It’s that time of the year again:
Update: Here are a few other videos. If you’re sick of christmas songs, you can have those playing in the background while you’re busy making a christmas cake (or whatever) instead:
Part 4, The Foundation of Rome:
(His youtube channel has a lot more)
Thanks for the feedback.
And just a remark in case you were in doubt (most people probably weren’t, but just in case) – yes, I know very well that it doesn’t make all that much sense to report population estimates on a population of millions of people 40 years into the future down to almost fractions of a person without even including error bars (like the 6.139.618 population estimate for 2050. 618 you say? Not 617?). But the report doesn’t include error bars and I don’t feel comfortable rounding these numbers – so I decided from the start to just report the numbers they give and work with those; there are all sorts of problems related to doing anything else. So anyway, here’s some more stuff from the report:
*According to Statistics Denmark’s latest model estimates, the number of non-Western immigrants in the population will grow with 39% from 2011 to 2050, so that there will be 358.000 non-Western immigrants in Denmark. Today the number is 258.000. The corresponding increase in the number of Western immigrants is estimated at 47%. (p.48)
*The number of descendants of Western immigrants is expected to increase significantly during the period, so that by 2050 the number will be 4,4 times higher than it is today. The number of descendants of non-Western immigrants is likewise expected to increase over time, by a factor of 2,2. Despite these differences in growth rates, the number of non-Western descendants is still expected to turn out to be a little more than 3 times as high as the number of Western descendants by 2050. (p.48) This is because the current number of descendants of non-Western immigrants living in Denmark is much higher (115.597) than the current number of descendants of Western immigrants (18.016) living in Denmark. (p.49)
*The ratio of the Danish population categorized as people ‘of Danish origin’ is expected to decrease over time from 89,9% in 2011 to 84,7% in 2050. (p.48)
*The total Danish population (people of Danish origin, immigrants and descendants combined) is expected to grow by 578.990 people from 2011 to 2050, from 5.560.628 people in 2011 to 6.139.618 people in 2050. The subset of Western immigrants living in Denmark is expected to increase by 79.876 over that time period, from 170.758 to 250 634. The number of descendants of Western immigrants is expected to grow by 61.477, from 18.016 to 79.493. The part of the total Danish population growth from 2011 to 2050 which can be explained by Western immigrants and their descendants is thus equal to 141.353, which is roughly one-fourth of the total estimated population growth (24,4%) (p.49). The subset of non-Western immigrants living in Denmark is expected to increase by 99.413 from 2011 to 2050, from 258.146 to 357.559. The number of descendants of non-Western immigrants is expected to grow by 135.221, from 115 597 to 250 818.
The part of the total Danish population growth from 2011 to 2050 which can be explained by non-Western immigrants and their descendants is thus equal to 234.634, or 40,5% of the total estimated population growth. The part of the population growth over the period explained by people of Danish origin is 203.003, or 35,1% of the total population growth – despite the fact that this group makes up ~85-90% of the population over the entire time period in question. (all numbers from Tabel 1.18, p.49. They didn’t actually report these specific growth component percentages in the report, but it doesn’t take much work to calculate them from the data provided and I thought they’d be interesting to have a look at.)
*When looking at age groups, a few developments are noteworthy. In 2050, people of Danish origin are expected to make out 80,7 % of people at the ages of 40-64, vs. 91,4% today. The employment level of this age group is relatively high, compared to other age groups, which is part of what makes this development interesting – non-Western immigrants in general have much lower levels of employment than do people of Danish origin; more on that stuff below. Another factor perhaps worth noting is that the percentage of immigrants from non-Western countries above 64 years old is expected to increase from 1,2% today to 7,9% in 2050 (the expected growth of Western immigrants in that age group is much smaller – from 2,5% to 3,5%). (p.49)
*The employment rate [beskæftigelsesfrekvens] of males of Danish origin was 75,1% in 2010. The employment rate of females of Danish origin was 73,0% in 2010. The employment rate of male Western immigrants was 62,8% and the employment rate of female Western immigrants was 57,4%. The employment rate of non-Western male immigrants was 53,9% in 2010. The employment rate of non-Western female immigrants was 44,6% in 2010. (p.54)
*The employment rate of non-Western male descendants was 55% in 2010, and the employment rate of female non-Western descendants was 56%. (p.51)
*The employment rate differences between people of Danish origin and non-Western immigrants are particularly pronounced in the age group of 50-59 year olds: Whereas the employment rate of that age group was 79% for females of Danish origin, the corresponding number for non-Western female immigrants was 38%. (p.51)
*The employment rate difference between males of Danish origin and male immigrants of non-Western origin was 21 percentage points in 2010, whereas the employment rate difference between females of Danish origin and female immigrants of non-Western origin was 28 percentage points in 2010.(p.51)
*In 1996 the difference in the employment rates of males of Danish origin and those of male immigrants of non-Western origin was 40 percentage points. The corresponding difference in the employment rates of females of Danish origin and those of female immigrants of non-Western origin was 44 percentage points in 1996. 1996 was two years before the first election where immigration policy became a major factor (though in terms of formation of the government, it did not decide the election – that didn’t happen until 2001).
*The previous 2008-report from Statistics Denmark contained a nice illustration of how the employment rate differences between non-Western immigrants and Danes vary with age and I decided to include it in this post – you can find it at page 65. The numbers are from 2007. Dark-blue = males, light-blue = females, the y-axis is the employment rate difference between people of Danish origin and non-Western immigrants measured in percentage points, the x-axis is age:
So, to take an example, the employment rate of non-Western female immigrants at the age of 40 was approximately 35 percentage points lower than the employment rate of females of Danish origin at the age of 40 in 2007.
*Back to the 2011 report: From 1996 to 2008 the employment rate of non-Western immigrants increased significantly; the male employment rate increased from 40% to 63% and the female employment rate increased from 26% to 50%. Here are two graphs from the report (p.53), click on them to view them in a higher resolution – the first one is on male data, the second is on female data:
“Indv., vestlige lande” = Immigrants from Western countries
“Indv., ikke-vestlige lande” = Immigrants from non-Western countries
“Dansk oprindelse” = Danish origin
“Eftk., vestlige lande” = Descendants, Western countries
“Eftk., ikke-vestlige lande” = Descendants, non-Western countries.
In both cases, the y-axis is the employment rate.
*Country of origin is a very important variable – not all Western countries are the same, nor are all non-Western countries the same. The employment rate of immigrants from the Netherlands is the same as that of people of Danish origin – 74%. The Polish immigrants have an employment rate of 66%, and so do the British. These employment numbers are much higher than those of the immigrants from the US, where the employment rate is just 49%. (p.57) However, ‘many young Western immigrants come to Denmark to study, they’re often only here for a short while and return home after they’ve finished their coursework here’ (paraphrasing some of the relevant remarks on p.76). The authors don’t go into any details about the US immigrants in the report, but I think it’s safe to say that they are more likely to be university students than are immigrants from, say, Poland – the lower employment rates probably shouldn’t be all that surprising. Employment rates on their own don’t care about differences in labor force participation rates.
*Non-Western immigrants generally have lower employment rates, and it’s also among these countries of origin that we find the subpopulations with the lowest employment numbers. The bottom three are Iraq (36% employed), Lebanon (35% employed) and Somalia (31% employed). Less than one in four of female Lebanese immigrants in Denmark are employed. But worth noticing here is also that some of the non-Western countries do quite well: 67% of Ukrainians are employed, and so are 63% of the immigrants from Thailand. (p.57)
A table from the report (p.57), click on it to view it full size:
As I know a lot of terms might cause problems I decided to add an explanation. It was either that, translate everything and make my own table or report some more of the numbers in the text – I decided you should have the data but I didn’t want to spend a lot of time reconstructing that table. You can probably figure out a lot of the stuff I’ve translated below on your own, but in my experience it’s very nice to not have to be the least bit in doubt when reading tables like these. If you have questions, ask:
Title: Employment rates of 16-64 year olds. 2010.
“Antal personer”: Number of people. (antal = number)
“Beskæftigelsesfrekvens”: Employment rate.
“Mænd” = Males.
“Kvinder” = Females.
“I alt” = Total/combined.
“Indvandrere, vestlige lande”: Immigrants, Western countries
Nederlandene = The Netherlands
Storbritannien = Great Britain
Polen = Poland
Rumænien = Romania
Sverige = Sweden
Tyskland = Germany
Litauen = Lithuania
Norge = Norway
Island = Iceland
Italien = Italy
Frankrig = France
“Indvandrere, ikke-vestlige lande” = Immigrants, non-Western countries
Kina = China
Tyrkiet = Turkey
Rusland = Russia
Indien = India
Jugoslavien = Jugoslavia
Marokko = Morocco
Filippinerne = The Philippines
Irak = Iraq
Libanon = Lebanon
The specific 30 countries were chosen because those were the 30 countries of origin with the highest amounts of 16-64 year olds.
The employment rate is somewhat dependent on how long people have lived here, so the authors also decided to split up the data using that variable. Again, click to view it full size:
From page 60. Additional explanation:
Title (roughly): ‘Employment rates of 16-64-year old immigrants – distributed based on the amount of time spent in Denmark. 2010.’
‘Opholdstid’ = Time spent in Denmark.
‘Under 3 år’ = Less than 3 years.
‘3-6 år’ = 3-6 years. [I think you get the picture…]
‘Over 15 år’ = More than 15 years.
*Do note when interpreting the employment numbers of e.g. Filipino women that people who are employed as au-pairs are not counted as employed. (p.59)
*’Even when taking into account differences in the amounts of time spent in the country, there are still big differences. Immigrants from Iraq, Lebanon and Somalia who have been in Denmark for at least a decade have employment rates between 30% and 41%. Immigrants from the Philippines, China and Thailand who’ve been in Denmark for at least a decade have employment rates between 67% and 75%.’ (p.59)
I’ll post at least one more post on this subject. I will probably add the posts together into one single post when I’m done.
The central Danish statistical office, Statistics Denmark, has just published a report with a lot of data on Danish immigrants, Immigrants in Denmark, 2011. I thought some of the non-Danes reading along might appreciate a post in English on this subject.
At the site, they’ve given no indications that they’re planning to translate this, so I don’t think an English version of this material is coming up anytime soon. My translation of the stuff is better than what you’d get from google translate, but do remember that I’m not exactly a professional translator. I’ve decided to page-source every bit of data for this reason, so that it’s easier to go have a look for yourself if you’re in doubt. It was most convenient for me to page-source the pdf version pages, not the official page numbers at the top of each page in the report. Don’t think of the statements below as direct quotations from the report – I’ve frequently had to reformulate the expressions used in the report. If something’s unclear, please ask away. Anyway, let’s start:
*10,1 % of the Danish population are immigrants or descendants of immigrants. (p.13)
*Immigrants make up 7,7% and descendants make up 2,4%. (p.13) [A small note here: The report only explicitly mentions the 10,1% and the 7,7%, not the 2,4% – but I think it’s safe to assume that this is a simple subtraction problem and that it makes good sense to post that number as well just for completeness.]
*60,2% of all immigrants are from non-Western countries. (p.13)
*66% of all immigrants and descendants are from non-Western countries. (p.25)
*The number of non-Western immigrants has almost sextupled since 1980. (p.14)
*From 1980 to 2011, the number of non-Western descendants has increased from 7.653 to 115.597. (p.15)
*The number of descendants of Western immigrants grew by 70% from 1980 to 2011. (p.15)
*The immigrants living in Denmark come from more than 200 countries. (p.15)
*The distribution is not uniform. Immigrants from the top 12 countries (in terms of the number of immigrants living in Denmark) make up 50% of all immigrants. (p.15)
*Turkey is at the top of the list with 32 479 immigrants living in Denmark. (p.15)
*5 out of the top 12 countries are Western countries (Germany, Poland, Norway, Sweden, GB). 7 are Non-western countries (Turkey, Iraq, Bosnia and Herzegovina, Iran, Lebanon, Pakistan, ex-Jugoslavia). (p.16)
*There’s significant variation in the age distribution of immigrants from different countries. When looking at the top twelve, 20% of the Western immigrants in that group are 60 years old or older, whereas only 10% of the non-Western immigrants in the top-twelve are 60 years old or older. (p.16)
*As to the Poles, they’re an interesting case because they’re quite different from the rest of the Western immigrants. They’re the third largest immigrant population (26 580) in Denmark – the number of Polish born people living in Denmark is higher than the number of immigrants from Sweden and Great Britain combined – and more than half of the Poles (53%) are between 20 and 40. 68% of the Polish immigrants are between 20 and 49 years old. 10 % of them are 60 years or older. (p.16)
*When looking at the descendant populations living in Denmark, 11 out of the top 12 countries are non-Western countries. More than one in five (21%) of all descendants living in Denmark are descendants of Turkish immigrants. Lebanon and Pakistan are next on the list, with 9% and 7% respectively. (p.17)
*Most descendants are quite young. 41% of them are below the age of 10, and only 10% have reached the age of 30.
[I used to comment on this fact back when I did political discussions, because it is often overlooked or simply ignored in discussions about what might be termed the demographic potential of descendant populations. We have no idea how many children descendants will end up having, and it makes no sense to try to draw strong conclusions out of sample from the data sets that are available now. Please have this in mind when we get to the forecasts later on. Putting the above numbers in context, the average age of women having their first child in Denmark was 29,1 years in 2010 (Statistikbanken, FOD11). I also urge people to remember here that the growth rate of population segment X in a population doesn’t just depend on the total fertility rate differential, but also on age of birth differentials. If women from population segment X get children at the age of 30 and women from population segment Y get children at the age of 20, population segment Y will grow faster than population segment X, even if every single woman in the two population segments have the same amount of children. This remark is relevant because non-Western immigrants as a rule get children at a lower age than ethnic Danes. Females of Danish origin get on average 0,21 children during the period of their lives where they are 20-24 years old. For all non-Western female immigrants, the corresponding average number is 0,35. For Lebanese women, the number is 0,72. (pp. 27-28)]
*Western descendants are much older than non-Western descendants, on average. [worsening the data problems mentioned above. Especially if you mix up the Westerns and non-Westerns – does it make sense to extrapolate birth rates of Turkish descendants in 2015 from the historical birth rates of descendants of Norwegian women?] One third of the descendants of Western immigrants are above the age of 30, whereas only 6% of the descendants of non-Western immigrants are that old. (p.18)
*Descendants from Turkey, Pakistan, Jugoslavia or Morocco make up 77% of all 30+ year old descendants from non-Western countries. (p.18)
*The total fertility rate of Somali immigrants in Denmark is 3,937. (p.26)
*In the period 2006-2010, there were an average of 64.056 living births pr. year. In the same period, there were an average of 5.860 (9,1%) children born every year of non-Western immigrants and an average of 2.310 (3,6%) children every year born of Western immigrants. The average annual number of children of descendants over the time period was just 961. (p.26)
*The report has some stats on family patterns and the degree of observed endogamy. When it comes to male immigrants from Western countries who are classified as being in a relationship, in 59% of the cases the partner is of Danish origin and in 37% of the cases the partner is an immigrant from a Western country. When it comes to the female immigrants from a Western country, 63% of the partners are of Danish origin and in one-third of the cases it’s a Western immigrant. The pattern is different when it comes to immigrants from non-Western countries. For male immigrants from non-Western countries, 13% have partners of Danish origin and 80% have partners from a non-Western country. For female immigrants from non-Western countries, 28% have partners of Danish origin and 68% have partners of non-Western origin. Interestingly, when it comes to descendants Western immigrants are more likely to have a partner of Danish origin than are first generation immigrants (83% and 85% for males and females respectively), whereas this pattern is actually reversed for females from non-Western countries, where descendants are less likely to have a Danish partner than are first generation immigrants (19% of females who are descendants of immigrants from non-Western countries with a partner have a partner of Danish origin, whereas the corresponding number for the first generation non-Western female immigrants is 28%.) 3 out of 5 non-Western descendants who are in a relationship are in a relationship with a non-Western immigrant and 18% of them have a partner who’s also a descendant of immigrants from a non-Western country. (all numbers above from Tabel 1.9, p.32)
*When it comes to the non-Western females who find Danish male partners, few of these women come from the major immigrant countries. Of the 19.981 female non-Western immigrants with a partner of Danish origin, females from Thailand, Philippines, Russia, China, Brazil and Ukraine make up 11.644 of them – 58%. (p.33)
*Females from Thailand and Philippines alone make up 39% of the non-Western females who have partners of Danish origin. (p.34)
*When it comes to females from Turkey, Pakistan and Iraq, only 2% of them have a partner of Danish origin. (p.34)
*97% of female Turkish immigrants with a partner have a partner of Turkish origin. 94% of Pakistani females in a relationship have a partner of Pakistani origin. (p.35)
*88% of Turkish descendants in a relationship have a partner of Turkish origin. (p.37)
*Today the country from which Denmark receives the largest number of immigrants is Poland. Denmark received 3850 Polish immigrants in 2010. (p.38)
*(not direct citation but paraphrasing…)’Immigrants from Western countries like USA, Spain and Italy rarely come to Denmark to live here permanently and a large share of them leave Denmark again.’ – ‘This is not the case for non-Western immigrants.’ (p.40) Some data: 77% of the Poles who came to Denmark in 2002 had left the country by January 1st, 2011. 88% of the immigrants from the US who came in 2002 had left Denmark by 2011. On the other hand, only 9 percent of Iraqis who came in 2002 had left by 2011. 24% of the Turks who arrived in 2002 had left by 2011. (all numbers from table, p.39) [the 9% number is interesting also because during that time period, Denmark actually had various policies (Danish links) in place where Iraqis who decided to leave Denmark could get a one-time cash prize for doing so.]
This post dealt with roughly the first 40 pages of the report. The report has 153 pages. So there’s a lot of stuff to cover – there’s also data on education, crime, employment, ect. I might write another post or two on this subject if people liked this one.
Major related hint: If you’d like me to write another post on this, tell me, either by using the rating system or by commenting. If I don’t get positive feedback, I probably won’t do any more work on this – it adds a not insignificant time component to not being able to just quote directly from the report because the stuff needs to be translated as well.
Here’s the link. If you have any interest in this subject, you should probably read all of it.
“We conducted a systematic review of literature on the CE of diabetes interventions recommended by the American Diabetes Association (ADA) and published between January 1985 and May 2008. We categorized the strength of evidence about the CE of an intervention as strong, supportive, or uncertain. CEs were classified as cost saving (more health benefit at a lower cost), very cost-effective (≤$25,000 per life year gained [LYG] or quality-adjusted life year [QALY]), cost-effective ($25,001 to $50,000 per LYG or QALY), marginally cost-effective ($50,001 to $100,000 per LYG or QALY), or not costeffective (>$100,000 per LYG or QALY). The CE classification of an intervention was reported separately by country setting (U.S. or other developed countries) if CE varied by where the intervention was implemented. Costs were measured in 2007 U.S. dollars.
RESULTS— Fifty-six studies from 20 countries met the inclusion criteria. A large majority of the ADA recommended interventions are cost-effective. We found strong evidence to classify the following interventions as cost saving or very cost-effective: (I) Cost saving — 1) ACE inhibitor (ACEI) therapy for intensive hypertension control compared with standard hypertension control; 2) ACEI or angiotensin receptor blocker (ARB) therapy to prevent end-stage renal disease (ESRD) compared with no ACEI or ARB treatment; 3) early irbesartan therapy (at the microalbuminuria stage) to prevent ESRD compared with later treatment (at the macroalbuminuria stage); 4) comprehensive foot care to prevent ulcers compared with usual care; 5) multi-component interventions for diabetic risk factor control and early detection of complications compared with conventional insulin therapy for persons with type 1 diabetes; and 6) multi-component interventions for diabetic risk factor control and early detection of complications compared with standard glycemic control for persons with type 2 diabetes. (II) Very cost-effective — 1) intensive lifestyle interventions to prevent type 2 diabetes among persons with impaired glucose tolerance compared with standard lifestyle recommendations; 2) universal opportunistic screening for undiagnosed type 2 diabetes in African Americans between 45 and 54 years old; 3) intensive glycemic control as implemented in the UK Prospective Diabetes Study in persons with newly diagnosed type 2 diabetes compared with conventional glycemic control; 4) statin therapy for secondary prevention of cardiovascular disease compared with no statin therapy; 5) counseling and treatment for smoking cessation compared with no counseling and treatment; 6) annual screening for diabetic retinopathy and ensuing treatment in persons with type 1 diabetes compared with no screening; 7) annual screening for diabetic retinopathy and ensuing treatment in persons with type 2 diabetes compared with no screening; and 8 ) immediate vitrectomy to treat diabetic retinopathy compared with deferred vitrectomy.
CONCLUSIONS — Many interventions intended to prevent/control diabetes are cost saving or very cost-effective and supported by strong evidence. Policy makers should consider giving these interventions a higher priority.”
In health cost-effectiveness analyses, it’s quite common to find measures/interventions that are cost-effective but do not actually save ‘you’ money, because the effectiveness variable is some sort of (/weighted) effect/$ measure. There’s also always the problem with figuring out what’s the relevant alternative course of (in-?)action. But what I found very, very interesting here is that one of these interventions was actually cost-saving when compared to doing nothing:
This is very interesting. Of course it’s also noteworthy that quite a few other treatment options would actually be cost saving if implemented on a larger scale than is currently the case. I should probably also comment on some of the stuff that’s not worth the money:
“The four interventions with strong evidence of not being cost-effective were 1) one-time universal opportunistic screening for undiagnosed type 2 diabetes among those aged 45 years and older compared with no screening; 2) universal
screening for type 2 diabetes compared with targeted screening; 3) intensive glycemic control in the U.S. setting for patients diagnosed with diabetes at older ages (55–94 years of age) compared with usual care; and 4) annual screening for retinopathy compared with screening every two years. All these studies were for type 2 diabetes.”
Some sort of universal opportunistic screening program is one of those things that might sound like a good idea, but probably isn’t. It’s just too damn expensive. Btw., when applying age-targeting approaches it’s not at all clear where to place the cut-off point:
“Current evidence is uncertain on how the CE of screening for undiagnosed type 2 diabetes would change with the age of
those screened. Two studies evaluated the CE of screening for undiagnosed type 2 diabetes; one study reported that costeffectiveness ratios (CERs) increased with initial screening age (16) while the other reported that they decreased with screening age (35).”
From one of the amazon reviews: “If you compare this book to its obvious competitors (e.g. Valerie Hansen’s Open Empire, Schirokauer’s Brief History of Chinese Civilization), you have to be amazed at the relatively low list price–especially considering that the publisher, Cambridge University Press, is not famous for selling cheap books. If you can buy only one textbook history of China, this one is worth considering for that reason alone.”
Cambridge University Press is also not famous for selling crappy books, and combine that observation with the remarks above and you have a big part of the reason why I bought it. Judging from what I’ve read so far it’s a good book with a reasonable amount of details, all things considered (there’s a lot of ground to cover here…). Some stuff from the book:
i. “The cart with a pole and two horses harnessed with a neck-yoke gave way at the time of the Warring States to the cart with two shafts. And it seems that at the same time the neck-yoke – which was to remain for a very long time the only method of harnessing known in the rest of the world – was replaced by the breast harness. This new device, and also the horse-collar, which was to appear between the fifth and ninth centuries A.D., were important pieces of progress in the field of animal traction. By freeing the horses from the pressure of the yoke, which tended to choke them, they made driving easier and rendered it possible to pull heavier loads. One single horse would suffice where formerly two or sometimes even four were required. It is noteworthy that the casting of iron and more rational methods of harnessing, attested in the Chinese world at the time of the Warring States, both appear in Europe at the end of the Middle Ages.”
ii. “Although the Han founder considerably softened the extreme harshness of the penal laws of the first empire, the political and administrative organization that Liu Pang put in place differed little from that of the Ch’in. We find the same division of the territory into commanderies (chün) and prefectures (hsien), and the same tripartite division of functions both in the capital and in the provinces: civil affairs, military affairs, and inspection and supervision of the administration. In short the same ‘Legalist’ empire was perpetuated not only in the territories directly dependent on the central power, but also in the ‘fiefs’ (feng-kuo) granted first to the founder’s companions-in-arms and later to relatives of the imperial family. Its power was based on the direct control of the peoples and individuals by the state. This implies recourse to accurate censuses, and in fact those which have been preserved from the Han period are reckoned to be among the most precise in history. Every subject was liable to a personal tax payable in coin (this tax was levied even on children of tender years), to annual stints of forced labour and to military service. In addition, the Legalist system of rewards and punishments […] made it possible to classify the whole population in the continuous hierachy of the twenty-four degrees of dignity (chüeh). […] The use of the passport, the antecendents of which go back to the age of the Warring States, is well attested in the Han period [206 BCE – 220 CE], as is the use of police dogs.”
iii. “the hold of the central power was firmest where the settlement was most recent; in the long-settled regions the imperial administration had to come to terms with the great families. […] This sheds light on one of the main reasons for transfers of population: it was in the state’s interest to move influential families, to shift them from their surroundings, in order to rob them of all power. Similarly, it was also in the state’s interest to extend the areas of land clearance and colonization, for it is easier to keep in hand a population consisting of displaced persons – convicts, freedmen, soldiers, and bankrupt peasants. […] a big effort was made to colonize the north-western regions, and the number of people settled there in the reign of the emperor Wu Ti [141-87] may be estimated at two million. A few figures will suffice to bring home the scale of these transfers of population. In 127, 100,000 peasants were settled in Shuo-fang […] in 102, 180,000 soldier-farmers went off to people the Chiu-ch’üan and Chang-yeh commanderies; and in 120,after big floods in western Shantung, 700,000 victims of the disaster were transferred to Shensi. These transfers of population were numerous enough to affect the distribution of the population in North China…”
iv. “Like the Ch’in, the first Han rulers pursued a policy of undertaking big public works, the majority of which were strategic or economic in character. In 192 and 190 B.C. peasants and their womenfolk from the valley of the Wei were conscripted for the construction of the walls of the new capital, Ch’ang-an. In each of these two years there were nearly 150,000 people at work. […] In 132 B.C. 100,000 soldiers were drafted to repair a breach in the dykes of the Yellow Rver. […] Besides ramparts and forts, canals and roads were also built. These reinforced the hold of the central power on the regions but also corresponded to economic needs. In 129 B.C. ninety miles of canal were dug between Honan and Shensi to connect the basin of the Wei with the Yellow River; 95 B.C. saw the opening of a canal some sixty miles long linking the course of the Wei to that of the Chiang further north. But innumerable irrigation works were carried out in the whole of North China during the reigns of Wu Ti and his immediate successors.”
v. “It would be simplistic to see in the Great Walls a sharp divide between the world of the nomadic cattle-raisers and that of the Chinese farmers and townspeople. The northern frontiers of the Chinese world formed a zone where the opposing modes of life of the farmer and the herdsman mingled and combined. Down the centuries sometimes the pasturages would advance and the cultivated land shrink, sometimes the arid lands would be conquered and developed by the sedentary peoples. Just as certain tribes of herdsmen changed over to agriculture, so some Han adopted the nomads’ mode of life. [… an example:] A defeat incurred by the Chinese armies in 201-200 [B.C.] caused a general retreat south of the Great Walls which lasted until about 135 [B.C.]. […] The organization of the Han armies and defence system on the northern frontier is fairly well known to us thanks to the discovery of a substantial number of manuscript texts on wood and bamboo and to the excavations carried out on the Chinese limes in the Han period since the beginning of the century. […] About 10,000 in number, they consist of reports, communiqués, inventories, soldiers’ letters, fragments of legal texts, and so on. […] The dates mentioned in them run from about 100 B.C. to A.D. 100. […]
Look-out duty, patrols, and training occupied a considerable part of the time of the troops serving in the first line of defence. Each post was in permanent contact with neighbouring posts and with the rear, thanks to a system of signals: red and blue flags, smoke by day and fires by night, rendered more easily visible by long pivoting poles rather like Egyptian shadoofs. This system of signals, which made possible, thanks to a fairly complex code, the swift transmission of relatively precise information about troop movements and attacks, is mentioned in the texts as early as 166 B.C. All messages sent and received were recorded in writing. The head of each post was obliged by a very formalistic administrative routine to write a large number of letters and to keep extensive records which deal not only with military activities but also with victualling and the weapons kept in magazine – bows, arrows, crossbows, and catapults.”
vi. “one of the most frequent practices in the Han age was that of sending hostages (chih) to the imperial court. As a token of their loyalty, princes of central Asian kingdoms and leaders of tribal confederations would offer their own sons, who were lavishly entertained in the capital at the emperor’s expense, received a Chinese education and were often appointed to posts in the imperial guards or in the domestic administration of the palace. Having been converted to the mode of life and culture of the Chinese, when they returned to their own countries they acted as agents of Han influence. Besides forming a guarantee against the breaking of alliances, the hostage system also provided a means of interfering more easily in the dynastic affairs of the countries allied with China.”
vii. “The progress in iron metallurgy continued under the Han. One has to wait until the sixth century A.D. to find a description of an open hearth process, the ancestor of the Modern Siemens-Martin process, but the Chinese could produce steel as early as the second century A.D. by heating and working together irons with different carbon contents. […] The reign of Wang Mang (9-23) saw the appearance of the water mill. […] We have written evidence of wheelbarrow in Szechwan in the third century A.D., but figurative representations of it go back to the first and second centuries. […]
“When the state monopoly in iron and salt was instituted in 117 B.C., forty-eight foundries were established by the government, each of which employed a labour force of some hundreds to a thousand workers. […] Outside the two big sectors of salt and iron, where in any case the state monopoly was strictly enforced for less than a century, private and public enterprises existed side by side. The same is true of silk weaving. […] One of the social peculiarities of the Han period as a whole was in fact the existence of very rich families who combined agricultural enterprises […] with industrial undertakings (cloth mills, foundries, lacquer factories) and commercial businesses, and who had at their disposal a very large labour force. […] The Cho family, one of the richest in Ch’eng-tu, owned huge expanses of cultivated land, fish-ponds, and game parks. It possessed ironworks and steelworks in which it employed 800 slave workers and grew rich through the iron trade…”
1. It’s been a very long time since the last time I had a blogging pause for more than a week – I hate that this had to happen so soon after Razib’s links, because that’s just the wrong impression to give to these potential new readers. Look at the monthly archieves – I’ve posted more than 200 posts this year so far. This is an active blog, dammit, with frequent updates!
But I’ve been very busy. Real life stuff.
2. Let’s say you’re a nudist. Say you’re invited to a party at a friend’s house. Most of your friends are ‘normal people’. Most normal people will probably prefer not to invite you if you insist on showing up naked at the party, and quite a few of them will probably make such an invitation conditional on you wearing clothes at the party.
Next, say you think the earth is a 6000 years old creation of an invisible sky fairy and that the person inviting you will Burn In Hell because he hasn’t ‘seen the light’. Say that in order to save his children you like to try to convince them, when you meet, that if they do not ‘sign up’ and go to an official Indoctrination Center every week, they (and their parents) will suffer unspeakable horrors for all eternity.
Now ask yourself what are the ‘standard’, as in ‘considered normal’, magnitudes of response to these two types of behaviours/behavioural patterns. If the religious nutter and the nudist both live in the same neighbourhood, is one of them more likely to be considered the ‘black sheep’ by the rest of the community than the other?
3. I’ve been following the live commentary of the London Games here. Here’s the main site. Comp. analysis is usually available at Polgar’s blog. ‘I’ve been busy’ = this is pretty much the only outlet I’ve allowed myself over the last days, aside perhaps from the piano. The commentators – Trent, King, ‘who was that third guy?’ – are doing a wonderful job and usually the guy who has a rest day joins the party and gives his views about a few of the games being played; so that’s live analysis by the world elite provided for free online. There’s also an extensive library available of the previous day’s coverage, so that you can see the game commentary later on if you don’t have the option of watching it live. (Little voice screaming in a very high-pitched voice inside my head: “Nerd, geek!”).
4. Some wikipedia articles of interest (from my bookmarks, haven’t spent much time at wikipedia of late): Hayflick limit. Paracetamol (“Paracetamol toxicity is the foremost cause of acute liver failure in the Western world, and accounts for most drug overdoses in the United States, the United Kingdom, Australia and New Zealand.”). [Related: After reading this, I sent a link to this study to my big brother – it’s a new result so it’s still uncertain if there’s ‘anything to it’, but I didn’t think I should keep it to myself given their situation (my brother’s GF is pregnant). My brother knows how to read a study too.] Red imported fire ant. Here’s a related link to Ed Yong’s post on the subject – don’t miss the awesome rafting video in that post! And here’s an article about the Kargil War (which very few people living in Europe has probably ever heard about).
Do Pressures to Publish Increase Scientists’ Bias? An Empirical Support from US States Data, by Daniele Fanelli (link). Abstract:
“The growing competition and “publish or perish” culture in academia might conflict with the objectivity and integrity of research, because it forces scientists to produce “publishable” results at all costs. Papers are less likely to be published and to be cited if they report “negative” results (results that fail to support the tested hypothesis). Therefore, if publication pressures increase scientific bias, the frequency of “positive” results in the literature should be higher in the more competitive and “productive” academic environments. This study verified this hypothesis by measuring the frequency of positive results in a large random sample of papers with a corresponding author based in the US. Across all disciplines, papers were more likely to support a tested hypothesis if their corresponding authors were working in states that, according to NSF data, produced more academic papers per capita. The size of this effect increased when controlling for state’s per capita R&D expenditure and for study characteristics that previous research showed to correlate with the frequency of positive results, including discipline and methodology. Although the confounding effect of institutions’ prestige could not be excluded (researchers in the more productive universities could be the most clever and successful in their experiments), these results support the hypothesis that competitive academic environments increase not only scientists’ productivity but also their bias. The same phenomenon might be observed in other countries where academic competition and pressures to publish are high.”
An important bit on ‘”negative” results’ from the paper:
“Words like “positive”, “significant”, “negative” or “null” are common scientific jargon, but are obviously misleading, because all results are equally relevant to science, as long as they have been produced by sound logic and methods [11,12]. Yet, literature surveys and meta-analyses have extensively documented an excess of positive and/or statistically significant results in fields and subfields of, for example, biomedicine , biology , ecology and evolution , psychology , economics , sociology .
Many factors contribute to this publication bias against negative results, which is rooted in the psychology and sociology of science. Like all human beings, scientists are confirmationbiased (i.e. tend to select information that supports their hypotheses about the world) [19,20,21], and they are far from indifferent to the outcome of their own research: positive results make them happy and negative ones disappointed . This bias is likely to be reinforced by a positive feedback from the scientific community. Since papers reporting positive results attract more interest and are cited more often, journal editors and peer reviewers might tend to favour them, which will further increase the desirability of a positive outcome to researchers, particularly if their careers are evaluated by counting the number of papers listed in their CVs and the impact factor of the journals they are published in.
Confronted with a “negative” result, therefore, a scientist might be tempted to either not spend time publishing it (what is often called the “file-drawer effect”, because negative papers are imagined to lie in scientists’ drawers) or to turn it somehow into a positive result. This can be done by re-formulating the hypothesis (sometimes referred to as HARKing: Hypothesizing After the Results are Known ), by selecting the results to be published , by tweaking data or analyses to “improve” the outcome, or by willingly and consciously falsifying them . Data fabrication and falsification are probably rare, but other questionable research practices might be relatively common .”
Yesterday I came across this website. Unlike 99.9 % of the stuff I post here, I’m actually not 100 percent sure if the link is NSFW – it probably depends on where you work but if you want to be sure don’t click the link. Not science, not a place to learn stuff – so if that’s what you’re here for; come back later, there’ll be plenty of that stuff later. I was arguing a long time with myself about whether I should link to this or not.
Some of them reminded me of the letters in Eric Ericson’s Brev till Utlandet which I’ve previously blogged here, though I’m not sure Ericson would like that comparison (the blogger is on a whole different level of hyperbole, rudeness, obnoxiousness ect.).
I thought the best of them were really, really funny and I decided to post a couple of examples:
“From Alex Mcgob to ***********@***********.org
Hey! I am interested in renting your place, it sounds awesome! I can pay straight cash every month. Just don’t ask where it comes from.
A little bit about myself, I am 22, and love having fun! I saw you are avid movie watchers, which is great because I have a large collection of [*]. I don’t really like cleaning, so I will expect people to clean after me. I have 5 german shepherds, but don’t worry, they are cool. I have a habit of eating any food I find, but I’ll try to restock the fridge with tap water at least once a week. I love playing the bagpipes, and I usually play them every night for a few hours.
Now I just wanted to let you know, I am a bit of an alcoholic. I drink every night until I black out and am often loud and obnoxious. I don’t have a car because I am currently sorting out my 3rd DUI, so is it cool if I borrow a car if I need to run to the liquor store or something? I’ll make sure I put some gas in it.
Some people have complained that I don’t shower, but my minor odor is nothing compared to the amount of money you will be saving on water.
I look forward to hearing from you!
[* word erased to avoid getting my blog caught in word filters used to block sites in workplace environments – it starts with a p, the next letter is an o…]
“This was in response to an ad for a guy looking for a parking pass to the Eagles/Giants game last season at Giant’s Stadium. I don’t think he actually looked at the parking pass I sent him. If he did try to use it, he’s a retard.
Timmy Tucker to ****************@***********.org
Hi there! I have season parking passes to the game and would be willing to give up my parking pass for this one because I am taking a cab to the game. I will sell it for $25.
I scanned a picture of it here if you are interested:
Please let me know!
Go Eagles! Fuck the Cowboys!
MATTHEW *************** to Me
Hey that sounds great! Do you think that maybe you could get me one for my friend too? He is going to the Carolina Arizona game and if you could get one for him, I would gladly give you 60 for the pair.”