, Italy and the United States. And, as is clear from the slope of the line, without a change in policy, the path is unstable. This is confirmed by the projected interest rate paths, again in our baseline scenario. Graph 5 shows the fraction absorbed by interest payments in each of these countries. From around 5% today, these numbers rise to over 10% in all cases, and as high as 27% in the United Kingdom.”
This is also part of why I posted a link to Paldam’s paper in this post. Look at the first graph again. Many of these modern, developed countries will end up in the group of basket case countries if the people in charge don’t change their ways.
People often note that it’s a bad idea to compare small European countries with a country that is so big that it is comparable in size to the continent that the small country is a part of. I’ll go into a bit more detail about the differences in this post.
So, in a comment I left over at MR I noted that:
‘The United States is 3 times as big as EU-15 used to be, and EU-15 included pretty much all of the countries in Western Europe that people from the US like to compare to their own country (Italy, Germany, Spain, France, UK, Sweden…)’
Here’s the map:
It’s not ‘completely true’, but it’s very close – the area of EU-15 was 3,367,154 km^2 (link). The area of the United States is 9.83 million km^2.
Some more random numbers, I used wikipedia’s numbers and I couldn’t be bothered to add links because it would have taken forever and nobody would follow them anyway – you can look it up if something sounds really wrong. Texas: 696,200 km^2. France: 674,843 km^2. (Metropolitan France – i.e. ‘France-France (+Corsica)’: 551,695 km^2). Spain: 504,030 km^2. California: 423,970 km^2. Germany: 357,021 km^2. Denmark: 43,075 km^2. Netherlands: 41,543 km^2.
The red bit in the picture below is larger than any country in Europe which is not Russia (or another way to visualize it: That bit is actually significantly larger than the Iberian Peninsula in the map above). Maybe the scales aren’t completely similar, but they’re actually not really that far off:
If you take a trip in Europe from Venezia, Italy to Amsterdam, Netherlands, you’ll travel ~1200-1300 kilometers depending on the route. The lenght and width of Texas are both in the neighbourhood of ~1,250 km.
Now, Arizona is another southern US state with an area of 295,254 km^2 and a population of 6,4 million people. The Netherlands’ population is estimated at 16.85 million. If you combine the populations of Netherlands (16,85), Denmark (5,5) and Belgium (11 mill), those 33 million people are distributed over an area of ~115.000 km^2. The (smaller) combined populations of Texas (25,1) and Arizona (6,4) have roughly a million square kilometers to deal with.
Does it make better sense to compare Texas with France? And those small countries with, say, the state of New York? It probably would. But it’s really hard to find good matches here, in particular due to the problem with population density differences. If you do find areas that match on this metric, odds are they don’t exactly match on other key metrics. The population density of the United States as a whole is 33,7/km^2. If you scale that up by a factor of ten, you get to the third most densely populated state, Massachusetts (324.1 /km^2). The population density of Massachusetts is somewhat lower than both Belgium’s (354.7/km^2) and Netherlands’ (403/km^2). The population density of Germany (229/km^2) is comparable to that of Maryland (229.7/km^2), which is in the US top five – Germany is almost 7 times as densely populated as ‘the US as a whole’. The population density of Great Britain is 277/km^2, comparable to Connecticut’s (285.0/km^2) – the state of Connecticut is btw. #4 on the US list. Italy is at 201.2/km^2, between Delaware and Maryland – it would be on the top 6 if it was a US state. Americans like to use the expression ‘France and Germany’, but at least in terms of population density, there’s a huge difference between these two countries that I’m not sure they’re aware of: The population density of France is much lower (116/km^2) than that of Germany, and rather more comparable to that of Spain (93/km^2). All US states outside the top ten have population densities well below 100/km^2, so note that even though Spain and France are relatively sparcely populated in a Western European context, France would be well within the top 10 and Spain just outside top 10 if the two countries were US states. The average population density of the entire European Union, including a lot of Eastern European countries most Americans couldn’t find on a map, is about the same as that of France, 116.2/km^2; 3.5 times as high as the US average.
The population density of Iceland is 3.1/km^2. As mentioned, the US average is 33.7/km^2 and Belgium’s density is 354.7/km^2. Remember these magnitudes. And yes, I know that the US population density is not homogenous and that a lot of it is almost empty. The population density of Europe isn’t homogenous either – to take an example, approximately one eighth of the German population – 10 million people – live in the very small Rhine-Ruhr metropolitan region (7,110 square kilometers, or less than 2% of the area). A fifth (12+ mill) of the French population live in the Paris metropolitan area. On the other hand, the population density of Norway, which even though she is a bit of an outlier is still very much a part of Western Europe, is 12,5/km^2, comparable on that metric to, say, Nevada (9.02/km^2) in the US.
If you look at differences in the US internally, when it comes to the 10 most densely populated states the one that is situated the most to the west of these is Ohio (the state border of which is still within 500 km of the Atlantic Ocean). Here’s a map:
Remember here that these numbers are people/sq mile, so to compare the numbers there with the rest of the numbers in this post you need to divide by ~2,6 or so. I found this comparable map of Europe convenient both because it gives density limits in sq. miles and because it’s a lot more fine grained than just data on the national level:
Last of all: Languages! Here’s the European map:
Let’s just say that a map of the US would look different. Yeah, a lot has been written about the Spanish/English-thing going on in the US. Well, intranational language barriers and -linguistic diversity aren’t exactly unknown phenomena in Europe either, despite the small size of the countries involved. A thing worth remembering here is also that in many of the bilingual regions of Europe highlighted here, English is the third language. If you’re a US tourist visiting some European bilingual region and you’re annoyed people don’t speak much English, ask yourself how many areas of the US you can think of where people can hold conversations in, say, English, Spanish and French.
Update: To the many visitors who followed Razib Khan’s link or the brownpundits link and have never seen this blog before – welcome! If you liked the post, take a look around – I’ve been blogging for 5+ years and it’s not unlikely that I’ve written other stuff that might be of interest. For instance, did you know that 90 percent of the human population lives on the Northern Hemisphere? I didn’t, before I wrote this.
I tend to think that the last couple of wikipedia articles posts I’ve posted weren’t all that good, sorry about that. Anyway, some of these articles were great:
“In social science generally and linguistics specifically, the cooperative principle describes how people interact with one another. As phrased by Paul Grice, who introduced it, it states, “Make your contribution such as it is required, at the stage at which it occurs, by the accepted purpose or direction of the talk exchange in which you are engaged.” Though phrased as a prescriptive command, the principle is intended as a description of how people normally behave in conversation.
Listeners and speakers must speak cooperatively and mutually accept one another to be understood in a particular way. The cooperative principle describes how effective communication in conversation is achieved in common social situations.
The cooperative principle can be divided into four maxims, called the Gricean maxims, describing specific rational principles observed by people who obey the cooperative principle; these principles enable effective communication.” […]
Maxim of Quality
*Do not say what you believe to be false
*Do not say that for which you lack adequate evidence.
Maxim of Quantity
Quantity of Information
*Make your contribution as informative as is required (for the current purposes of the exchange).
*Do not make your contribution more informative than is required.
Maxim of Relevance
Be relevant. […]
Maxim of Manner
Avoid obscurity of expression.
Be brief (avoid unnecessary prolixity).
Even though the article makes it clear that these maxims are not to be considered prescriptive but rather descriptive, the piece in which he introduces them basically contains no data analysis whatsoever. And really, who needs data anyway when you can just postulate that “it is just a well-recognized empirical fact that people do behave in these ways…” (p.28-29). If I ever happen to refer to these maxims in the future, expect me to apply them as sensible prescriptive rules and nothing else; and seriously, I really think the guy who made them up should have limited himself to that as well. It’s not that they are wrong, it’s worse than that – I don’t see how they’re even testable. It’s perfectly simple to come up with examples where the maxims are violated and examples where it’s not hard to argue that they are not, but there’s a lot of stuff in between. Wikipedia also has an article on some related politeness maxims.
Incidentally, following simple ‘rules’ like these – whether you are explicitly aware of the fact that you do it or not – is actually pretty important in some contexts. I can think of at least two Danish bloggers (I won’t name names) who I’ve debated in the past who (…”in my mind”…; remember that this is a big part of the reason why it’s so hard to evaluate these maximes empirically – people have different standards of evidence, information requirements, ect.) so systematically violated these maxims every time we had a discussion that I eventually gave up any interaction with them. Obfuscation, ambiguity, irrelevant remarks, arguments based on insufficient data – that stuff is poison to any debate and I won’t engage people who add a lot of that stuff to the conversation, whether they do it deliberately or not. (I should probably add here that none of the readers who currently comment here are even close to violating any kind of ‘code of conduct-rules’ – you do brilliantly (which is why you should all comment more often 🙂 ). Of course, the above remarks also point to a second problem related to the maxims and the cooperative principle: Optimizing the efficiency of the information exchange that takes place is often not a main goal when people communicate, and doing it anyway can be suboptimal. Think of gossip related to bonding and tribal affiliations/coalition forming. Think of verbal communication along the lines of this discussion between Will and ‘the jerk’ – these kinds of discussions are status games and little else; zero sum, the winner gets the girl. Political discussions are often zero-sum; ‘the winner’ gets more power and status, ‘the loser’ loses face. There are a lot of settings where humans communicate with each others and where an approach of cooperation does not make sense even in theory.
“The French and Indian War is the common American name for the war between Great Britain and France in North America from 1754 to 1763. In 1756, the war erupted into the world-wide conflict known as the Seven Years’ War and thus came to be regarded as the North American theater of that war.” […] The war in North America officially ended with the signing of the Treaty of Paris on February 10, 1763, and war in the European theatre of the Seven Years’ War was settled by the Treaty of Hubertusburg on February 15, 1763. The British offered France a choice of either its North American possessions east of the Mississippi or the Caribbean islands of Guadeloupe and Martinique, which had been occupied by the British. France chose to cede Canada, and was able to negotiate the retention of Saint Pierre and Miquelon, two small islands in the Gulf of St. Lawrence, and fishing rights in the area. The economic value of the Caribbean islands to France was greater than that of Canada because of their rich sugar crops, and they were easier to defend. The British, however, were happy to take New France, as defense was not an issue, and they already had many sources of sugar. Spain, which traded Florida to Britain to regain Cuba, also gained Louisiana, including New Orleans, from France in compensation for its losses. Navigation on the Mississippi was to be open to all nations. […]
The war changed economic, political, governmental and social relations between three European powers (Britain, France, and Spain), their colonies and colonists, and the natives that inhabited the territories they claimed. France and Britain both suffered financially because of the war, with significant long-term consequences. […] The Seven Years’ War nearly doubled Britain’s national debt. The Crown, seeking sources of revenue to pay off the debt, attempted to impose new taxes on its colonies. These attempts were met with increasingly stiff resistance, until troops were called in so that representatives of the Crown could safely perform their duties. These acts ultimately led to the start of the American Revolutionary War.
France attached comparatively little value to its North American possessions, especially in respect to the highly profitable sugar-producing Antilles islands, which it managed to retain. Minister Choiseul considered he had made a good deal at the Treaty of Paris, and philosopher Voltaire wrote that Louis XV had only lost “a few acres of snow”. For France however, the military defeat and the financial burden of the war weakened the monarchy and contributed to the advent of the French Revolution in 1789.”
Here are two maps from the article (I’ve modified the first a bit to make it fit the page, but no significant detail was lost. I decided it was better to just put in a thumbnail of the other, click on it to view that one in full resolution):
iv. Chemotaxis. Of course I stumbled upon this one while reading Human Microbiology.
“Chemotaxis is the phenomenon in which somatic cells, bacteria, and other single-cell or multicellular organisms direct their movements according to certain chemicals in their environment. This is important for bacteria to find food (for example, glucose) by swimming towards the highest concentration of food molecules, or to flee from poisons (for example, phenol). In multicellular organisms, chemotaxis is critical to early development (e.g. movement of sperm towards the egg during fertilization) and subsequent phases of development (e.g. migration of neurons or lymphocytes) as well as in normal function. In addition, it has been recognized that mechanisms that allow chemotaxis in animals can be subverted during cancer metastasis.
Positive chemotaxis occurs if the movement is towards a higher concentration of the chemical in question. Conversely, negative chemotaxis occurs if the movement is in the opposite direction.” […]
“The overall movement of a bacterium is the result of alternating tumble and swim phases. If one watches a bacterium swimming in a uniform environment, its movement will look like a random walk with relatively straight swims interrupted by random tumbles that reorient the bacterium. Bacteria such as E. coli are unable to choose the direction in which they swim, and are unable to swim in a straight line for more than a few seconds due to rotational diffusion. In other words, bacteria “forget” the direction in which they are going. By repeatedly evaluating their course, and adjusting if they are moving in the wrong direction, bacteria can direct their motion to find favorable locations with high concentrations of attractants (usually food) and avoid repellents (usually poisons).
In the presence of a chemical gradient bacteria will chemotax, or direct their overall motion based on the gradient. If the bacterium senses that it is moving in the correct direction (toward attractant/away from repellent), it will keep swimming in a straight line for a longer time before tumbling. If it is moving in the wrong direction, it will tumble sooner and try a new direction at random. In other words, bacteria like E. coli use temporal sensing to decide whether life is getting better or worse. In this way, it finds the location with the highest concentration of attractant (usually the source) quite well. Even under very high concentrations, it can still distinguish very small differences in concentration. Fleeing from a repellent works with the same efficiency.”
vi. Hermann Detzner (if you haven’t heard about that guy, don’t beat yourself up. Neither had I, until I read this article. I knew a little about the Japanese holdouts after WW2 before reading this, but until now I had never heard about holdouts from WW1.)
(I know there’s been a lot of video posts recently, this is almost turning into a vlog, but…)
Some additional data: I’ve previously blogged a Danish version of the ‘health care spending as a percentage of GDP’ -graph, going back to ~ 1970. The title is in Danish but it really shouldn’t be much of a problem for non-Danish speaking readers to figure out what’s going on:
This did not turn out like the Goiânia accident, but it’s still a scary story that illustrates that these kinds of problems are likely to persist over time. I’ve decided to quote rather extensively from the piece:
“Compared to a nuclear explosion, a dirty bomb would be a hiccup in terms of destructive force. The real problem would be panic. A light coating of radioactive dust raining down on Manhattan might cause only a minor increase in cancer rates, but it would definitely result in a major national freak-out. Set off at a major port, a dirty bomb would cause a chain reaction of precautionary closures and painstaking inspections that could bring the entire U.S. economy to a crawl within weeks. “The idea that dirty bombs could cause major destruction is complete bullshit. What they could do is cause billions and billions in economic damage,” says James Acton, an analyst at the Carnegie Endowment for International Peace. “Dirty bombs are weapons of mass disruption.”
In the U.S., officials have significantly beefed up security at the nation’s ports since 9/11, and according to the Department of Homeland Security, 99 percent of incoming cargo is now scanned for radiation once it hits U.S. soil.” […]
“So after 10 years and more than $1 billion spent on scanners, radiation detectors, and beefed-up intelligence, most U.S. ports are still scanning containers onshore, after unloading. Unfortunately, the detectors are easily foiled. Lots of harmless things are slightly radioactive — kitty litter, ceramic tiles, even bananas. So most detectors are set to ignore low radiation levels. Basic shielding would be enough to mask all but the strongest sources. “The radiation portals that were deployed in the aftermath of 9/11 are essentially fine, except for three problems: They won’t find a nuclear bomb, they won’t find highly enriched uranium, and they won’t find a shielded dirty bomb,” says Stephen Flynn, a terrorism expert and president of the Center for National Policy. “Other than that, they’re great pieces of equipment.”” […]
“On the day Montagna scanned container 307703 — July 20, a week after it was offloaded — the two men were driving back from a meeting in the nearby town of Varazze. Calimero wasn’t surprised to see Montagna’s name on his cell phone — he sometimes called about bureaucratic stuff. But this was no routine matter.
Montagna quickly told them about his readings, and Calimero and Garbarino headed for the port, stopping at their office to pick up their own gear, well-used radiation detectors packed in padded aluminum cases. They arrived at Voltri less than an hour after Montagna’s phone call and found him and an official standing about 250 yards from container 307703, now moved to an unused area on the eastern edge of the port.
The first thing on everyone’s mind: Was there a nuclear bomb inside? Instruments in hand, Calimero and Garbarino walked toward the container, confirming Montagna’s readings. At 25 yards away, Montagna had measured radiation levels of 0.1 millisieverts per hour. (The maximum allowable exposure for radiation workers in the U.S. is 50 millisieverts per year.) Calimero and Garbarino didn’t want to get anywhere near the thing. The high readings were actually good news. The active ingredients of a nuclear device, plutonium or uranium, can be surprisingly difficult to detect. “Bombs don’t have such high levels,” Montagna says. “If it were a nuclear bomb, there would be much less radiation than was coming out of this thing.” […]
“After arriving and conducting their own analysis, fire department specialists decided to use a line of containers to create a quarantine zone. It wasn’t a great solution, but it bought some time. Over the next few days, Calimero and Garbarino managed to figure out exactly what they were dealing with. The hottest spot was about 2 feet off the ground, in the center of the container’s long left side. The team then brought in one of the most sensitive portable detectors on the market, an $80,000 Ortec HPGe Detective DX-100T. Inside the unit, a 1.65-pound chunk of germanium cooled to -260 degrees Fahrenheit releases electrons when hit with gamma radiation. As they decay, many radioisotopes emit gamma rays, and those occur at specific energy levels. Whatever was in the box was giving off gamma rays at 1,173 and 1,332 kiloelectron volts. It could be only one thing: cobalt-60 slowly alchemizing itself into nickel.
Cobalt-60 is usually sold as a solid piece of metal to be used in medical devices like teletherapy machines and blood irradiators. Other isotopes are better suited for dirty bombs. […] Nobody had any good explanations of why cobalt-60 would be in this container. And even if it wasn’t a bomb, what could they do with the box? It couldn’t stay in the port, but no one in the port would move it. The threat had been downgraded to a serious environmental hazard, but officials still couldn’t entirely rule out some kind of terrorist plot. “The radiation is so high it’s not possible for humans to go inside. We need to use robots,” Garbarino said last spring. “The final answer will come when they extract the source.” […]
Today, Voltri is the gateway to northern Italy’s industrial heartland. In addition to containers, 50,000 cars a year come through the port on their way to dealers across southern Europe. “Historically, Genoa has always based its life on the port,” says Ivan Drogo, head of Multicon, a local business association. “Shutting down the port would shut down Genoa.”
For six months after the container was discovered, officials made no public announcement about it, and the port’s business continued as usual. But rumor spread through the city. For a while, the only reaction was from port workers. Giacomo Santoro, whose FILT union represents most of the port’s longshoremen, claims Voltri management had his members move the container before adequately explaining the risks involved. And because the box spent a week on the dock between the time it was offloaded and when Montagna scanned it, dozens of people may have been unknowingly exposed to dangerous radiation. In protest, port workers staged a 24-hour strike in August 2010, three weeks after the container landed on the dock. For the next five days, the terminal’s union workers struck for two hours each shift.” […]
“Genoese officials were stuck. No shipping line in its right mind would transport container 307703 knowing only that it was radioactive but not what was inside. Neither Saudi Arabia nor the United Arab Emirates were willing to take it back. As a temporary measure, six months after the container was delivered the port built a three-sided “castle” of triple-stacked yellow containers half-filled with concrete around the unwanted box, which still sat at the terminal’s unused far end. Signs reading pericolo — radiazione ionizzante (“Danger — Ionizing Radiation”) were posted at regular intervals, reminding port workers to keep their distance.
After months of wrangling over who was responsible for the removal operation — priced at $700,000 — the port and the Italian ministry of the interior finally decided to split the bill. On July 18, 2011, just over a year after the box was unloaded in Genoa, 40 firefighters, a police bomb squad, representatives from the port authority, a team of robot operators, and Calimero and Garbarino descended on the Voltri terminal. Five huge green tents were pitched on the port’s blacktop to house computers and gear. Ten fire trucks and emergency vehicles were parked 100 yards behind the shield wall.
Using a remotely controlled excavator specially fitted for demolition work, firefighters drilled a foot-wide hole in the corrugated steel roof. Because there was still an outside chance that the container might hold a bomb, the fire department then tested for chemicals that would indicate explosives. When it didn’t find any, a waist-high tracked robot with three high-resolution cameras was lowered by crane onto the top of the box. Using the robot’s cameras, the bomb squad searched the inside of the container’s door for tripwires or detonators. All they could see were the radiators and copper wire that were officially supposed to be in the box — more than 22 tons of it.
Confident that container 307703 wasn’t going to explode, firefighters let the excavator go to work. “We ripped it open like a tin can,” says Alessandro Segatori, then the Genoese fire department’s second-in-command. That part was easy; finding the radioactive bit was not. A piece of metal weighing less than 6 ounces had to be plucked out of nearly 50,000 pounds of scrap.” […]
“Finally, on July 29, the object was sealed inside several inches of lead and placed into a green and yellow steel tank bolted to the flatbed of a truck. A police car escorted the truck across the docks, through the gates, and onto the highway.
Aside from a few scratches, there are no identifying marks on the cylinder to help investigators figure out what it is or where it came from. The encapsulated chunk of cobalt will make its way north to Leipzig, Germany, where a specialized firm will search it for a serial number and eventually melt it down and recycle it. Judging by its size and shape, the object was probably part of a medical device or a machine used to sterilize food. Disposing of such material is expensive; Italian officials won’t speculate on how it got conveniently lost in a Saudi scrap yard. No one knows how the cobalt got into the container or how the container got into the system.”
“This is a terrible debate and you should all feel bad for having it. Now let me join in.
The research on this topic is split into “completely useless” and “mostly useless”. In the former category we have studies that, with a straight face, purport to show that women like nice guys by asking women to self-report on their preferences. To illuminate just how silly this is, consider the mirror case of asking men “So, do you like witty charming girls with good personalities, or supermodels with big breasts?” When this was actually done, men rated “physical attractiveness” only their 22nd most important criterion for a mate – number one was “sincerity”, and number nineteen was “good manners”. And yet there are no websites where you can spend $9.95 per month to stream videos of well-mannered girls asking men to please pass the salad fork, and there are no spinster apartments full of broken-hearted supermodels who just didn’t have enough sincerity. So self-reports are right out.
Other-reports may be slightly less silly. Herold and Milhausen, 1999, found that 56% of university women believed that women in general were more likely to date jerks than nice guys. But although women may have less emotional investment in the issue than men, their opinions are still just opinions.
The few studies that earn the coveted accolade of “only mostly useless” are those that try to analyze actual behavior. Bogart and Fisher typify a group of studies that show that good predictors of a man’s number of sexual partners include disinhibitedness, high testosterone levels, “hypermasculinity”, “sensation seeking”, antisocial personality, and extraversion. Meston et al typify a separate group of studies on sex and the Big Five traits when she says that “agreeableness was the most consistent predictor of behavior…disagreeable men and women were more likely to have had sexual intercourse and with a greater number of partners than agreeable men and women. Nonvirgins of both sexes were more likely to be calculating, stubborn, and arrogant in their interpersonal behavior than virgins. Neuroticism predicted sexual experience in males only; timid, unassertive men were less sexually experienced than emotionally stable men…the above findings were all statistically significant at p<.01”
These studies certainly show that jerkishness is associated with high number of sexual partners, but they’re not quite a victory for the “nice guys finish last” camp for a couple of reasons. First, men seem to come off almost as bad as women do. Second, there’s no reason to think that any particular “nice” woman will like jerks; many of the findings could be explained by disagreeable men hooking up with disagreeable women, disagreeing with them about things (as they do) and then breaking up and hooking up with other disagreeable women, while the agreeable people form stable pair bonds. Boom – disagreeable people showing more sexual partners than agreeable people.
I find more interesting the literature about intelligence and sexual partners. In high-schoolers, each extra IQ point increases chance of virginity by 2.7% for males and 1.7% by females. 87% of 19-year old US college students have had sex, yet only 65% of MIT graduate students have had sex. There’s conflicting research about whether this reflects lower sex drive in these people or less sexual success; it’s probably a combination of both. See linked article for more information.
The basic summary of the research seems to be that smart, agreeable people complaining that they have less sex than their stupid, disagreeable counterparts are probably right, and that this phenomenon occurs both in men and women but is a little more common in men.
Moving from research to my own observations, I do think there are a lot of really kind, decent, shy, nerdy men who can’t find anyone who will love them because they radiate submissiveness and non-assertiveness, and women don’t find this attractive. Most women do find dominant, high-testosterone people attractive, and dominance and testosterone are risk factors for jerkishness, but not at all the same thing and women can’t be blamed for liking people with these admittedly attractive characteristics.
There are also a lot of really kind, decent, shy, nerdy women who can’t find anyone who will love them because they’re not very pretty. Men can’t be blamed for liking people they find attractive either, but this is also sad.
But although these two situations are both sad, at the risk of being preachy I will say one thing. When a girl is charming and kind but not so conventionally attractive, and men avoid her, and this makes her sad…well, imagine telling her that only ugly people would think that, and since she’s ugly she doesn’t deserve a man, and she probably just wants to use him for his money anyway because of course ugly women can’t genuinely want love in the same way anyone else would (…that would be unfair!) This would be somewhere between bullying and full on emotional abuse, the sort of thing that would earn you a special place in Hell.
Whereas when men make the same complaint, that they are nice and compassionate but not so good at projecting dominance, there is a very large contingent of people, getting quite a lot of respect and validation from the parts of society that should know better, who immediately leap out to do their best to make them feel miserable – to tell that they don’t deserve a relationship, that they’re probably creeps who are only in it for the sex and that if they were a real man they’d stop whining about being “entitled to sex”.
I hate this attitude with the same part of my brain that hates racism and homophobia, because I feel like it has the same root: kicking a low-status person while he’s down in order to show how high-status you are. It is abominable when done to women and abominable when done to men and I hate that this has become the sort of thing where some people feel they have to cheer one on in order to reject the other.”
Here’s some data from the main post that I found interesting:
“About 78% of college students have had at least one ‘one-night stand’, and most such encounters were preceded by alcohol or drug use.3 Indeed, many young people today no longer go on ‘dates’ to get to know a potential partner. Instead, they meet each other at a social event, ‘hook up’, and then go on dates (if the hookup went well).4” [I had no idea]
“According to one study, 60% of undergraduates have been a ‘friend with benefits’ for someone at one time.5”
(I’ve decided not to write any more posts about If Ignorance Is Bliss…, but I’ll probably incorporate a quote or two from the book in posts like this one in the future for some time to come.)
i. “Manners easily and rapidly mature into morals.” Horace Mann
ii. “A conclusion is the place where you got tired of thinking.” Arthur Bloch
iii. “All marriages are happy. It’s living together afterwards that is difficult.” Unknown source.
iv. “Nostalgia isn’t what it used to be.” Peter De Vries
v. “Life is what happens to you, while you’re busy making other plans.” John Lennon
vi. “Children have never been very good at listening to their elders, but they have never failed to imitate them.” James Arthur Baldwin
vi. “Consistency requires you to be as ignorant today as you were a year ago.” Bernard Berenson
vii. “I must be getting absent-minded. Whenever I complain that things aren’t what they used to be, I always forget to include myself.” George Burns
viii. “Silence is not always tact, and it is tact that is golden, not silence.” Samuel Butler
ix. “In judging others, folks will work overtime for no pay.” Charles Edwin Carruthers
x. “To ask advice is in nine cases out of ten to tout for flattery.” John Churton Collins
xi. “People don’t resent having nothing nearly as much as too little.” Ivy Compton-Burnett
xii. “Middle age is when your broad mind and narrow waist begin to change places.” E. Joseph Cossman
xiii. “My idea of an agreeable person is a person who agrees with me.” Benjamin Disraeli
xiv. “An intellectual is a man who takes more words than necessary to tell more than he knows.” Dwight D. Eisenhower
xv. “It’s almost impossible to overestimate the unimportance of most things.” John Logue
xvi. “Man is so intelligent that he feels impelled to invent theories to account for what happens in the world. Unfortunately, he is not quite intelligent enough, in most cases, to find correct explanations. So that, when he acts on his theories, he behaves very often like a lunatic.” Aldous Huxley
I recently stumbled upon The Wordsworth Book of Humorous Quotations, the first 76 pages or so of which you can read at googlebooks here.
Update: Here’s a link to Lesswrong’s latest post with rationality quotes.
From the World Bank indicators. This is not how I’d have liked it to look like, but it’s exceedingly difficult to import data representations from the site to a blog like this, anyway I didn’t figure out how to do it and thought I’d spent too much time on it not to at least post this. Click to view in a much higher resolution:
“Primary completion rate is the percentage of students completing the last year of primary school. It is calculated by taking the total number of students in the last grade of primary school, minus the number of repeaters in that grade, divided by the total number of children of official graduation age.” The data is here.
I just took a look at some specific countries I was curious about for which data were available (there are lots of gaps in the data here, as you can tell from the graph). The world average was 75% in 1991, 78,9 in 2000 and 87,3 in 2009. Which kinda puts Afghanistan’s number of 21 % from 2005 into perspective. Note that the remainder here isn’t the number of females who don’t get a high school diploma (or equivalent); it is females who most likely haven’t really learned how to read. In case you were wondering, I did look at Somalia as another country example – this is one of those countries for which there are no data. Countries like these are not included when calculating the averages so the averages of the measures here are the high bars for these numbers, not the low bars.
The Indicators also have numbers on the gender ratios of variables like these, and that’s probably a better variable if you want to figure out if a particular country having a very low score is just an ‘ordinary’ s*#¤hole country where nobody can afford to go to school; or if it is a maledominated version of same where females just aren’t ever given the chance. Note that in some s*¤$hole countries, it’s probably the case that these numbers don’t look all that bad because the gender discrimination doesn’t take place at this specific level, but instead only kicks in later on (i.e. related to secondary or tertiary education). If you want to take a closer look at these cases there’s data for that stuff too, for example the ‘Ratio of female to male primary enrollment (%)’, ‘Progression to secondary school, female (%)’ and similar variables.