https://shepherd.com/best-books/how-human-language-works

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[This post was originally published in April 2013.]

The recently published World Economic Forum report on global travel and tourism competitiveness contains a wealth of data that is significant beyond just tourism. Several data sets pertain to health infrastructure in the 140 countries considered by the WEF. Under the “Health and Hygiene” rubric one finds figures pertaining to physician density, number of hospital beds per capita, access to improved sanitation, and access to improved drinking water. This post will focus on the first two issues, as the latter two sets of figures concern hygiene, rather than health infrastructure or personnel. These figures from the WEF report will be supplemented by data on nurse/midwife density from the World Health Organization, remapped with the same color-coding. The three sets of figures are mapped; several instructive patterns emerge involving both individual maps and map comparisons.

The first map illustrates the global patterns in physician density, that is the number of physicians per 1,000 people. The highest numbers of doctors per capita are found in Russia and some of the former Soviet states, as well as elsewhere in Europe. Greece, perhaps surprisingly, has the highest figure, 6.2 physicians per 1,000 inhabitants. Austria and Georgia have slightly fewer than 5, and the only other countries with 4 or more are Russia, Norway, Kazakhstan, Switzerland, and Spain. Portugal and Azerbaijan round up the top ten list. Several Western European countries rank much lower, most notably Finland and the Netherlands (2.9 physicians per 1,000 in each), and the UK (2.7 physicians). In the New World, Argentina, Uruguay, and Australia outrank United States, Canada, and New Zealand. In fact, the U.S. has fewer doctors per capita than Malta, Mongolia, or Moldova. Mexico has the same number of physicians per capita as does Canada (2.0), while other countries in Central and South America lag far behind. Figures for Asian countries range from 2.8 physicians per 1,000 in Mongolia to 0.2 in Nepal. Africa is doing even worse, containing all the bottom twenty countries on the list. Almost all of sub-Saharan Africa finds itself in the lowest category, with South Africa registering a physician density of only 0.8.

Despite common preconceived notions, physician density does not correlate well with national wealth measured in terms of GDP. Some of the world’s richest countries—including the U.S., Canada, the UK, and Finland—have fewer physicians per capita than poorer countries such as Ukraine, Kazakhstan, and Moldova. The higher figures in the former USSR are likely a legacy of Soviet times, when doctors were numerous even if not always well-qualified or well-paid. Many of those physicians were and still are female. Moreover, the relative ease of becoming a physician may have something to do with these figures as well. Nor does GDP correlate with physician density if one considers each world region separately. For example, in Latin America, Mexico, Argentina, and Chile are in the same general GDP category, but Argentina has 3.2 physicians per 1,000 population, Mexico has 2.0, and Chile merely 1.0. In Asia, poorer Mongolia is well ahead of richer Japan and South Korea (2.8, 2.5, and 2.0, respectively). As we shall see below, physician density does not correlate with nurse/midwife density or the number of hospital beds per capita either. But first let’s consider those figures individually.

When it comes to the number of nurses and midwives per capita (including professional nurses and midwives, auxiliary nurses and midwives, enrolled nurses and midwives, and related occupations, such as dental nurses and primary care nurses), the global picture is rather different from that of physician density. The highest-ranking areas include Canada, Northern Europe, and several countries in Western Europe, such as Germany, the UK, Ireland, and Switzerland. Former Soviet states, with the exception of Belarus, place in the lower categories. Whereas in terms of physician density Europe appears rather homogeneous, with only a couple of former Yugoslav republics having fewer than 2.0 physicians per capita, when it comes to nurse/midwife density, Western Europe is very heterogeneous. A sharp contrast exists between Switzerland, Ireland, Germany, and the UK, which have some of the highest nurse densities in the world, and France, Italy, Belgium, and the Netherlands, which find themselves in the lowest category, below Colombia, Democratic Republic of Congo, and Papua New Guinea. I am lost for explanation here. Obviously, national wealth or cultural factors could not have produced the sharp contrast between Germany and the Netherlands, or between Argentina and Uruguay. However, in some cases cultural and economic factors may play a role; for example, the Philippines have more nursing personnel (6.0 nurses/midwives per 1,000 population) than do the much richer countries of South Korea and Japan (5.3 and 4.1, respectively). But the Philippines are also known worldwide for “exporting” well-educated and well-qualified nursing personnel; nursing is the most important occupational niche for Philippine female émigrés.

The map of hospital bed density (i.e. the number of hospital beds per 10,000 population) reveals yet another pattern.* The hot zone, with over 60 beds per 10,000 people, covers virtually all post-Soviet space and most of Central and Western Europe, although exceptions—such as low ranking Spain, Portugal, Italy, the UK, Norway, Denmark, and especially Sweden—stand out. The U.S., Canada, and Australia find themselves in a mid-level category, with 30, 32, and 38 beds per 10,000, respectively. With the exception of Argentina, Latin America places low, as do African countries, except Ethiopia, which has the world’s 20th highest figure in this respect, with 63 beds. Asian countries differ considerably in this respect as well, with Japan and Korea occupying the top two spots (137 and 103 beds, respectively), but with the Philippines supporting only five beds per 10,000 and Bangladesh a mere three. Again, while the explanation for some of these figures can be reduced to national wealth, others do not follow from GDP figures; Ethiopia is a particularly aberrant example. Economic factors do seem to play a significant role in defining patterns of hospital stays. For example, according to the figures published recently by the International Federation of Health Plans, a global network of private health-insurance plans with 100 members in 31 countries, the average cost of an appendectomy in the U.S. is nearly $14,000, almost three times the price an Australian or New Zealander would pay for the same operation, four times what a British or South African patient would pay, six times the price in Spain, and fourteen times what it would cost in Argentina. These high costs of health care in the U.S. have been negatively correlated with the average length of hospital stays. However, cultural factors may be significant as well. Compare, for example, the United States and Russia. In the U.S., which ranks 64th with 30 hospital beds per 10,000 population, patients are expected to stay in the hospital as little as possible, sometimes leaving the day after a heart procedure, a major surgery, or a childbirth. Indeed, according to the OECD figures, the average length of stay in U.S. hospitals for all causes in 2009 was 4.9 days, well below OECD average of 7.2 days.** In contrast, in Russia, which ranks 3rd with more than three times more hospital beds per capita than the U.S., patients stay in hospitals much longer on average: 13.6 days. One reason for the discrepancy, or at least one correlate, is that in Russia patients and doctors have very different expectations about how care is to be administered and who is to make the decisions about it. Hospital stays are longer because doctors expect to have more control over patient care, deciding not only what treatments or medications are to be used, but sometimes even withholding the diagnosis from the patient. In the U.S., hospital care is much more under the patient’s own control, sometimes exasperatingly so, as doctors expect patients or next of kin to make difficult decisions without the benefit of specialized education and professional experiences.

As mentioned above, there is no clear correlation between these three measures of health infrastructure. For example, the juxtaposition of the two maps on the left shows that some countries with high physician density have much lower figures for nursing personnel and vice versa. While Russia and Kazakhstan have some of the world’s highest physician densities (in 4th and 6th place, respectively), they are doing much worse in regard to nurse/midwife density. Argentina has more than six times more doctors than nurses per capita (3.2 and 0.5 per 1,000). Conversely, New Zealand and Canada rank relatively low with respect to physician density (40th and 58th place, respectively) but have much higher figures for nurse/midwife density.

The patterns of physician density and hospital bed density diverge greatly as well. The most striking example concerns Japan and Korea, which, as mentioned above, rank 1st and 2nd in the number of hospital beds per capita, but only 53rd and 57th in physician density. Discrepancies in the other direction can be illustrated by Sweden, which places 11th in the number of physicians per capita but only 66th in terms of hospital beds.

Finally, figures for nurse/midwife density and the number of hospital beds per capita are rather divergent as well. Russia and other post-Soviet countries have very high numbers of hospital beds, but few nurses to care for patients in those hospitals. This discrepancy is fully confirmed by my acquaintances who have had the misfortune to be treated in these hospitals; they agree that patient-per-nurse ratios are still very high and that nursing care leaves room for improvement. The crisis with nursing care in countries such as France, Italy, or Greece, all of which have high numbers of hospital beds but very few nurses, looms large. The situation is much different not only in the U.S., Canada, and Australia, but also in Brazil and Uruguay, which all have much lower patient-per-nurse ratios.

Finally, while the intricacies of the health care reform debate in the United States go far beyond the scope of this post, it is worth mentioning that while the opponents of the National Health Care Act argue that introducing a single-payer health care system would lead to a drastic reduction of available health infrastructure and personnel per capita, an examination of figures for countries that have implemented such systems, such as Canada and the UK, and the corresponding figures for the U.S. does not reveal a sharp contrast. For example, the U.S. registered 2.4 doctors per 1,000 inhabitants in 2009, while the corresponding figures for Canada and the UK are 2.0 and 2.7, respectively. Availability of nurses and midwives per capita is actually slightly higher in both Canada and Britain, 10.4 and 10.1, respectively, compared to 9.8 in the U.S. Likewise, the availability of hospital beds per capita is also slightly higher in Canada and the UK (32 and 33 beds per 10,000 population, respectively) than in United States (30 beds per 10,000 population). Conversely, the average length of hospital stay is much lower in the U.S., with only 4.9 days compared to 7.7 days in both the UK and Canada. An American patient with acute myocardial infarction would expect to stay in hospital only 5.3 days, a day less than a Canadian counterpart and nearly three days less than a British patient with the same diagnosis. While the type of health care system undoubtedly plays a role in determining the quantity and quality of care provided, other factors including cultural ones are also crucial.

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*One thing to note is that it is not clear whether these figures include mental hospitals, as the resulting patterns can be quite distinct.

**On the whole, the availability of hospital beds per capita correlates with the average length of hospital stay: the average length of stay in the top ten countries by the number of beds per capita (for which data on hospital stays is available) is 9.5 days, whereas the corresponding figure for the ten countries with the least bed availability (again, for which data on hospital stays is available) is 5.7 days.

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[This is a guest post, written by Roger Fernàndez from Barcelona, Spain]

Can a few simple accents become the center of a controversy that occupy headlines? In Catalonia, yes. Catalan is the language of this northeast Spain region, whose capital is Barcelona. The Catalan language, however, is not only spoken in Catalonia; other Spanish regions such as the Balearic Islands, Valencia and some Aragon areas as well as areas of southern France, and the Italian city of Alghero, make this Romance language the 20th most spoken language in Europe (9,4M speakers ).

On 29 September an intention was announced to eliminate the vast majority of diacritical accents. The proposal was made by the IEC, the Institute of Catalan Studies, which is the organization that, since 1911, defines the rules of grammar, spelling and new vocabulary of the Catalan language. And, as if someone had thrown a match into a powder keg, a discussion has exploded and unleashed far beyond the purely academic circles.

But what diacritical accents mean in Catalan and what role do they have? The diacritical accents are marks that are introduced in some words to help distinguish words with different meanings; they do not follow the rules of accentuation,. A few examples illustrate this:

Ma (my) / Mà (hand)

Dona (Woman) / Dóna (gives)

Pel (for the) / Pèl (hair)

Net (clean) / Nét (grandson)

Deu (Ten) /  Déu (God)

And so up to 150 pairs of words were defined by Pompeu Fabra, the philologist who created the prescriptive rules of modern Catalan orthography in the early twentieth century. The new IEC proposal reduces the number of such pairs to just 14!

Initially, the news appeared in the Catalan newspapers, but it was only a small article in the Culture section of each newspaper. But after a few hours, thanks to social networks, the debate was on like an uncontrollable fire. Soon the “Diacriticals affair” was the cover story in the media all around the country.

That day, Empar Moline, one of the most prestigious writers in Catalan, published an article in the newspaper “Ara” denouncing, in his usual humorous style, that the disappearance of diacritic marks would become an oversimplification of a language which, by constant contact with the powerful Spanish language, is already suffering a loss of rigor. Why not, Moline asked ironically, remove Catalan personal pronouns (“pronoms febles” or weak pronouns), the real nemesis for any student of Catalan.

Within a few hours, Quim Monzo, a close friend of Empar Moline and probably the most recognized living writer in Catalan, responded in Tweeter standing at the other side of the controversy:

“Please, we need an immediate crowdfunding campaign to save the diacritics” wrote the eternal candidate for the Literature Nobel Prize, Quim Monzó.

The discussion, however, was not limited only to a philological and literary milieu, and Twitter was starting to warm up. That evening #diacritics hashtag became Trending Topic on Twitter. Catalan TV channels and radio stations buzzed and the controversy grew hour by hour. Right now, platform Change.org has three active campaigns to collect signatures to “save the 136 diacritical accent marks from a death sentence.”

The following day, instead of troubled waters getting calm, tempers were inflamed even more. Even some graffiti appeared:

The sentence, which with stress marks would be written “La dona dóna un os d’ós al nét net” will hardly ever be used, considering its meaning: “The woman gives a bone of bear to the clean grandson”, but it is a symptomatic example of the sudden Catalans’ love for their 136 words with diacritical stress marks. Some online media took advantage to propose tests and surveys to determine how many diacritics readers were able to recognize, as many Catalan speakers are not able to spell all the words with diacritical accents, as required by prescriptive rules. Note that these written accents do not follow any rules and, therefore, the only way to learn them is to do it by memory.

If I had to evaluate a distribution of supporters and opponents of diacritic accents suppression, I think much of the academic world (philologists and linguists) are for this simplification, while writers are divided 50-50. Interestingly, however, a large majority of Catalan speakers, let’s say, ordinary people, are absolutely against simplifying their language. Even songs and flash mobs appeared in YouTube in defense of Diacritic accents:

What makes Catalan speakers so zealous about an alleged complexity of the language? Before trying to answer, I would like to clarify that Catalan is as simple or complex as any other language of the Romance branch of Indo-European may be. Well, back to the question: With the end of sovereignty of Catalonia (in the eighteenth century), political and cultural decline began, the Catalan language was banned from public administration and education. The language was restricted to the private sphere and suffered a clear recession, reaching an almost jeopardized state during the fascist dictatorship of General Franco (1939-1975). With the arrival of democracy in Spain and the recognition of a certain autonomy for Catalonia, the language became the center of the Catalan cultural identity. Catalonia is currently undergoing a process of independence that has made people feel more proud than ever of their culture and, therefore, of their language. Catalan language now has a strong presence in all areas of society, government, education and the media, despite being a region where two languages (Catalan and Spanish) live quite harmoniously. And maybe diacritical accents have become a symbol of Catalans’ pride for their language.

After this controversy, I don’t want even to think what will happen with the spelling reform announced for 2017! If this point was reached with diacritics reform, I hope not to see barricades in the streets in defense of the only exclusively Catalan letter “L geminada “(l·l)!

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[This post was originally published in October 2013]

Honesty, like other personality traits, is notoriously difficult to test, let alone map. A rather ingenious new study attempted to measure honesty in an unusual way. Instead of using questionnaires that ask respondents whether they (or their behaviors) fall under a certain rubric, this study examined the behavior directly. The study, conducted by the makers of Honest Tea, involved setting up an unmanned booth with bottles of their product on display. Customers were asked to use the honor system and leave $1 for each bottle of tea they took. The percentage of people who paid for their drink in each state could easily be calculated.

The results of such a study are merely suggestive, as it is unclear whether the sample sizes were large enough or representative enough to produce robust results. A rigorous study of this nature would also have to make sure that the booths were located in areas with similar demographic characteristics in each state. Multiple sites in each state would also be necessary, especially in large states with distinct regional cultures, such as Texas and California. But regardless of such problems, we thought that they study was intriguing enough to merit a short post.

The booths prominently displayed the word “Honest” as part of the brand’s logo, but that did not prevent a relatively small percentage of people in most states from stealing drinks. Only in Alabama and Hawaii did everybody pay for the product. Other states vary as to the percentage of people who exhibited honest behavior (see my map on the left). Besides Alabama and Hawaii, Indiana and Maine topped the list with 99% of the folks there leaving a dollar for their drink. Residents of the District of Columbia proved to be the least honest, as only 4 out of 5 people paid for the drink. West Virginia, Texas, and Kentucky also did poorly on this score, with less than 88% of people leaving money.

As for larger geographical patterns, few unequivocal patterns can be gleaned from the map. The West Coast seems to be honest, but other regions are not uniform on this measure. For example, New England is generally honest, but Connecticut stands out as the least honest state (89%). People in the Midwest are shown as generally honest, but Michigan stands out with only a 92% payment rate. Similarly, the core states of the U.S. South are honest, but states in the periphery of the region (Texas, Florida, and North Carolina) do not fit the pattern (also, data is lacking for two Southern states: Louisiana and Mississippi). In several instances, sharp contrasts exist between neighboring states, such as North Dakota (96%) and South Dakota (90%), New Jersey (96%) and Delaware (88%), Oklahoma (98%) and Kansas (90%), or Tennessee (98%) and North Carolina (90%).

Interestingly, the spatial results of this study do not correlate the distribution of the Big Five personality traits, such as Conscientiousness (see map), or of the Seven Deadly Sins, such as Greed or Gluttony, as discussed in my earlier posts.

Nor is there a clear correlation with crime rates, especially property crime rate (see my map on the left). While the District of Columbia is just as crime-ridden as one would expect from the honest study, many other states pattern differently according to the two measures. Most striking is the example of Alabama, where 100% of the residents paid for their drink, but the property crime rate is one of the highest in the nation. More generally, the South is the most crime-ridden region in the country, yet it has come out as seemingly honest in the tea study. Another seemingly honest state, Hawaii (1000%) finds itself in the second-to-highest category of property crime rates. The reverse is true of South Dakota, Idaho, and West Virginia: although a high percentage of people there did not leave money in the booths, property crime rates in those states are very low (18.18, 20.69, and 22.74 per 1,000 population, respectively). New York and Connecticut, both of which have low “honesty” ranking, have some of the lowest property crime rates in the nation (19.12 and 21.67, respectively).

The post Mapping Honesty and Property Crime appeared first on Languages Of The World.

[This post was originally published in February 2012]

As discussed in earlier posts, abstract concepts such as personality or happiness can be mapped. A few years ago, geographers from Kansas State University tried to map the spatial distribution of another such abstract notion, that of evil. Geography research associate Thomas Vought and his colleagues used certain statistical measurements to quantify transgressions and came up with a county-by-county map purporting to show various degrees of the “seven deadly sins” in the USA (illustration on the left is a painting by Hieronymus Bosch). As UCLA statistician Nathan Yau pointed out on FlowingData.com, “these types of maps are always kind of iffy as they draw from data from various sources gathered with different methods and usually use some kind of researcher-defined metric”. Abigail Goldman of Las Vegas Sun is even harsher in her evaluation: “this is a precision party trick—rigorous mapping of ridiculous data”. Yet, these maps are instructive as they highlight and juxtapose a number of interesting social issues.

In Christianity, especially in Catholicism, a distinction is drawn between mortal (or cardinal) sins and the lesser, venial sins. What is included under which heading has changed over the years, but today’s list of the cardinal sin, dating back to the 590 CE version created by Pope Gregory I, includes wrath, greed, sloth, pride, lust, envy, and gluttony. The understanding of what each of the seven deadly sins actually encompasses has also evolved over time. Keep in mind that the quantifiable per-capita statistics chosen by the Kansas State team, such as theft (envy) and STDs (lust), may not correspond closely to any historical or modern definition of a given sin.

Let us start with wrath (Latin, ira), a word defined by Dante as “love of justice perverted to revenge and spite. Today the term “wrath” is perceived as somewhat archaic, with “rage” or “anger” generally used instead. It is best described as inordinate and uncontrolled feelings of hatred and anger. Such feelings need not be engendered by self-interest and can manifest themselves in different ways, including impatience, revenge, and vigilantism. The Kansas team calculated the “wrath” quotient as the total number of violent crimes—murder, assault, and rape—reported to the FBI per capita. Interestingly, in its original form, the sin of wrath encompassed not only anger pointed externally, but also rage directed internally. Thus suicide, deemed to be the ultimate rejection of God’s gifts, was counted as a wrathful act. But suicide rates were not included in the “wrath” metric by Vought and his colleagues. As can be seen from the map on the left, wrath in this sense is concentrated in Florida and surrounding states, Louisiana, east and south Texas, Delaware, central Michigan, New Mexico and Northern California. While some areas notable for their “rage” are urban (e.g. San Francisco Bay Area), others are rural. Overall, the Midwest and northern New England are classified as the least “angry” regions.

Another sin calculated in this study by using crime rates is envy (Latin, invidia). Originally derived directly from the Ten Commandments, specifically the injunction that “neither shall you desire… anything that belongs to your neighbor”, envy was defined by Dante as “a desire to deprive other men of theirs”. In his Divine Comedy, the punishment for the envious is to have their eyes sewn shut with wire because they have gained sinful pleasure from seeing others brought low. Thomas Aquinas described envy as “sorrow for another’s good”. In the Kansas study, “envy” was calculated using the total number of thefts—robbery, burglary, larceny, and grand theft auto—per capita. The envy hot zones include southern states, particularly Florida, Georgia and the Carolinas, and large metropolitan areas such as Detroit, Michigan; Dallas, Texas; New Orleans, Louisiana; Phoenix, Arizona; Denver, Colorado; Seattle, Washington; and Portland, Oregon. Surprisingly, San Francisco Bay Area is among these “envious” urban areas, but Los Angeles is not.

Like envy, greed (Latin, avaritia) is characterized by an insatiable desire; it is essentially a sin of excess, applied to a rapacious desire for and pursuit of material possessions. Envy has been classified as a mortal sin, that is sin against God, “in as much as man condemns things eternal for the sake of temporal things”, as Thomas Aquinas put it. In Dante’s Purgatory, the penitents were bound and laid face down on the ground for having concentrated too much on earthly thoughts. Greedy behaviors include disloyalty, deliberate betrayal, or treason, especially for personal gain, for example through bribery. Scavenging and hoarding of materials or objects, theft and robbery, especially by means of violence, trickery, or manipulation of authority are all actions that can be inspired by greed. The statistics used by Vought and his colleagues to represent greed is a curious one: they compared average incomes with the total number of inhabitants living beneath the poverty line. In one sense, this is a measure of social inequality, rather than of behaviors inspired directly by greed, such as bribe rates or the number of convicted con men per capita. Unsurprisingly, the highest rates of “greed” are found in urban areas such as the northeastern coastal strip extending from Boston to Washington DC; the extended “Chicagoland” in northern Illinois and Indiana, southeastern Wisconsin and southwestern Michigan; and the metropolitan areas of Detroit, Denver, and Seattle. Hotspots around the large cities of Dallas and Houston in Texas stand out, as does Clark County, Nevada, home of Las Vegas (more on which below). In California, both San Francisco and Los Angeles are “greedy”, as is indeed most of the state. Though “angry” and “envious”, most of the Southern states are not “avaricious”, with the exception of southern Florida.

Like greed, lust and gluttony are sins of excess. Lust (Latin, luxuria) today is defined as excessive sexual wants; however, the word originally denoted the intense desire for money, fame, or power. (Hence, the English word luxury refers to the best and most costly things that lead to any form of comfort and satisfaction.) In Dante’s Purgatory, those guilty of lust walk within flames to purge themselves of lustful/sexual thoughts and feelings, while in his Inferno, the unforgiven souls guilty of the sin of lust are blown about in restless hurricane-like winds symbolic of their own lack of self-control over their lustful passions in earthly life. In the Kansas study, the modern definition of “lust” as having to do with sexual passions alone has been employed, with the degree of “lust” calculated by compiling the number of sexually transmitted diseases—HIV, AIDS, syphilis, Chlamydia, and gonorrhea—reported per capita. Needless to say, this measure incorporates not only “lust” (even if in the narrowly defined modern sense), but also a certain degree of recklessness. The hot zone of lust extends along the Atlantic seaboard from southern New Jersey to Georgia and from there westward into northeastern Texas. Unexpectedly, Florida, a popular vacation and spring break destination, is not particularly “lustful” (except the western panhandle part of the state, adjacent to the “licentious” states of Georgia and Alabama); neither is California. An interesting contrast is presented by South Dakota: the western part of the state ranks much higher in “lust” than its eastern counterpart. Another mystery is a peculiar hot zone of “lust” in eastern New Mexico and the adjacent parts of Texas.

Another sin of excess, gluttony (Latin, gula), derives from the Latin verb gluttire, meaning to gulp down or swallow; it is defined as the over-indulgence and over-consumption of anything, but especially of food and drink, to the point of waste. In Christianity, gluttony was considered a mortal sin because it was interpreted as indicating selfishness, as the excessive desire for food leads to withholding it from the needy. Medieval church leaders like Thomas Aquinas took a more expansive view of gluttony, arguing that it could include not only eating too much (Latin, nimis), but also an obsessive anticipation of meals (praepropere), and the constant eating of delicacies and excessively costly foods (laute). Even matters of good manners entered into this concept, as eating too eagerly (ardenter), too daintily (studiose), or too wildly (forente) were all considered gluttonous acts. The Kansas study again takes a narrow definition of this sin, which runs counter to the historical view of gluttony as daintily eating expensive foods, and calculates it by counting the number of fast food restaurants per capita. There are three such “gluttony” hot zones in the U.S.: one in the rural areas of west-central Texas, another in eastern Virginia and northeastern North Carolina, and a third at the confluence of Virginia, West Virginia, Kentucky, North Carolina, and Tennessee. On the state level, Texas ranks highest in gluttony. Along with North Carolina, Tennessee, and Kentucky, Texas is also one of the biggest spenders on fast food, as can be seen from this map.

Crucially, it is the number of fast food restaurants per capita that counts, not the total number of such eateries, which are most numerous in urban areas in zones that do not stand out on the “gluttony” map, as the map reproduced on the left shows.

While previous sins can be described as stemming from passion, sloth (Latin, acedia or socordia) is decidedly lacking in zeal or enthusiasm. While sloth is often defined as physical laziness, the Christian tradition emphasizes spiritual laziness, or a rejection of grace and God. Sloth has also been defined as a failure to do things that one should do, as evil exists when good people fail to act. Over time, this sin was reinterpreted to encompass a failure to utilize one’s talents and gifts. Already in Dante’s Purgatorio, the penance for sloth was running continuously at top speed. In the Kansas study, the measure of sloth is perhaps the weirdest of all: it is calculated by comparing expenditures on arts, entertainment, and recreation with the rate of employment. As the statistical measure of “sloth” is odd, so is its the spatial distribution, with several small hotspots, some in urban areas and some in rural ones. There is no clearly defined “laziness” belt, nor a particularly hardworking zone.

Nor is there any apparent negative correlation between the sin of sloth and the personality trait of conscientiousness, as mapped by Renfrow and colleagues. Texas and South Carolina, which are mapped as having the least slothful areas, are not among the top 10 states when it comes to conscientiousness. The most dutiful state, New Mexico, has some of the counties most noted for their rate of “sloth”.

The seventh and final sin, considered the original and most serious of the seven deadly sins, and the source of the others, is pride (superbia in Latin or hubris in Greek). Pride is identified as a desire to be more important or attractive than others, failing to acknowledge the good work of others, and excessive love of self. Dante defined “pride” as the “love of self perverted to hatred and contempt for one’s neighbor”, but a more spiritually serious aspect of pride is putting oneself out of proper position toward God, making it a mortal sin. The best-known example of this sin and the consequences is the story of Lucifer, whose pride and desire to compete with God caused his fall from Heaven, and his resultant transformation into Satan. According to Dante, those guilty of pride were forced to walk with stone slabs bearing down on their backs to induce feelings of humility. In accordance with the view that pride is the root of all other mortal sins, the Kansas geographers calculated it by aggregating the data from the six other sins, averaged into an overview of all evil.

When it comes to pride, there is a clear north-south divide, which correlates roughly with the general crime rates, as can be seen from the map on the left. Yet, the discrepancies are instructive as well. For example, Nevada, one of the most crime-ridden states is relatively low on “pride”; conversely, Mississippi, which is very “proud”, is not noted for a particularly high crime rate.

One final note pertains to Las Vegas, Nevada, which bears the nickname of “Sin City”. Vought and his colleagues made a detailed study of the level of sin in 10 top casino markets around the country and discovered that the moniker of Las Vegas is not entirely deserved. While the Las Vegas Strip ranks highest in greed, it comes only second in wrath (after Shreveport, Louisiana, one of the most unhappy urban areas in the country, according to a different study). Las Vegas could muster no better than third place for pride, the aggregate of all sins; it was the southern gambling cities—Lula in Mississippi and Shreveport, Louisiana—that came out on top of the bottom. Despite all the strip clubs, sex shows and the like, Las Vegas ranked only fourth in lust (after Tunica, Mississippi; Shreveport, Louisiana; and Biloxi, Mississippi). When it comes to sloth, envy and gluttony, Las Vegas is a mere fifth, “bested” by such places as Atlantic City, New Jersey; Chicagoland (Illinois/Indiana); and Detroit, Michigan.

The post The Geography of Sin appeared first on Languages Of The World.

[This post was originally published in March 2013]

A recent study, conducted by researchers at the University of Vermont, once again looked into the question of where happy people live. Previous studies on the geography of personality, discussed in earlier posts, were interview-based attempts to assess permanent personality traits (which may even be encoded genetically). This recent study looks at the state of happiness, temporary as it may be for any given person. The technique used to gauge happiness is novel as well: instead of asking people how happy they are, researchers sifted through more than 10 million geotagged tweets from 2011, looking for “happy” and “sad” words. They used the Mechanical Turk Language Assessment word list, which includes 10,000 words rated on a scale 1 to 10 according to how much “happiness” they convey. “Sad” or “negative” words include damn, boo, mad, ugly, hate, no, smoke, jail, and lied, as well as a colorful and thorough assortment of expletives. The inclusion of the cusswords among the indicators of unhappiness may have biased the results, as the liberal use of swear words seems to be a key factor in the overall happiness score of several locations, both on the state and city level. On the positive end of the scale are the ubiquitous LOL and haha, as well as love, beauty, hope, good, nice, wonderful, sleep and wine, along with words related to food or the beach. According to the list, rainbow is one of the happiest words, and earthquake is one of the saddest. While the researchers admit that their technique ignores context, they claim that for large datasets, simply counting the words and averaging their happiness content produces “reliable” results.

The map reproduced above demonstrates the results of the study that focused on urban areas. The happiest state turns out to be the aloha-filled Hawaii, followed by Maine, Nevada (think Las Vegas!), Utah, and Vermont. At the bottom of the list is Louisiana; Mississippi, Maryland, Delaware, and Georgia round-out the list of the five least happy states. Since beach-related vocabulary featured prominently in the “happy word” list, the high ranking of Hawaii is not surprising: according to TripAdvisor’s Travelers’ Choice 2013 list, 8 of the top 25 beaches in the U.S. are located in Hawaii. However, nine of Florida’s beaches made into the top 25 list, yet Florida is not among the happiest states in the Union. At the city level, the wine- and beach-oriented vacation destinations of Napa, Santa Cruz, and Santa Barbara (all three in California) were predictably at the top of the ranking. But other locales, both cities (Longmont, Colorado; Green Bay, Wisconsin; Spokane, Washington; and San Jose, California) and states (Idaho, Maine, Washington), which are not year-round tourism hot spots still measure high on the happiness ranking. The five most bummed-out cities, according to their residents’ word choices, were Beaumont, Texas; Albany, Georgia; Texas City, Texas; Shreveport, Louisiana; and Monroe, Louisiana. Overall, coastal areas appear to be more chipper than landlocked areas. Curiously, the cities with a higher density of tweets tend to be less happy, the cheerful designation of San Jose notwithstanding, which leads to a surprising conclusion of the study that “cities with high technology adoption rates (as most geotagged tweets come from devices like smartphones) are in fact less happy than their less technological counterparts”. The researchers also compared their results with census data and found that wealthy areas tend to have higher happiness levels—so perhaps money can buy some degree of happiness after all? Another fascinating finding is that areas with high rates of obesity have lower happiness levels. In order to address this latter discovery, researchers created lists of words that were more common in low-obesity areas (e.g. cafe, sushi, brewery, and banana) or in high-obesity areas (such as McDonalds, wings, ham, and heartburn).

Apart from examining the levels of happiness in different locales, this study underscores the promise of social networks for social science research, but also highlights some major limitations. For example, the researchers point out that only 15% of online adults use Twitter, individuals who do not accurately represent the demographics of the country. In particular, the authors did not look at Twitter in Spanish. The prevalence of Western states with large Latino populations on the happy list would seem to suggest that cities where the poor population is primarily Spanish speaking would appear happier than warranted by the alleged positive correlation between income and happiness levels. Another issue worth exploring is whether people might project happiness in their speech differently in different parts of the country or within various demographic groups. For example, the study identified people with Norwegian ancestry as happier than African Americans. Is that because the Norwegians are actually happier or do they just tweet as if they are happier? This is not an easy question to solve, but the researchers show that their data is buttressed by a correlation with other measures of happiness, primarily surveys conducted by Gallup, such as this most recent survey, which too found that “that states from the West, Midwest and New England held many of the top spots, while the South took many of the spots at the low end of the scale”. There are some important discrepancies between the Twitter-based study and the recent Gallup findings: for example, Maryland in the bottom five according to the former study, but ranks 11th according to the Gallup survey; Maine is the second happiest state according to Twitter, but only #20 (tied with Wisconsin) according to Gallup; and Nevada is the 3rd happiest state according to Twitter, but tied at 39th place with Oklahoma and South Carolina according to Gallup.

Another interesting question is whether the results of this study correlate with permanent personality traits, such as those used in the Five Factor Model (Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness to new ideas). The obvious candidate for such a linkage is neuroticism: people—and consequently locations—that rank high on the neuroticism scale are expected to be frequently unhappy. But the correlation does not hold very well. While three out of the five “happy states” (Hawaii, Nevada, and Utah) rank low on the neuroticism scale, twitter-cheerful Maine and Vermont are in the top half of the neuroticism ranking. Similarly, some of the unhappy states, particularly Mississippi and Louisiana, are ranked as very neurotic, but Georgia ranks only 33rd on this scale. Nor do any of the other four personality traits correlate with happiness. For example, the sixth most extraverted state, Georgia, is unhappy, but the eighth, Utah, is in the top five cheerful states. Introverted Vermont is happy, while the even more introverted Maryland is miserable. Agreeable residents of Mississippi are despondent, but equally agreeable Utahans are contented. Most states high on the happiness scale rank low on conscientiousness (especially Vermont, Hawaii, and Maine), but the very dutiful inhabitants of Utah are happy, while the equally dutiful Georgians are sad. High openness to new ideas appears to cheer up the residents of Nevada and Vermont, but not those in Maryland.

Overall, it appears that although Leo Tolstoy may have been right in that “happy families are all alike”, another Russian writer Arkady Gaidar hit it on the nail with his “what happiness is, everybody understood in their own way”.

The post The Geography of Happiness—According to Twitter appeared first on Languages Of The World.

[This post was originally published in November 2012]

While research on the geography of personality, such as the 2008 study by Rentfrow and colleagues, published in Perspectives on Psychological Science and described in the previous post, provides an interesting insight into the distribution of psychological traits over the country, there are a number of problems with this sort of inquiry, some recognized by the authors and others not.

Several of the flaws in Rentfrow et al.’s study are inherent to the Five Factor Model of personality that they use. First, the five factors—extraversion, agreeableness, conscientiousness, neuroticism, and openness to experience—are not fully orthogonal to one another. For instance, there appears to be a negative correlation between neuroticism and extroversion: those who are more prone to experiencing negative emotions tend to be more introverted. Certain behaviors, moreover, can be seen as manifestations of more than one of the five traits: for example, thinking before acting is linked by some psychologists to introversion and by others to conscientiousness. Second, the same traits can be given either negative or positive values: for instance, low level of openness to new ideas can be viewed as narrow-mindedness or as valuing tradition, while a high score on the neuroticism scale may be branded positively as “being in touch with one’s feelings”. Such differences in labeling the same trait may have a geographical dimension. According to Ted Ownby of the University of Mississippi, residents of this state, which ranks 4th on the neuroticism scale, “would be proud”, of such a ranking, as “in the home of William Faulkner, [they] take intense, almost perverse neuroticism as a sign of emotional depth”. Third, a number of psychologists have argued that the “Big Five” do not encompass all aspects of human personality, and have therefore suggested adding other traits to the list, especially those that are more privately held or more context-dependent and are therefore harder to observe in a stranger. Among such additional traits are honesty, attachment, need for achievement, manipulativeness, thriftiness, masculinity/femininity, sense of humor, sexiness/seductiveness, snobbishness/egotism, and risk-taking/thrill-seeking. As Rentfrow et al. point out, “it is tempting to suppose that geographic variation in such variables would be linked to an assortment of important geographic social indicators, such as crime, social capital, marriage and divorce rates, and economic growth” (p. 364). I, for one, would like to see whether sense of humor correlates with crime rates, or whether sexiness/seductiveness has any connection with economic growth.

An additional issue is that the same trait may manifest itself differently, both at the individual and regional levels of analysis. For example, a dutiful person may apply his thoroughness and self-discipline in a number of distinct ways. At the state level, this trait correlates almost equally strongly with both religiosity and with health-promoting behaviors (see the table reproduced on the left).

Moreover, a comparison of the conscientiousness map and the church attendance map (see on the left) reveals that while some “dutiful” states, like Utah (which ranks 4th on conscientiousness scale), also have high rates of church attendance, others, like Colorado (which ranks 15th on conscientiousness scale), have some of the lowest church attendance rates in the nation. But Colorado has many outdoors and sports enthusiasts. Thus, it appears that conscientiousness manifests itself through going to church in some states and through going to the gym in others, but Rentfrow’s study obscures that distinction.

A much more significant problem is that the study provides psychological snapshots of states as a whole. As alluded to in the previous post, my impression of New Yorkers, based on residents of Ithaca, might have been quite different had I been more exposed to Manhattanites. Such averaging of upstate “apples” and uptown “oranges” may well bring an average resident of the state down on the agreeableness scale and up on the neuroticism scale as compared to what I would have imagined based on my personal experience. In a state as large and diverse as California, profound regional differences in personality formation would likely be encountered. Rentfrow et al. admit that “it would be useful to examine even narrower geographic levels of analysis” (p. 363). They refer to an earlier study of individualism and collectivism, conducted in Australia and Japan, which found that “participants from rural locales were higher in collectivism than were those living in metropolitan cities” (p. 363).* Moreover, as pointed out by Wall Street Journal’s Stephanie Simon, “the assessments were linked to each respondent’s current residence, so there was no way to tell if a New Yorker was a New Yorker born and bred, or had just moved from Kansas… who may, after all, have been drawn to New York because the big-city bustle suited their personality”.

But how often do people move to places that suit their personalities? This brings us to the biggest problem of all, the chicken-and-egg question, formulated by Simon as follows: “Do states tend to nurture specific personalities because of their histories, cultures, even climates? Or do Americans, seeking kindred spirits, migrate to the states where they feel at home? Maybe both forces are at work—but in what balance?”. Rentfrow and colleagues raise a slew of larger related questions, which their current research can merely probe:

“Are people happier in environments where their personalities fit the modal personalities of the places they live? Does a lack of fit predict depression or decisions to live elsewhere? Do regional differences in personality have a genetic or environmental origin? How stable is region-level personality over time? Are regional differences in personality related to differences in regional cultures? If so, does one give rise to the other? Can regional personality differences influence the efficacy of social, economic, or health policy reforms? That is, are certain policies more effective in environments where specific personality traits are prevalent? What are the regional characteristics that attract people to live in a place? Do people find those characteristics equally attractive? Do natural disasters or sudden economic shifts within regions affect personality trait prevalence?”

At the moment, the causal directions of the relationships among biology, personality, and culture are not yet clear. Some scholars (e.g. McCrae 2001) attribute geographical differences to biology and suggest that culture is a reflection of biological and genetic differences, while others attribute the differences to culture and argue that national cultural differences cause individuals to develop different personalities (cf. Hofstede 2001; Triandis & Suh 2002). Rentfrow et al. suggest conducting time-lagged analyses using geographic personality estimates and social indicator data, such as those used in their 2008 study, but collected over several years. They hypothesize that “if region-level personality is a cause of differences in culture and geographic social indicators (e.g., crime rates, public opinion, morbidity), then changes in personality trait prevalence should lead to changes in the outcome variables” (p. 363). For example, if a high number of “open” individuals migrate to a state ranking low on the openness scale, such as Alabama or Wyoming (48th and 50th, respectively), “that change may lead to an increase in liberal public opinion and patent production and, thus, to a more open culture”. The causal relationship from region-level personality and differences in culture and geographic social indicators is well supported by research in several disciplines. Numerous personality studies clearly indicate that individual differences in personality are connected to a range of psychological and behavioral tendencies; work in macroeconomics, political science, sociology, and cultural psychology provides evidence that group behavior affects macrosocial variables such as crime rates or voting patterns.

What is much less clear is whether “macrosocial variables precipitate regional differences in personality”; that is, whether “societal changes should lead to changes in personality trait prevalence” (p. 363). According to this hypothesis, a drop in crime rate in a given region would be expected to lead to an increase in agreeableness and a drop in neuroticism. While no controlled studies are available to confirm or disprove this idea, it appears that changes in personality cannot be brought about easily by changes in macrosocial variables. For example, New York state as a whole has experienced a significant drop in crime rates in the 1990s; by 2008 its crime index has dropped to nearly a third of that in 1990.

New York’s crime rate in 2008 (the year of Rentfrow et al. study) was comparable to that of Kansas or Ohio, yet New York remains near the bottom of agreeableness ranking, in the 47th place (out of 51). Ohio ranks higher, at 27th place, while Kansas ranks higher still, at the 17th place. Clearly, even if New York state has experienced a rise in agreeableness, it could not have been a significant one. (When it comes to neuroticism ranking, Kansas is ranked much lower than New York—34th and 3rd places, respectively—while Ohio’s 9th place ranking is close to that of New York.)

Incidentally, crime rate figures remind us of the dangers inherent in generalizing over states: when it comes to crime rate statistics, New York’s counties vary widely, even if we compare only rural counties. For example, the property crime rate in Tompkins County (where Ithaca is located) is only about half that of Cattaraugus County, also in upstate NY, while the same figure for Herkimer County exceeds that of Tioga County eight-fold.

Similarly, counties differ in regard to their crime trends: for example, Tompkins County experienced a sharp increase in crime rates—both property and violent crime—in 2001-2008, whereas Albany County (home of the state’s capital, Albany) experienced a drop in crime over the same period.

In other states, the situation is much the same. For example, in California property crime rate in San Joaquin County in 2007 was more than double that the more peaceful and prosperous San Mateo, Orange, and Ventura counties.

Let’s go back to the issue of whether the prevalence of a certain personality trait in a given region or state may change in response to institutional or policy shifts and consequent transformations in macrosocial variables. In principle, there are two ways in which such changes in a state’s psychological profile may occur: either through established residents developing a certain trait in response to external social changes or through individuals already possessing that trait moving to the state because of such social changes. For example, a drop in the crime rate might cause old-time residents to develop warmer and less neurotic personalities, or it might attract warm and calm individuals from other areas. While both possibilities probably happen, personality changes in individuals are neither quick nor sharp, in large part because the Big Five traits have been shown to be affected by both nature and environment in roughly equal proportion. Depending on the trait, between 42% and 57% of observable differences between individuals is said to be due to genetic differences. While these heritability figures are derived mostly from twin studies, new light has been shed on the nature/nurture issue in regard to personality by genetic research. Studies such as Depue & Collins (1999) have linked extraversion to higher sensitivity of the mesolimbic dopamine system to potentially rewarding stimuli, which has in turned been shown to be genetically encoded.

Individualism/collectivism too has been shown to have a genetic basis. Having analyzed data from 30 countries, Chiao and Blizinsky (2010) found a strong correlation between collectivism and the presence of a certain genetic marker in the serotonin transporter gene (i.e. S allele of 5‑HTTLPR), which is known to put individuals at greater risk for depression when exposed to life stressors—in the absence of social support networks found in collectivist cultures.** The figure, reproduced on the left from Chiao and Blizinsky (2009), illustrates the geographical coincidence between genes and culture across countries. The map (a) in the upper left shows world-wide variation in individualism-collectivism ranging from yellow (individualist) to red (collectivist). The map (b) in the upper right shows the frequency distribution of the relevant genetic marker. The map (c) in the bottom left depicts the global prevalence of anxiety, while the map (d) in the bottom right illustrates the global prevalence of mood disorders (yellow to red color bar indicates low to high prevalence).

The idea is that that collectivist cultures protect individuals from the genetically predetermined risks by embedding them more strongly in communities with strong social links thus providing robust psychological support networks. Therefore, such a gene is more adaptive in collectivist cultures and may be selected against in individualist cultures.

Another study, Way and Lieberman (2010), identified another marker in a gene involved in neurotransmitter regulation. They reasoned that this gene operates by making people more socially sensitive and thus more prone to depression in the absence of the strong social support available in collectivist cultures. A third personality-related genetic marker, also in a dopamine receptor gene, has been linked to non-conformity, novelty seeking, impulsivity, and attention deficit hyperactivity disorder.

As a result of personality traits having a genetic basis, it is not easy to turn a born-introvert into an outgoing extravert, a collectivist into an individualist, an anxiety-ridden person into a happy and calm one, a perfectionist into a careless and easy-going individual, or vice versa. But what of the possibility that people migrate to areas that suit their personality? Hard data is not available but it is possible that such process occurs, even if on a subconscious level. For example, there is ample evidence that some people decide to move to areas that tend to vote along the same lines. Since voting patterns have been shown to be linked to psychological traits, it is natural to assume that people also sort themselves by personality—even if indirectly so.

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*Japanese participants on average turned out to be higher in collectivism than those from Australia.

**Another study by Stoltenberg et al. (2002) related the 5-HTTLPR polymorphism associated with the serotonin transporter gene to openness to experience, whereas an earlier study by Lesch et al. (1996) found some connection between this polymorphism and neuroticism. Such multiple connections between a given genetic marker and a number of different personality traits further highlight the point that the Big Five Factors may not be fully orthogonal.

Sources:

Chiao, Joan Y. and Katherine D. Blizinsky (2010) Culture–gene coevolution of individualism–collectivism and the serotonin transporter gene. Proceedings of Biological Sciences 277(1681): 529–537.

Depue, R. A., & Collins, P. F. (1999). Neurobiology of the structure of personality: Dopamine, facilitation of incentive motivation, and extraversion. Behavioral and Brain Sciences 22: 491–517.

Hofstede, G. (2001) Culture’s consequences: Comparing values, behaviors, institutions, and organizations across nations (2nd ed.). Thousand Oaks, CA: Sage.

Lesch, Klaus-Peter; D. Bengel; A. Heils; S. Z. Sabol; B. D. Greenberg; S. Petri; J. Benjamin; C. R. Muller; D. H. Hamer; and Dennis L. Murphy (1996) Association of anxiety-related traits with a polymorphism in the serotonin transporter gene regulatory region. Science 274 (5292): 1527–1521.

McCrae, R.R. (2001) Trait psychology and culture: Exploring intercultural comparisons. Journal of Personality 69: 819–846.

Stoltenberg, Scott F.; Geoffrey R. Twitchell; Gregory L. Hanna; Edwin H. Cook; Hiram E. Fitzgerald; Robert A. Zucker; Karley Y. Little (2002) Serotonin transporter promoter polymorphism, peripheral indexes of serotonin function, and personality measures in families with alcoholism. American Journal of Medical Genetics 114 (2): 230–234.

Triandis, H.C., & Suh, E.M. (2002) Cultural influences on personality. Annual Review of Psychology 53: 133–160.

Way, Baldwin M. and Matthew D. Lieberman (2010) Is there a genetic contribution to cultural differences? Collectivism, individualism and genetic markers of social sensitivity. Social Cognitive and Affective Neuroscience 5(2-3): 203-211.

The post Problems with “Geography of Personality” Research appeared first on Languages Of The World.

[This post was originally published in November 2012]

When I moved from upstate New York to California some five years ago, the culture shock was almost as significant as when I had moved from Russia to Israel, then to Canada, then to the UK, then to Norway, and then to the United States. This time the language, the currency, and the shape of power outlets were the same, but people appeared quite different in how they handled themselves, socialized with others, or approached life’s problems. Neurotic New Yorkers versus Laid-Back Californians? Perhaps. Though in some ways, my former neighbors in Ithaca, New York seemed more laid-back and less neurotic than my new neighbors in Mountain View, California. Where upstate New Yorkers appeared more friendly and more willing to resolve issues by relying on the common sense, Californians seemed more concerned with rules and appearances. But are these just my personal impressions of the specific people that I had met by chance, or is there such a thing as a psychological portrait of a state? According to some sociological studies, such regional stereotypes are not mere clichés, but have empirical support.

One such study was conducted by Peter Jason Rentfrow of the University of Cambridge (England), in collaboration with colleagues from Austin, Texas and Cambridge, Massachusetts. The study, based on more than 600,000 questionnaires and published in the journal Perspectives on Psychological Science in 2008, maps regional clusters of personality traits and searches for correlations with data on crime, health, and economic development. The personality assessment test consists of 44 questions and evaluates the so-called “Big Five personality traits”: extraversion, agreeableness, conscientiousness, neuroticism, and openness to experience. The extraversion dimension (E) characterizes how people energize themselves: extraverts tend to be energized when around other people, whereas introverts gain energy through reflection and solitude. Where extraverts are described as “outgoing”, “talkative”, “assertive”, and “gregarious”, introverts are typically more solitary and reserved. Agreeableness (A) manifests itself in behaviors that are perceived as kind, sympathetic, cooperative, warm, and considerate; the two ends of the its continuum are “friendly/compassionate” versus “cold/unkind”. Conscientiousness (C) includes such elements as self-discipline, carefulness, thoroughness, self-organization, deliberation, and need for achievement.* People who score high on this trait are characterized as being efficient, organized, neat, and systematic, or even as “workaholics” and “perfectionists”; those who score low can be described as “easy-going” or “careless”. Neuroticism (N) manifests itself through anxiety, moodiness, worry, envy, and jealousy; individuals who score high on neuroticism are often self-conscious and shy. Finally, openness (O) to experience involves such characteristics as active imagination, aesthetic sensitivity, and intellectual curiosity. According to Rentfrow’s team, although “each state shows substantial variation on all of the FFM [Five Factor Model] variables” (p. 350), there are significant state-level differences in personality profiles. For example:

“North Dakota ranks highest on E and A, in the middle on C, near the bottom on N, and lowest on O, suggesting that North Dakotans are more sociable and affable and less anxious and imaginative than are people in other states. In contrast, New York ranks in the middle on E, near the bottom on A and C, and at the top on N and O, indicating that New Yorkers are less warm and dutiful yet more high-strung and creative than are people in the rest of the country.” (p. 350)

Their study also shows that “the personality dimensions are not randomly distributed, but geographically clustered” (p. 350). For example, extroversion appears to be highest in the Great Plains, Midwest, and Southeastern states and lowest in the Northwest and most of the Mid-Atlantic and East Coast states. Both New York and California rank fairly low on the extraversion score (32nd and 38th place, respectively). The most extraverted state is North Dakota and the most introverted one is Maryland.

Agreeableness is highest in the Midwest, South Central, and Southeastern states and lowest in the Northeast. New Yorkers rank much lower on this trait than Californians (47th vs. 28th place). As with extraversion, North Dakota again tops the charts, whereas Alaskans come out as having the coldest personalities.

Conscientiousness is highest in the Southwest, Midwest, and Southeast and lowest in the Mid-Atlantic and New England. In contradiction to the stereotypes, Californians are more “workaholics” and “perfectionists” (27th place) than the “easy-going” New Yorkers (42nd). According to the study, the most conscientious state in the nation is New Mexico and the least conscientious one is again Alaska.

In line with expectations, neuroticism is highest in the Northeast and Southeast and lowest in the Midwest and West Coast. New York has the third highest score on this trait, while California ranks relatively low (37th). Curiously, the list of high-anxiety states includes not just New York and New Jersey, but also states stressed by poverty, such as West Virginia, which scores highest on this trait, and Mississippi, which ranks 4th. The least neurotic state turns out to be Utah.

The statewide distribution of openness to experience is also in line with the earlier studies and tends to be high in New England and in the Mid-Atlantic and West Coast states and low in the Great Plains, Midwest, and South Central states. Both New York and California rank high (2nd and 6th, respectively). District of Columbia tops the chart on this trait, while North Dakotans are at the bottom of the list.

While these findings tend to support some cultural stereotypes, there are numerous surprises as well. For instance, New Englanders, often viewed as “flinty pragmatists”, come out as less dutiful than they may seem, ranking at the bottom of the “conscientious” scale. Those who remember the movie “Fargo”, which depicted North Dakota “as a frozen wasteland of taciturn souls”, would be surprised that this state is rated as the most outgoing in the nation. As Wall Street Journal’s Stephanie Simon puts it, “turns out you can be a laconic extrovert, at least in the world of psychology”. And who would have thought of Floridians as conscientious (8th) or of Kentuckians as neurotic (7th)?

Perhaps even more revealing than the snapshots of states’ psychological profiles are the correlations between each state’s dominant personality type and certain social indicators such as crime rates, levels of social involvement, religiosity, political opinion, occupational prevalence, health behavior, and mortality. “Agreeable states”, such as Minnesota (which ranks 2nd), tend to have low crime rates and high life expectancy. In contrast, life expectancy is lower in “neurotic states”, which are characterized by lower levels of health-promoting behaviors such as exercising at home, and unsurprisingly, also by higher incidence of deaths from heart disease and cancer. “Dutiful states” have a larger proportions of computer scientists and mathematicians, while states ranking low on conscientiousness produce more artists and entertainers. States that rank high in openness to new ideas are quite creative, as measured by per-capita patent production. They also have a high proportion of residents in both artistic and investigative professions. But such states are also known for high levels of crime and low level of social involvement (as measured by such activities as “going to a bar or tavern” and “spending a lot of time visiting friends”). Social involvement is predictably high both in states that rank high on the extraversion and it those with elevated agreeableness rankings, but in a different manner. Residents of extraverted states spend more time going to club meetings or bars, but “their socializing is apparently somewhat indiscriminate and is not restricted to close friends” (p. 355). In contrast, residents of agreeable states are more involved in “activities that promote tight social relations, including spending time with friends and entertaining at home” (p. 356).

Each state’s psychological profile also correlates with the views of its residents on religion and politics. While religiosity is linked with both agreeableness and conscientiousness on state level, it appears that agreeableness is a better predictor of church attendance, while conscientiousness correlates stronger with the importance that individuals place on religion in their value systems. Conversely, residents of states that rank high on openness to experience “place considerably less importance on religion and attend church less often than do those in low-O states” (p. 360), which seems to reflect the degree to which individuals uphold or reject conventional value systems. But high ranking on the openness scale goes hand in hand with liberal value indicators: people in such states tend to “have more progressive and tolerant views about sundry social issues” (p. 360), such as legalization of marijuana, abortion, and gay marriage. These views are typically put into practice in high openness states: for example, nine of the top ten “open” states have either legal medical marijuana (e.g. Washington and Vermont), have decriminalized marijuana possession (e.g. New York and Massachusetts), or both (e.g. Oregon, California, Nevada, and Colorado).

Similarly, legal recognition of gay marriage correlates strongly with the state’s ranking on the openness scale: nine out of top ten “open” states, as well as District of Columbia, have some sort of legal recognition of same-sex marriage. Three of the states governments—New York, Massachusetts, and Vermont—allow same-sex marriage.** California, Colorado, Maryland, Nevada, Oregon, and Washington have had legal unions for same-sex couples that offer varying subsets of the rights and responsibilities of marriage. In 2012 elections, citizens of Maryland and Washington voted in favor of approving the respective state laws passed earlier the same year legalizing same-sex marriages. The only state among the top ten “open” ones that bans same-sex marriages and other kinds of same-sex unions is Virginia.

High scores for openness to new ideas correlates not only with liberal social values but also with Democratic voting habits. However, three of the top ten “open” states—Colorado, Nevada, and Virginia—have voted Republican in most recent presidential races.*** While they all went for Obama in the 2008 election (the same year that Rentfrow’s study was conducted), all three states voted Republican in 2000 and 2004, and two of them—Colorado and Virginia—also voted Republican in 1996. In this year’s elections, Colorado, Nevada, and Virginia were hotly contested, but ultimately all three voted for Obama again.

Some social scientists suggest taking the findings of this research further than predicting voting patterns and into the realm of socio-economic development. Perhaps, they argue, it would be beneficial for health officials in the Northeast “stress belt” to consider programs to help folks relax, while dutiful states “might look to woo more innovative personalities, perhaps by nurturing an artists’ enclave or encouraging young chefs to start restaurants”. But before policy makers may far-reaching decisions, it might be worth considering some of the problems with such research, to which we shall turn in the next post.

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*According to some psychologists, deliberation is also part of the introversion package.

**The only state that currently offers same-sex marriages and which ranks low on the openness scale is Iowa (43rd).

***District of Columbia ranks highest on the openness scale, hence the list of the top ten states includes Virginia, which ranked 11th.

The post The United States of Mind appeared first on Languages Of The World.

As promised in an earlier post, I am presenting here an informal response to the article, published recently in Genome Biology and Evolution by Paul Wexler, Eran Elhaik and colleagues (henceforth, Das et al. 2016). To summarize my reaction, I find this article not only wrong in substance but also badly written, with the latter flaw partially concealing both the depth of the problems in the underlying research and the unremarkable ultimate conclusion of the paper is (if it were correct, which I don’t think it is). I will start with exposition issues and move on to the more substantial problems in the second half of the post.

To begin with, the authors make it very difficult for a reader to know what they are saying and what they mean by using both technical terms and non-specialist words with meanings that seem to be peculiar to them. For instance, the term substratum is used in this article to mean (as far as I can glean from context) ‘lexical borrowings’, whereas linguists use this term to refer to influences of a language that was supplanted by the target language. For example, in the second sentence of the “Introduction”, they describe their view (which opposes the general consensus) as ascribing to Yiddish “a Slavic origin with strong Iranian and weak Turkic substrata”. For the term substrata to be meaningful here, Yiddish must have supplanted (some) Iranian and Turkic languages. But there is zero evidence—and Das et al. certainly offer none—that non-Jewish Iranian and/or Turkic speakers shifted from their original languages to Yiddish. Moreover, substratal influences are typically grammatical and/or phonological, not merely lexical. Das et al. and the references they cite (mostly to one of the team’s researcher’s own earlier works) offer no convincing evidence of such structural influence of either Iranian or Turkic languages on Yiddish.

Or consider the word primeval, which appears both in the title and the text of the article (total 8 times). A dictionary definition of this word is “of or resembling the earliest ages in the history of the world, prehistorical, antediluvian, primordial”. However, the authors do not examine prehistorical events. Rather, their story concerns the events of merely 10-12 centuries ago; medieval would certainly be a more appropriate word. With respect to certain peoples or parts of the word, using prehistorical in reference to the 9^th century CE would be accurate, as this term is normally reserved for “the past before the advent of writing”, but when talking about Jewish traders on the Silk Routes, this word choice is hardly appropriate. Is using primeval in this context aimed to impress a reader whose area of expertise is not in the realm of human history? Perhaps.

Sloppy and confused understanding of historical geography is another major issue with the Das et al.’s article. Let’s consider three quotes from the article. First, on page 5 the authors describe the consensus view, the so-called “Rhineland hypothesis”, as envisioning two mass migration waves that gave rise to Eastern European Ashkenazi Jewry: the first wave was “from ancient Israel to Roman Empire”, while the second wave “took place in the 13th century, when German Jews allegedly migrated into monolingual Slavic lands and rapidly reproduced via a ‘demographic miracle’”. That is, however, an inaccurate representation of most historical sources, which attribute the biggest wave of eastward migration from Germanic-speaking lands to the 1300s, or the 14^th century, particularly to the second half of that century, when, in the wake of the Black Death, the Jews of Western Europe came under attack from their Gentile neighbors, which many Jews escaping prosecution in what is now Poland, Ukraine, and Lithuania, which were considerably less affected by the plague. The 13^th century, on the contrary, was relatively peaceful for the Western European Jews, a temporary respite between the persecutions that had resulted from the First and Second Crusades and the persecutions to come in the wake of the Black Death. In the second half of the 13^th century especially, the vector of Jewish migration went westward more than eastward: after a massive—and well-documented—destruction of the Jewish Quarter in Kiev in 1240 at the hands of the Mongols, individual surviving Jewish merchants dispersed westward, though there is little historical evidence of the Kiev Jewish community as a whole resettling elsewhere.

Further down on the same page in Das et al., we read: “some of the Turkic Khazar rulers and the numerous Eastern Slavs in the Khazar Empire converted to Judaism”. However, the issue of whether the bulk of the Khazarian population, both the Turkic-speaking majority and Slavic-speaking minority, converted to Judaism remains highly controversial. The Judaic conversion of the originally pagan Khazars appears to have happened “top down”, with the Khazar elite converting to Judaism. But whether other social classes followed suit is unclear (cf. Golden 2007a, b).

Yet, what I find most peculiar is the way that Das et al. write of (present-day) northeast Turkey, the Khazar Khanate, “Ukrainian and Sorbian (in the eastern German lands)” as the “geographical origins for Yiddish and [Ashkenazi Jews]” as if these terms refer to the same time and place. This could not be further from the truth. The geographical extent of the Khazar Khanate stopped at the Great Caucasus Mountains, an imposing geographical feature that served as a geopolitical boundary throughout most of the known human history; even today, the southern border of the Russian Federation follows the crest of the formidable range. No historical map of the Khazar Khanate that I am aware of shows it as extending to what is now (NE) Turkey. It is true that the Khazar Empire extended as far as Kiev, present-day capital of Ukraine, but one can hardly speak of “Ukraine” or “Ukrainians” as such before the 17^th century, long after the fall of the Khazar Empire (see Plohy 2015 for a detailed discussion). In the relevant time period, Kiev was the center of the Kievan Rus’. It is therefore just as appropriate to speak of Russian as Ukrainian roots of Ashkenazi Jewry. Still, Eastern Slavs constituted a minority within the Khazar Khanate. Finally, Sorbian-speaking lands were situated in what is now eastern Germany, not far from today’s Dresden, nearly 900 miles west of Kiev, over 1600 miles west of the former Khazar lands, and over 2000 miles west of the area in NE Turkey, where Das et al. locate the “primeval villages” of the Ashkenazi Jews.

Considering all this confusion in time and place, as well as the authors’ peculiar use of terminology, it is not easy to identify what exactly they claim. As far as I can tell from putting together information in the article itself and in the diagram on page 38, which is supposed to provide a summary of the historical picture that Das et al. reconstruct, they claim the following: the roots of Askenazi Jews and of Yiddish are in (what is now) northeastern Turkey, where “Irano-Turko-Slavic merchants” who were Jewish (Jews supposedly had a trade monopoly on the Silk Road; cf. page 5) “invented” a “secret language” that only they would understand. Linguistically, this language had no Germanic elements to begin with; Das et al. state that only later did it acquire some Germanic (or even “Germanoid”; cf. page 19) lexicon. It would indeed be most peculiar if “Irano-Turko-Slavic merchants” in what was then a predominantly Greek-speaking part of the Eastern Roman Empire (until the arrival of the Seljuks some 200 years later, which finally brought with them a Turkic language) were to “invent” a language that was thoroughly Germanic in nature. Yet Das et al. actually state that the “Irano-Turko-Slavic merchants” “invented” an East Slavic language. I also have a problem with the use of the term invented, as it makes it sound as if Yiddish is not a natural language (in the technical sense); there is, however, no evidence that Yiddish is a constructed language, like Esperanto or Klingon, let alone an argot. But let’s go back to Das et al.’s reconstruction of history. In the 9^th century (some or all of these) “Irano-Turko-Slavic” Jews “began settling in Western and Eastern Slavic lands, [where] Yiddish went through a relexification process, i.e., replacing the Eastern Slavic and the newly acquired Sorbian vocabularies with a German vocabulary while keeping the original grammar and sound system intact” (page 5). Why the Jews would introduce German(ic) vocabulary into their language if they settled in “Western and Eastern Slavic lands” remains a mystery. To be sure, there were German-speaking communities sprinkled all over the Slavic-speaking lands, and Germans were generally associated with the more urban and more prestigious social class; still, Yiddish has considerably more German-derived vocabulary than any West or East Slavic language—a fact that Das et al. offer no explanation for.

It seems to me that Das et al. end up with this rather nonsensical scenario simply to bypass Germany and thus to dispute the consensus “Rhineland hypothesis”. If they were to say explicitly that the German influences occurred in or after the 9^th century due to these ex-“Irano-Turko-Slavic” Jews from today’s Turkey (then part of the Eastern Roman Empire) resettling in Germany, it would reduce their proposal to a mere prequel to the “Rhineland hypothesis”, not an alternative theory. Whether any Jews migrated from present-day Turkey to Sorbian-, Czech-, or German-speaking lands in the 9^th century, as depicted in Das et al.’s summarizing diagram (page 38), they must have eventually made their way to Eastern Europe—Poland, Ukraine, Belarus, Lithuania, and later Russia—just as the proponents of the “Rhineland hypothesis” claim. Thus, even if the hypothesized Iranian-Jewish migration in the 9^th century took place (a claim whose validity I have serious reasons to doubt, as I will discuss below), Das et al. make no earth-shattering discoveries, do not contradict the consensus view, nor offer any solution to the problem of the Ashkenazi Jewish “demographic miracle” (see van Straten 2007 for a thorough discussion).

It is also important to note that the research offered by Das et al., as well as the earlier works by Paul Wexler and Eran Elhaik, have been taken to challenge the historical, cultural, or genetic connection of Ashkenazi Jews to the Land of Israel. If read carefully, however, their article does not make this claim nor does it offer grounds for dissociating Ashkenazi Jewry from ancient Israelites. Even if we assume that Das et al. are correct in their story of “Irano-Turko-Slavic” Jews having moved to German- or Sorbian-speaking lands, with subsequent mass migration further eastwards giving rise to Eastern European Ashkenazi Jewry, we have to ask where those “Irano-Turko-Slavic” Jews came from in the first place. I do not think that Das  et al. would dispute that a substantial number of Jews remained in Iran and the Fertile Crescent after the Babylonian exile. In fact, they explicitly claim that “already by the 1st century, most of the Jews in the world resided in the Iranian Empire” (page 5). While they claim that their “Irano-Turko-Slavic” Jews were ethnic Iranian, Turkic, or Slavic peoples who adopted Judaism, it possible that they were descendants of these ancient exiles who adopted local languages. The only way to distinguish between these possibilities is by a careful examination of genetic evidence, but I do not think that Das et al. meet the burden of proof there, to which I return below. Thus, even if Das et al. are correct, the Jewish traders from the Silk Road would be merely a “stop over” on what would turn out to be a more circuitous route from the Land of Israel to Germany to Eastern Europe.

But is the story of Ashkenazi Jews, as described by Das et al., correct? Did the migration route of the Jews from the Land of Israel to Germany take place via the Roman Empire (as most historians suggest) or did it take a detour via Iran and Turkey? Hopefully, genetic findings would be able to distinguish those two hypotheses. In particular, geneticists would have to figure out how much admixture from Iranian, Turkic, or Slavic peoples can be found in Ashkenazi Jewish gene pool (and how much admixture from Italians, for example), what the nature of that admixture is (e.g. did it come from both genders equally or predominantly from men or women?), and most crucially when this admixture has occurred. While I am not qualified to evaluate the genetic methodology and claims in Das et al., several geneticists I have spoken with were quite skeptical about their genetic findings. In particular, they point out that the GPS technique used in Das et al. can “diagnose” only relatively recent admixture (i.e. not admixture from “primeval” groups). Also, the entire research program examining the extent of the Khazar admixture among different Jewish populations runs into a serious problem of the lack of present-day direct and easily identifiable descendants of the Khazars. Simply put, who among living peoples should the Jewish genomes be matched to? Elhaik has used Caucasian groups, such as Armenians, as a proxy for Khazarians of yesteryear. In an earlier post, I reviewed Razib Khan’s eminently sensible critique of this approach. Essentially, other research has shown that Armenians are close to all Jews, not only Ashkenazi Jews, for whom such Khazarian connection has been claimed, as well as to non-Jewish peoples of the Fertile Crescent and the Near East such as Kurds and Turks. Therefore, to the extent that Ashkenazi Jews show some genetic similarity with Armenians, this finding can be attributed to an areal contact in the ancient Fertile Crescent rather than to the Khazars.

However, even if subsequent (and hopefully more careful) research shows that Ashkenazi Jews trace their physical descent to Turkey, Khazaria, Ukraine, or Sorbian lands—make your pick!—this issue is irrelevant to the question of the origin and development of their language, Yiddish. One might argue that this issue is unimportant for an article published in Genome Biology and Evolution. Yet, the authors themselves focus on Yiddish as much as the genetic issues, with the phrase the Yiddish language opening the abstract, where the word Yiddish appears three times in the first three sentences, and 87 times in the entire paper. So what is the relevance of Yiddish to genomics? Das et al. make an explicit assumption of “the strong relationship between geography, genetics, and languages […], implying that the geographical origin of Yiddish would correspond to that of Yiddish speakers”, an assumption that is utterly unjustified. While a relationship between languages and genes often clearly exists, human linguistic history is rife with examples of peoples whose physical descent (i.e. their genes) and their languages do not match at all (see my earlier posts here, here, and here). Among such discrepancies are most Native North American peoples: the majority of whom speak English but are not genetically related to Anglo-Saxons, Scandinavians, and/or Celts. Similarly, African-Americans carry genes of their West African ancestors despite speaking English and no West African languages. Likewise, most indigenous peoples of Siberia and the Russian Far North speak Russian, but are not genetically Slavs. In Africa, Pygmies speak Bantu languages yet are genetically very distinctive; in contrast, Hadza and Sandawe show more genetic similarities to the Bantus and the Pygmies, yet speak languages that were classified as Khoisan. (More recently, this classification has been challenged, yet nobody to the best of my knowledge claims that Hadza and Sandawe languages are Bantu or more generally Niger-Congo.) Finns, Saami, and Hungarians too illustrate the non-correlation of genes and language. The list can be easily continued.

It is therefore impossible to claim that wherever Ashkenazi Jews come from genetically, the origins of Yiddish are necessarily to be found in the same locale. What’s more, the claim of Das et al. that whatever language their “Irano-Turko-Slavic” Jewish merchants spoke was the precursor of Yiddish does not hold water. According to Das et al. themselves, that language had no German(ic) elements whatsoever. Any German or “Germanoid” vocabulary in modern Yiddish is to be attributed to a later relexification (i.e. massive lexicon replacement), they claim. The grammar of modern Yiddish, they maintain, is thoroughly and unequivocally Slavic (with elements of Iranian and Turkic, though they never cite any examples of such grammatical elements). Crucially for them, Yiddish grammar is not, and has never been, Germanic in nature. Why then do they call the language of “Irano-Turko-Slavic” Jewish merchants “Yiddish” since, according to their own claims, it was a completely different language? This labeling makes as much sense as calling English a West African language just because some of its native speakers trace physical descent to West Africa, or calling Russian a Paleo-Siberian language because some of its native speakers trace physical descent to Paleo-Siberian ethnolinguistic groups (e.g. Itelmen). A more reasonable claim would be that the “Irano-Turko-Slavic” Jewish merchants, to the extent that they existed and migrated en mass to Germany or Slavic-speaking lands, spoke one language in their original homeland and then underwent a language shift, much like African-Americans or Siberian peoples did.

This brings me to the most fatal, from a linguist’s perspective, flaw of the Das et al. article: their claim that “Yiddish grammar and phonology are Slavic (with some Irano-Turkic input) and only some of the lexicon is German” (page 21). This is a very odd claim indeed, and it is completely unsubstantiated in this article, except for a reference to a book chapter by one of the article’s authors, Paul Wexler (Wexler 2012). As this is the crucial point, on which the legitimacy of the entire argument about the origins of Yiddish depends, at least some evidence for the validity of the claim needs to be presented in the article, not buried in some semi-obscure publication (not available at Stanford library, Google Books, or Amazon). In his other works, Wexler has presented arguments for the Slavic nature of Yiddish grammar, but they are limited mostly to loan derivational morphology, calqued grammatical morphemes, and phonological patterns, which can be borrowed from one language into another. The grammatical system of Yiddish, however, looks far more Germanic than Slavic: Yiddish has definite and indefinite articles, which express gender and case; its case system is Germanic too (none of the peculiarities of Slavic case system, like the Genitive of Negation, are present in Yiddish); and its word order is subject to rules like Verb-Second, not information structure. While Yiddish borrowed the Slavic multiple wh-fronting pattern (e.g. “Who what has bought?”), it retains the Germanic pattern where only one wh-expression is fronted (cf. Diesing 2003). Similarly, as shown in detail by Peter Arkadiev (2015), even though Yiddish calqued some aspectual prefixes (e.g. cumulative on– by analogy with the Slavic na-), the overall aspectual system looks Germanic rather than Slavic. In my own research (Pereltsvaig in press), I have shown how the extension of the Verb-Second pattern from main to embedded clauses might have resulted from Slavic influence on a Germanic language; the same data cannot be explained as a result of Germanic influence on Slavic. The burden is thus on the advocates of the Slavic origin of Yiddish to show how its grammar can be analyzed by applying Slavic models. Short of that, the argument is not particularly convincing.

Overall, I think that Das et al. manage to muddy the waters—by using sloppy historical-geographical nomenclature, imprecise terminology, and references to authors’ own earlier works, which few readers would bother to track down—to make an impression that there is a viable alternative to the consensus Rhineland hypothesis, one that indiscriminate readers could use to make ideological statements with far-reaching geopolitical consequences. It is bad enough when solid science gives rise to bad ideological misuses, but when bad science feeds such political spin-offs, the moral burden is both on the ideologues and the scientists themselves.

References:

Arkadiev, Peter (2015) Areal’naya tipologiya prefiksal’nogo perfektiva. Moscow: Jazyki slavjanskoj kultury.

Das, Ranajit; Paul Wexler, Mehdi Pirooznia, and Eran Elhaik (2016) Localizing Ashkenazic Jews to primeval villages in the ancient Iranian lands of Ashkenaz. Genome Biology and Evolution Advance.

Diesing, Molly (2003) On the Nature of Multiple Fronting in Yiddish. In: Cedric Boeckx and Kleanthes Grohmann (eds.) Multiple Wh-fronting. Amsterdam: John Benjamins. Pp. 51-76.

Golden, Peter B. (2007a) Khazar Studies: Achievements and Perspectives. In: Peter B. Golden, Haggai Ben-Shammai, and András Róna-Tas (eds.) The World of the Khazars: New Perspectives. Handbook of Oriental Studies 17. BRILL. Pp. 7–57.

Golden, Peter B. (2007b) The Conversion of the Khazars to Judaism. In: Peter B. Golden, Haggai Ben-Shammai, and András Róna-Tas (eds.) The World of the Khazars: New Perspectives. Handbook of Oriental Studies 17. BRILL. Pp. 123-162.

Pereltsvaig, Asya (in press) On Slavic-influenced Syntactic Changes in Yiddish: A Parametric Account. In: Yohei Oseki et al. (eds.) Formal Approaches to Slavic Linguistics. The NYU Meeting.

Plohy, Serhii (2015) The Gates of Europe: A History of Ukraine. New York: Basic Books.

Van Straten, Jits (2007) Early Modern Polish Jewry The Rhineland Hypothesis Revisited. Historical Methods: A Journal of Quantitative and Interdisciplinary History 40(1): 39-50.

Wexler, Paul (2012) Relexification in Yiddish: a Slavic language masquerading as a High German dialect? In: Danylenko A, and Vakulenko SH (eds.) Studien zu Sprache, Literatur und Kultur bei den Slaven: Gedenkschrift für George Y. Shevelov aus Anlass seines 100. Geburtstages und 10. Todestages. München, Berlin: Verlag Otto Sagner. Pp. 212-230.

The post Turkey, Shmurkey! — A Response to Das et al. (2016) appeared first on Languages Of The World.

[Thanks to Boris Denisov and Martin Lewis for helpful discussions of these issues.]

A recent question from a student about just how religious Russians really are has sent me to look for statistics on this issue. As sociologists of religion know, it is not easy to measure religiosity in any country, as people often lie in response to survey questions about their religious beliefs and attendance. Since religion is not part of the Russian population census data, the best statistics could be gathered from sociological surveys conducted by Levada Center, but although it is considered the best sociological research organization in Russia, some Russian demographers have suggested that I take their findings with a grain of salt. With that in mind, let’s consider Levada Center’s figures.

According to the Center’s director Lev Gudkov, religiosity among the Russians (citizens of Russia, not ethnic Russians) is on the rise: according to the first sociological survey conducted on this matter in the late Soviet years, 16-19% of the population characterized themselves as “believers” (in Russian, верующие), whereas the corresponding figure in 2014 was 77%. Only 19% characterize themselves as non-believers. According to the first map in the National Geographic article “The World’s Newest Major Religion: No Religion” by Gabe Bullard, the number of non-religious people in Russia shrank by more than 5% between 2005-2015. Moreover, as the second map in that article indicates, that shrinking of non-religious population is due mostly to the growth of Christian rather than Muslim population.

However, the relatively high proportion of “believers” needs to be understood in context of what it means to be a “believer” in Russia. A recent sociological survey conducted by the All-Russia Public Opinion Research Center (VTsIOM) has shown that the growth in the number of self-identified believers is accompanied by increasingly more popular beliefs in phenomena associated with religion. In this poll, 50% of the respondents said they believe in religious miracles (compared to 32% in 1991), 46% of the respondents believe in life after death (compared to 33% in 1991), and 40% believe in the devil and hell (compared to 25% in 1991). In response to a question as to “whether human life is predestined by higher forces”, 48% of those polled said that it is (compared to 25% in 1991), and only 26% said it is not (compared to 45% in 1991).

Yet, a substantial number of self-identified believers in Russia do not adopt all beliefs and practices of their religion. In the interview cited above, Gudkov explained (translation from Russian here and below is mine):

“On the surface, the number of believers grew in one generation manifold, but what is meant by that concept is more of an ethno-religious identity. Only 4-7% adhere all the required observances, and this number doesn’t change. And about 40% of people who call themselves Orthodox doubt the existence of God, Last Judgement, possibility of Salvation.”

Of the 77% believers, the distribution across different faiths corresponds to the ethnic groups. For example, most of the 7% who self-identify as Muslims come from traditionally Muslim ethnic groups from the Middle Volga region (Tatars, Bashkirs) and North Caucasus (Chechens, Ingush, various ethnic groups in Dagestan). Similarly, the 1% who identify as Jewish by religion are also Jewish by ethnic group (a designation that is included in the census data). Only about 1% of Russia’s population self-identify as Catholics or Protestants.

The relatively high figure of self-identified believers who do not adopt all the articles of their faith—even the existence of God!—mentioned by Gudkov (see above) is matched by a relatively high proportion of non-observance (or rare observance) of religious practices. According to a 2013 sociological survey, only 14% of the population attend religious services at least once a month; this figure is down from 20% in 2007. Only 16% attend religious services only once a year, 17% go several times a year, and 13% do so once in a few years; 35% of respondents admitted to never attending religious services at all.

Even fewer people are taking part in the sacraments: 62% of those who self-identify as Orthodox or Catholics never go to Communion, only 14% go to Communion at least once a year, while 22% do so less than once a year. Based on these figures, deputy director of Levada Center Alexei Grazhdankin said that:

“14% is the approximate number of people who are true believers rather than identifying themselves as belonging to this or that religion based on cultural identity, without having ties to the church. The concept of spiritual-religious identity is much broader than having stable and well-defined religious views. But even that number may be considered too high. Those who regularly participate in the life of their religious community, maintain regular contacts with other believers and conduct their lives in accordance with confessional requirements constitute about five-six percent.”

A recent study, conducted in March 2016, supports the view that while the majority of Russian citizens identify themselves as “believers”, very few are prepared to follow the stricter religious observances. On the eve of Shrovetide (in Russian, Масленница), a carnival-like celebration immediately preceding the 7-week-long fast of Lent, Levada Center conducted a study of what people are planning to do for both the Shrovetide and the fasting period. According to their findings, only 11% of the Russian citizens were not planning to do anything special for Shrovetide, while the majority planned to celebrate it with family and friends (30%) or in public celebrations (23%). Seven out of 10 respondents were planning to bake the traditional pancakes (in Russian, bliny), consumed with copious amounts of butter, sour cream, and sometimes caviar. A quarter of the respondents planned to eat meat on Shrovetide.

But when it comes to a stricter observance, the 7-week Lent fast, very few Russians were planning to stick to its observance. Three out of four people planned to eat as they normally would. Only 16% were going to make partial changes to their normal diet and routine, and 4% planned to fast only during the last week of the fast. Merely 3% of respondents said that they will be observing the fast fully during the entire 7-week period. While 1 in 3 respondents were prepared to give up alcohol for the duration of the fast, but only 1 in 5 were ready to temporarily give up smoking or sex. One in four could abstain from entertainment but only 13% were prepared to curb their business or professional lives.

In accordance with the claims cited above that religion is a matter of cultural and/or ethnic identity rather than faith, many people who do not identify themselves as Christians were planning to celebrate Shrovetide alongside their Orthodox compatriots. Thus, a higher proportion of atheists than of the Orthodox believers were planning to eat meat (27% vs. 24%) or to participate in public Shrovetide celebrations (28% vs. 23%). Moreover, even when it comes to less conspicuous practices such as baking pancakes or celebrating Shrovetide with family and friends, the proportion of the atheists who would do that is almost as high as among the Orthodox. Even a sizeable minority of believers from other faiths would bake pancakes (32%), participate in public Shrovetide celebrations (11%), or celebrate with family and friends (10%). As for Lent, the same proportion of atheists and of the Orthodox, only 2%, would observe the fasting requirements fully for the entire period.

Russian religious activist Dmitry Tsorionov, known under pseudonym Enteo, ascribes this shallow religiosity to “70 years of the communist yoke, when the government fought against the church and the faith”, while also comparing it to the situation found in “other developed countries”. One way or another, Russian society can be best characterized as only nominally Orthodox. It would be interesting to look more closely into the religiosity levels among members of other faiths, particularly among Russia’s Muslims, which I suspect is much higher than among those who self-identify as Orthodox.

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