The 2015 Turkish Election: The Unclear Economic Dimension

Turkey 2015 Vote Parties MapThe 2015 Turkish General Election struck many observers as highly significant, due mainly to the drop in support for the previously dominant Justice and Development Party (AKP), closely associated with president and former prime minister Recep Tayyip Erdoğan. Although the AKP remains the largest party in the Turkish parliament, it gained only 41 percent of the total vote, thwarting Erdoğan’s plans for strengthening the presidency. To some extent, the election can be seen as a referendum on Erdoğan himself. Highly popular a decade ago, when Turkey’s economy was growing strongly and the country enjoyed peaceful relations with most of its neighbors, Erdoğan has seen his support drop as the economy has faltered, as regional tensions have intensified, and as Turkish democratic institutions have been partially undermined.

As the first map, from the invaluable website Electoral Geography 2.0, shows, the moderately Islamist, “center-right to right-wing” (according to the Wikipedia) AKP triumphed across most of Anatolia, while the “center-left,” moderately nationalistic, “Kemalist” Republican People’s Party (CHP) came in first in most of European Turkey and along most of the greater Aegean coastal region. The new, left-wing Peoples’ Democratic Party (HDP), closely associated with Kurdish nationalism, did relatively well, taking a majority of the votes in the Kurdish-speaking southeast. It received fewer votes overall, however, than the extremely nationalistic Nationalist Movement Party (MHP): 13 percent for the HDP vs. 16 percent for the MHP. But the MHP triumphed only in a few districts concentrated in the south-central part of the country, as its electoral support is much more spatially dispersed than that of the HDP.

Turkey Income by Province MapEthnic and religious factors obviously played a large role in this election, as will be examined more closely in subsequent posts. For now, however, I will concentrate on economic factors. Can we find any geographical correlations between voting patterns and economic conditions? To address this question, we must first find a map that shows some measure of the economic ranking of the provinces of Turkey. Doing so, however, is not easy. A commonly reproduced Wikipedia map that purports to show “per capita income by province in 2011” is not adequate. This map is incomplete, lacking a key, but more problematic is the patterns that it depicts, which seem to be inaccurate. It places Mardin Province in the southeast, for example, in the highest economic category, yet the Wikipedia itself describes this province as suffering from serious poverty, unemployment, and out-migration.

Turkey Socio-Economic Development MapThe best map of economic differentiation in Turkey that I have located come from an article entitled “Regional Disparities and Territorial Indicators in Turkey: Socio-Economic Development Index (SEDI)” by Metin ÖZASLAN, Bülent DINCER, and Hüseyin ÖZGÜR. This map shows generalized levels of socio-economic development; note that I have remapped the original data with a different color scheme in order to emphasis disparities. The main pattern here is quite clear: western Turkey is much more prosperous than eastern and especially southeastern Turkey. Coastal areas also tend to be more developed that interior regions, although here the differences are not pronounced. More striking is the fact that the provinces containing Turkey’s largest cities, Istanbul, Ankara, Izmir, and Bursa, are all in the top category of socio-economic development.

Turkey 2015 AKP Vote MapIn comparing the map of the electoral showing of the AKP (Erdoğan’s party) with that of socio-economic development, only one pattern stands out: the impoverished southeast voted heavily for the left-wing Peoples’ Democratic Party (HDP). In some respects there is noting unusual here, as poor areas often vote for economically leftist parties. But the Turkish HDP is also noted for its culturally left positions, positions that might not be expected to gain widespread support in a mostly rural, peripheral portion of a developing country. Here, I think, one must look to the political aspirations of the Tuerkey Development Vote MapKurdish people, as will be explored in a subsequent post. Otherwise, the 2015 Turkish voting patterns do not correlate strongly with those of socio-economic conditions. Some very poor provinces voted strongly for the AKP, such as Bayburt, while some wealthy provinces, such as Kocaeli, gave a plurality of their votes to the AKP. Intriguingly, the party’s highest level of support came from provinces in the middle of the socio-economic spectrum: Konya and Rize.

One problem with generalized socio-economic rankings is the fact that they do not capture recent changes and general developmental tendencies. Turkey, for example, has over the past 15 years seen the rise of several so-called Anatolian Tiger cities, which have surged ahead in economic production and productivity. These cities have been widely associated with Islamic values, which differentiate them from the older and Anatolian Tigers Maphistorically more secular Turkish industrial cities, such as Istanbul, Ankara, and Izmir. According to the Wikipedia article on the “Anatolian Tigers”:

Beyond their shared characteristics in an economical perspective, references have also been made, especially in international media, to different political connotations within the term, including by associating this capital with Islamic values or extending its whole under such definitions as “Islamic capital” or “green capital”. … A 2005 study by the European Stability Initiative that was focused on Kayseri uses the term “Islamic Calvinists” to define the entrepreneurs and their values.

Turkey AKP Vote Decline MapI have crudely mapped the most important of these “Anatolian Tigers” by highlighting the provinces in which they are located. Note that these provinces vary fairly widely in terms of their levels of socio-economic development. They also vary quite a bit in regard to their level of support for the AKP, although in general they did gave a higher percentage of their votes to Erdoğan’s party than did the “average” Turkish province. What I find most intriguing, however, is the fact that two of these “Tiger” provinces, Gaziantep and Kayseri, showed a major drop in support for the AKP between 2011 and 2015. Perhaps Turkey’s recent economic problems have played a role here. The AKP’s most precipitous drop in support, however, was found in the southeast, a phenomenon most closely linked to the emergence of the Kurdish-oriented Peoples’ Democratic Party.


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Xinjiang, China: Ethnicity and Economic Development

China GDP by Prefecture MapAn impressive map of China’s per capita GDP by prefecture, reposted here, appeared in late 2012 on the website Skyscraper City, posted by user “Chrissib” Cicerone.  According to the map, the two poorest parts of China are in southern Gansu province, an area demographically dominated by Han Chinese, and in southwestern Xinjiang, an area demographically dominated by Uighurs, a Turkic-speaking, Sunni Muslim people.

As noted in the previous GeoNote, the level of economic development in Xinjiang as a whole is slightly lower than the Chinese average, as measured by per capita GDP. But as Chrissib’s map shows, Xinjiang shows striking disparities in its own regional economic patterns. As a comparison of a detail of his map with a Wikipedia map of ethnicity in Xinjiang shows, areas dominated by Han Chinese have much higher levels of economic productivity than those dominated by Uighurs. Also essential to note is the fact that the Han Chinese domination of eastern Xinjiang largely stems from relatively recent immigration to the region, a process much resented by Uighur activists.

Xinjiang GDP and Ethnicity mapChina is currently seeking to enhance the economic development of Xinjiang, along with the country’s other western regions. But as Preeti Bhattacharji explains in a recent article published by the Council on Foreign Relations, the project faces a number of ethnic issues:

Xinjiang’s wealth hinges on its vast mineral and oil deposits. In the early 1990s, Beijing decided to spur Xinjiang’s growth by creating special economic zones, subsidizing local cotton farmers, and overhauling its tax system. In August 1991, the Xinjiang government launched the Tarim Basin Project to increase agricultural output. During this period, Beijing invested in the region’s infrastructure, building massive projects like the Tarim Desert Highway and a rail link to western Xinjiang. In a 2000 article for the China Journal, Nicholas Bequelin of Human Rights Watch said these projects were designed to literally “bind Xinjiang more closely to the rest of the PRC.”


Ethnic tension is fanned by economic disparity: not only are the Han-dominated areas more productive, but the Han individuals tend to be wealthier than the Uighurs in Xinjiang. Some experts say the wage gap is the result of discriminatory hiring practices. The CECC reported in 2006 that the XPCC [Xinjiang Production and Construction Corps] reserved approximately 800 of 840 civil servant job openings for Han. This policy was changed in 2011, however, and the XPCC “left almost all positions unreserved by ethnicity.” But the 2011 CECC says both government and private sectors had discriminatory hiring practices against the Uighurs and also denied them religious rights such as observing Ramadan and allowing Muslim men to wear beards and women to wear veils.


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Regional Trends in Chinese Economic Development

China GDP by province growth 2011 mapA widely distributed China Briefing map shows per capita GDP gains by province* for 2011. As can be seen, all parts of China experienced rapid economic expansion in that year, but the more prosperous and productive coastal zone did not fare as well as many interior areas. The mineral-driven boom in Inner Mongolia is well known, but the rapid recent growth experienced in such provinces as Sichuan and Guizhou has not received as much attention in the international press. As several of these rapidly expanding areas are quite poor by Chinese standards —with Guizhou having China’s lowest per capita GDP—such patterns indicate a slight lessening of the country’s stark regional disparities.

IChina GDP ranking by province 2010 mapt remains to be seen, of course, whether such patterns will persist. When examined over the past several decades, a strikingly different map of regional development emerges. To illustrate such differences, I have made several maps of the relative economic standing of Chinese provinces, using Wikipedia data. The first map shows per capita GDP ranking in 2010. Here blue provinces have higher than average figures and red provinces lower than average figures, with the two richest areas (Shanghai and Beijing) shown in dark blue, the third and fourth richest is a somewhat lighter shade of blue, and so on. On this map, the economic development of the coastal zone is clearly evident, as is the low economic productivity of the greater southwest.

China GDP ranking by province 1978 mapThe second map portrays the country in the same manner for 1978, just as China’s economic transformation was beginning. (Note that 29 rather 31 entities are mapped here, as at the time Chongqing was part of Sichuan, whereas data for Hainan were not tabulated). The economic pattern at the time was strikingly different from that of 2010; in the late 1970s, the northeast (Manchuria) was the clear economic leader, while much of the far west, including the entire Tibetan Plateau, ranked at a relatively high level.

China Change in GDP by Province MapThe final map shows changes in relative rankings over the same period. Three province-level municipalities, Beijing, Shanghai, and Tianjin, remained the same, occupying the top three positions in both years. Xinjiang in the northwest also retained the same ranking, remaining in position number 19. Other regions show significant changes. The coast surged ahead, particularly Fujian, Zhejiang, and Shandong, as did mineral-rich Inner Mongolia. The rust-belt zone of Manchuria, on the other hand, dropped significantly. An even greater drop, however, is seen in the Tibetan Plateau (Tibet proper and Qinghai) and the adjoining province of Gansu. Tibet itself dropped from the 9th position to the 28th.


*Strictly speaking, the units in question are province-level administrative divisions, including autonomous regions and direct-controlled municipalities. China’s Special Administrative Regions (Hong Kong and Macau) are not included.


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Mappery and the Problems with “True” and “Real” Maps

"Real" Map of PakistanThe useful website Mappery “was created for map enthusiasts to find, explore, and discuss great maps. Anyone can contribute maps, comments, and ratings to the site.” The site contains numerous maps, and is certainly worth exploring. Thankfully, users seldom exploit the site for propagandistic purposes. Mappery does contain, however, a few problematic political maps, such as the “Real Map of South Asia” posted here. This map not only appends all of Kashmir to Pakistan, a common and understandable maneuver, but also includes other parts of India in a future enlarged Pakistan.

Maps of "greater Pakistan"Such mapping is part of an established “greater Pakistan” cartographic genre, a few examples of which are included in the second illustration posted here. Some of these maps entail merely the hoped-for annexation of India’s portion of Kashmir, whereas others call for the addition of part or all of Afghanistan, as well as part or all of India and even Sri Lanka. Fantasy knows few bounds when it comes to nationalistic mapping. Such maps can be found on anti-Pakistan as well as pro-Pakistan webpages, as they are sometimes used in India to incite fears about Pakistani expansionism.

"True" Map of AzerbaijanNot all maps that purport to show “real” or “true” geopolitical conditions, however, necessarily fall into the propaganda category.  Mappery’s  “True Map of Azerbaijan,” for example, shows the area that Azerbaijan does actually control, rather than the area that its government, and the internationally community, regards as its legitimate territory. Still, it is impossible to avoid controversy here. Note that the map regards Nagorno-Karabakh as simply part of Armenia, whereas the Wikipedia describes it is “a de facto independent but unrecognized state.” The “true” situation of Nagorno-Karabakh, however, is actually highly ambiguous, and hence cannot nagorno-karabakh_occupation_mapeasily be captured in any mapping scheme.



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Remapping Poverty in India

Indian Households without Assets mapData Stories (“… on India, One Chart at a Time”) recently published some intriguing maps and other visualizations of poverty and wealth in India. Its poverty map, posted here, shows households that “don’t own any of the assets listed on the census forms – that means no phone, no TV or radio, and no vehicle of any kind…,” a category that encompasses 18 percent of Indian households nationwide. This map deviates from more conventional maps of poverty in India in several regards (see the Pinterest map posted below). A number of districts in Kashmir in the north and in India’s far northeast (particularly in Nagaland) show much more deprivation on the Data Stories assets map than on the Pinterest poverty-line map. Uttar Pradesh in north-central India, on the other hand, appears much better off on the assets map than on the poverty-line map, as do some districts in northern Tamil Nadu (in the southeast).

Indian Poverty MapParticularly striking on the Data Stories map is the depiction of a belt of extreme poverty in west-central India, where the states of Gujarat, Rajasthan, Madhya Pradesh, and Maharashtra converge, an area near some of India’s most prosperous cities. The explanation of this belt, however, is clear, as it closely tracks the territory of the Bhils, a so-called tribal (or Adivasi) people some twelve-million strong. In several parts oBhil People India MAPf India, the map of “asset-less” household” correlates relatively well with Adivasi populations.


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The New York Times’ Flubbed China Cartograms

NY Times China Population CartogramAn interesting story in today’s (April 9) New York Times—“Hello, Cambodia: Wary of Events in China, Foreign Investors Head to the South”—is illustrated in the print edition with two striking cartograms of eastern Asia, one of which shows population and the other economic output. The cartogram legends claims that “countries and Chinese provinces are sized according to population” and, respectively to “economic output.” Actually, they are not. On the population cartogram, for example, compare the sizes of Hong Kong and Taiwan with that of Thailand. Is Thailand shown as almost ten times larger than Hong Kong and almost three times the size of Taiwan, as an accurate depiction would have it? Hardly.


NY Times China Economic CartogramThe real problem with the maps, however, is the claim that Chinese provinces are also sized according to these metrics. In actuality, it appears that no efforts were made to depict China’s first-order internal divisions (which include autonomous regions and direct-controlled municipalities in addition to standard provinces) in the manner of a cartogram. If this had been done, China would not retain its familiar shape, as can immediately be seen on an actual population cartogram of the country, produced by Worldmapper. On an economic cartogram, the shape distortion would be even more pronounced, as production is concentrated in the coastal provinces. As the Economist map shows, the GDP of the Tibetan Autonomous Region is roughly equivalent to that of Malta.

WorldMapperChinaPopulationCartogramThe New York Times cartograms also seemingly imply that Hong Kong is an independent country, rather than a “special administrative region” of China.




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Egypt and the World Diesel Price Map

World Diesel Price MapThe price of fuel in Egypt, and especially that of diesel, has been featured in many recent news stories, owing to the perilous state of the Egyptian economy. As an April 1 article in Financial Times notes:

Egypt imports up to 70 per cent of its diesel, which it uses to fuel cars, farm equipment and power plants. In addition, it subsidises diesel to the tune of at least $1.5bn a month, draining the country’s already perilously low hard currency reserves. A spate of shortages in recent weeks has raised questions about Egypt’s ability to keep the lights on, feed its people and prop up its moribund economy in the coming months.

But Egypt is not the only country that subsidizes diesel. In fact, at US$ 0.32 per liter, diesel is expensive in Egypt compared to what it costs in some other countries. In Venezuela, Iran and Saudi Arabia, the corresponding figures are $0.013, $0.016 and $0.067 respectively. Those three countries, or course, are major oil exporters, unlike Egypt. Egypt is now a net importer of oil, although it does have abundant natural gas deposits. In no other net oil importer is the price of diesel even close to that found in Egypt. Although Sri Lanka appears on the map in the same color as Egypt, its diesel price is as at 0.66 US$ per liter.

As can be seen on the map, based on data from the World Economic Forum’s Travel and Tourism Competitiveness Report, diesel is generally expensive in the major industrialized countries and inexpensive in the major oil exporters. Oil-exporting Norway, however, has the world’s second highest price level, exceeded only by that of Turkey. Canada and especially the United States stand out for their relatively low prices. Prices vary greatly in Latin America and especially sub-Saharan Africa, which reflect governmental subsidies more than anything else.

I would like to post a world map of natural-gas prices, but I have not yet been able to find one, or the data necessary to construct my own.


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Mapping the Cell Phone Revolution

Mobile Telephone Subscriptions World MapIt is often noted that inexpensive cellular telephones have revolutionized communications across much of the world, especially in poor countries that lack landlines. Confirmation of this development is found in the World Economic Forum’s 2013 Travel and Tourism Competitiveness Report, which features detailed data tables for 140 countries. According to the report, 80 countries have more mobile telephone subscriptions than people. The United States, Canada, and France are not among them. Over most of the world, levels of economic development correlate poorly with cell phone subscription levels.

I have mapped the mobile telephone data to make the geographical patterns immediately evident. As can be seen, high subscription rates are found across much of the former Soviet Union and in the Arabian Peninsula, and more generally in Central and Eastern Europe and in South America. Hong Kong, however, has the highest figure (214.7), followed by Saudi Arabia, Panama, Montenegro, Russia, and Suriname. Such extremely high subscription rates are likely linked to the widespread use of inexpensive disposable phones. In Russia, moreover, people often keep different phones or, more commonly,  different SIM (subscriber identity module) cards, for personal and business purposes, and many purchase local phones when traveling.

Cell phone subscription levels are lower than average across much of Asia and Africa. Yet even in countries as poor as Mali and Zimbabwe, the figures are still relatively high, at 68 and 72 subscriptions per 100 people respectively. In only two countries, Burundi and Ethiopia, is the figure below 25 percent, although several unmapped countries, such as DR Congo and Central African Republic, could well have lower rates.

Mobile Boradband Subscriptions World MapThe situation is quite different in regard to mobile broadband subscriptions, as can be seen in the second map. Here subscription rates range from negligible (fewer than 0.1 per 100 people) across most of Africa and South Asia to a high of 114 in Singapore. South Korea and Japan also boast more broadband mobile subscriptions than people. It is significant that Germany, France, and Italy lag behind Poland, the Czech Republic, and Russia in this regard. The high figure for Ghana is also noteworthy.

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Some Strange Fantasy Maps

Drenai MapThe world of science fiction and fantasy is an excellent place to find strange maps, and few are stranger than the Drenai map posted here. David Gemmell’s Drenai series has prompted a number of fans to map the world depicted in the novels. Most are rather straightforward pictures of the author’s fantasy realm. One amateur cartographer, however, decided to map the world on the basis of the Earth analogues of the various societies portrayed in the series. To do this, he has smashed together the British Isles, France, North Africa, Iberia, Mongolia, Korea, and eastern China. Such a maneuver is odd enough, but the really bizarre feature is the doubling of eastern China. Note how the southeastern subcontinent is formed by two mirror images.

Tetrakon MapMaps used in fantasy game-playing can be quite intricate and sophisticated. Cartographers working in this genre, however, can also get carried away. The political map of Tetrakon posted here is impressively large, as can be gathered from the detail that I have also posted. The map looks fairly realistic at first glance, owing in part to fractal geometry; the use of self-similar patterns allows geographical features to remain distinct as one zooms in on any particular place. The problem is that in the real world, many coastlines are relatively smooth Tetrakon Map detailand straight. As a result, the Tetrakon map has a jarring appearance, as all of the land/sea patterns here are much the same.

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Mapping the 2013 Swiss Referendum: Executive Compensation

Switzerland Executive Compensation Election Map2In the Swiss referendum of 2013, voters overwhelming approved a measure to limit executive compensation. Despite the fact that opponents outspent proponents 40 fold, and despite warning that the move would “undermine the country’s investor-friendly image,” 68 percent of voters approved the initiative.

As specified by the Wikipedia, the measure will:

  • require an annual vote by shareholders for the president and other members of the management board of directors, members of the remuneration committee, and any advisory board and executive officers of the organisation.
  • require the articles of association to include bonus schemes and pay plans for directors and executive officers, any loans granted to such employees, the number of mandates outside the organisation, and the duration of employment contracts of executive officers.
  • ban advance and severance packages.
  • ban corporate proxy and the representation of shareholders by depository banks.
  • requires pension funds to disclose the way it votes, and to vote in the interests of pension policyholders.

The geographical patterns revealed by the vote on this measure are not pronounced. All parts of the country voted in favor the measure, although support varied from tepid to overwhelming, as can be seen on the map. But unlike the family law issue, spatial generalization about the voting pattern are not easy to make, whether in regard to language or the degree of urbanization. Nor is there any correlation with religion, as can be seen in the map below. At the canton level, the central cantons that formed the original core of the Swiss state were slightly less inclined to support the measure than most of the rest of the country, but that is about all that one can conclude.

Switzerland Executive Compensation Election Map1This Electoral Politics map does, however, depict differences at the district level, unlike yesterday’s map of the family-law measure, which showed only the canton level. Here we can see profound disparities across Bern, Switzerland’s second-most populous canton. The French-speaking area in the north, Bernese Jura, overwhelmingly supported the measure, whereas Obersimmental-Saanen in the southwest barely gave it a majority of its votes. Intriguingly, Obersimmental-Saanen includes Gstaad, described by the Wikipedia as “a major ski resort and a popular destination amongst high-class society and the international Jet set” that also hosts “some of the world’s most prestigious and academically intensive boarding schools, such as Institute Le Rosey and Gstaad International School.”

Switzerland Bern Religion MapIn central Switzerland, Obwalden canton also saw a close contest. This area is noted for its fiscal conservatism. As the Wikipedia states, “In 2007 Obwalden replaced the former degressive income tax (lower tax rates for higher incomes) with a flat 1.8% income tax, which is the lowest in the country.”




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Geographical Patterns in the 2013 Swiss Election, Part I

Swiss Family Law 2013 Election MapA three-part referendum held in Switzerland in early March received minimal press attention. Some media reports noted the passage of a measure to restrict executive compensation, but the family policy initiative was virtually ignored, as was the one on land-use planning. Today’s post briefly considers the family policy issue, whereas tomorrow’s will look at the executive compensation measure.

The Swiss election guide description of the family policy measure is not very specific:

Do you want the federal order of 15 June 2012 taken on family policy? The federal order would add an amendment to the federal constitution to require the federal government to take account of the needs of the family when performing its duties, and to work with the cantons to promote balance between family and work and to create more day-care facilities to complement schools.

Even though the measure sounds rather indistinct, it provoked strong reactions, with some parts of the country overwhelmingly favoring it, and others strongly opposing it. The general patterns are clear. I have modified the Electoral Politics map of the election results to highlight them. As can be seen on the first map, the French- and Italian-speaking areas of the country in general favored the initiative strongly, which received 54 percent of the vote nationwide. The more rural parts of the German-speaking zone, as well as the Romansh-speaking areas, opposed it. Such patterns would probably be even more clear-cut if the map showed voting behavior below the canton-level. I would not be surprised, for example, if the French-speaking part of Bern, Bernese Jura, actually voted for the measure, although the map would seeming indicate that it voted against it.  By the same token, I would not be surprised if the eastern, German-speaking portion of Valais actually voted against it.

Swiss Family Law 2013 Election Map2Generalization can also be made about the areas that voted strongly against the measure. The core “no” area in the center of the country corresponds closely with the original nucleolus of the Swiss state in the 14th century. The measure was most overwhelmingly rejected, however, in Appenzell Innerrhoden, a northeastern canton. Appenzell Innerrhoden is strongly conservative on social issues, not having given women the right to vote on local issues until 1991. The Wikipedia article on the canton includes some interesting information:

Somewhat before the early 2000s, the idyllic countryside of Appenzell Innerrhoden apparently became popular with nudists, and at the 2009 Landsgemeinde the canton’s residents voted to prohibit naked hiking. Violators would be fined. However nudists who appealed against their fines to the federal court have been reimbursed by the local authorities, as nudism is not a crime under Swiss federal law which takes precedence. It is common for cars rented in Switzerland to be registered in Appenzell Innerrhoden, and thus having license plates starting with “AI”, because of the reduced tax on cars in this canton.



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Zoï’s Fantastic Central Asia Water Map, and Turkmenistan’s Geo-Engineering Projects

Aral Sea Water MapThe Geneva-based Zoï Environment Network has created some detailed and well-designed environmental maps. Available through flickr photostream along with many other images, the maps are not very well catalogued. Regardless of such organizational problems, the site is well worth exploring. The map that I have posted here, moreover, is the best presentation of the Central Asia’s water crisis that I have seen.

Note on the map how the Amu Darya no longer reaches the Aral Sea, which as a result has largely turned into a dry salt-flat. As can be seen as well, the much-diminished Syr Darya still does reach the Northern Aral Sea. Kazakhstan has recently built a series of dikes to keep water from flowing out of this restricted northern lake onto the dry southern lake-bed, thereby keeping the water level high enough and the salt content low enough to allow fish to survive and indeed to thrive. The so-called Aral Sea is thus not entirely dead, although the vast bulk of it is.

Other interesting developments are also evident on the map. Note, for example, the label “Golden Age Lake (under construction)” in northern Turkmenistan.

According to the Wikipedia:

Golden Age Lake known as Altyn Asyr locally, is the name of a man made lake under construction in the Kara Kum Desert of Turkmenistan.  Upon completion, the lake will span 770 square miles (2,000 km2) with a maximum depth of 230 feet (70 m), and hold more than 130 cubic kilometers (4600 billion cubic feet) of water. Filling the lake could take 15 years and cost up to $4.5 billion. According to government plans, it is intended to be filled by a 2,650-kilometer (1,650 mi) network of tributary canals.

However critics point out that much of the water pumped into the searing desert will evaporate, adding that it is likely to be contaminated with toxic pesticides and fertilisers. It is also feared that Turkmenistan may seek to siphon water from the Amu Darya river, which runs along the country’s northern border with Uzbekistan. That could trigger a dispute between the two countries and inflict further damage of the environment.

Although Turkmenistan claims that the lake will provide wildlife habitat and other environmental benefits, any such gains will likely be short-lived. This “lake” is perhaps most accurately described as a waste-water sump. Irrigated lands in desert environments must be over-watered and then drained in order to prevent the accumulation of salt in the soil. The resulting drainage sumps can initially provide fine wildlife habitat, but the salt content will gradually increase, eventually eliminating most life. California’s Salton Sea is a prime example of such a process. Tellingly, The Guardian referred to the construction of Turkmenistan’s Golden Age Lake as “a logic-defying feat that might have appealed to Stalin.”

Note also that some of the drainage water from the agricultural lands of the lower Any Darya Valley ends up in Sarygamysh, a large, undrained lake that fluctuates significantly in area. Last summer, Turkmenistan announced another quixotic project in this area. As reported by TerraDaily:

Turkmenistan is allocating tens of millions of dollars to plant trees in a region neighbouring the stricken Aral Sea, state newspaper Neutral Turkmenistan said Tuesday. “A project has been developed to target environmental problems in the Aral Sea zone, which entails planting greenery over 20,000 hectares on the eastern bank of the Sarygamysh lake,” the newspaper said.

Considering the harsh environmental circumstances in the area, it is questionable whether this artificial forest will survive.  Unfortunately, information on the project, and on the lake more generally, is difficult to find.

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Intense Ethnic Divisions in the 2013 Kenyan Election

Kenya 2013 Election MapMedia reports of the recent Kenyan presidential election have generally focused on the facts that the contest was not as violent as many feared it would be, and that the winner, Uhuru Kenyatta, has been charged by the International Criminal Court with committing crimes against humanity in relation to the bloody presidential election of 2007. Some articles have also mentioned the intensely ethnic nature of the voting pattern, the topic of today’s GeoNote.

Although the election was relatively close, with Kenyatta receiving just over 50 percent of the vote, in most counties the results were extremely lopsided. As can be seen on the map that I constructed, in most cases Kenyatta either took over 80 percent of the vote or less than 30 percent, with his tally ranging from more than 97 percent (Nyandarua) to less than a quarter of one percent (Homa Bay). Such patterns reflect ethnic divisions. In the most basic terms, Kenyatta won handily in Kikuyu and Kalenjin areas, whereas his opponent, Raila Odinga, won by similar margins in Luo and Kamba areas. Not surprisingly, Kenyatta is himself Kikuyu, whereas his running mate, William Ruto, is Kalenjin, while Odinga is Luo, and his running mate, Stephen Kalonzo Musyoka, is Kamba.  Such a divisional pattern is typical in Kenyan elections. The voting behavior of the fifth of Kenya’s “big five” ethnic groups, the Luhya, is less predictable.  As the Wikipedia explains:

In Kenyan politics, the Luhya population commonly referred to as the Luhya vote in an election year, is usually a deciding factor of the outcome of an election. The community is known to unite and vote as a block usually for a specific political candidate without division of mind and regardless of political differences. Given their high population numbers, a political candidate who enjoys Luhya support is almost always poised to win the country’s general elections, barring incidents of fraud. The community is thereafter “rewarded” politically, by one of their own being appointed vice president or to a high profile political office by the winning candidate.

Kenya Counties mapIn the 2013 election, however, such patterns did not hold, as the Luhya voted fairly strongly for Odinga, the losing candidate. As it was known ahead of time that Odinga was popular in Luhya-land, some bloggers thereby incorrectly predicted that he would win the election. Evidently Kenyatta did better than expected among some of the country’s smaller ethnic groups.

These election returns indicate that Kenya has a fairly poorly consolidated sense of common nationality. Here, ethnicity matters far more than anything else, outweighing national issues and ideological divisions. Although regionally and ethnically skewed elections are common in many countries, seldom are they as extreme as in Kenya.

(Data source: Electoral Politics:

Inset Map:



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Mapping Evangelical Christian Missionary Efforts

World Evangelical MapIt is difficult to find maps depicting religious adherence in areas outside of the historical boundaries of the major universalizing faiths, such as much of sub-Saharan Africa and Oceania. Many such places, however, are characterized today by profound religious change, as missionaries seek converts and as syncretic forms of worship emerge. Some proselytizing organizations, however, maintain intricate maps of their own activities. One prime example is the Joshua Project, an evangelical organization that defines itself as “a research initiative seeking to highlight the ethnic people groups with the fewest followers of Jesus Christ.”

The Joshua Project’s world map of “Gospel Progress,” posted here, is extraordinarily precise, although its accuracy is questionable. The map makes it seem as if a significant Christian evangelical community has been established virtually everywhere in Amazonia, the Congo Basin, and Highland New Guinea, with only a few small red splotches indicating “unreached” or “least reached” populations. Such a scenario seems unlikely, considering how remote some of these areas are, although it is undeniable that Christian missionaries have been highly active in many such places. The map is difficult to interpret, however, as it does not indicate how the three major categories are determined, leaving us to wonder what differentiates a “formative” from an “established” evangelical presence. Other maps on the same site, however, provide the necessary information. As it turns out, the thresholds set are relatively low, as a mere two-percent evangelical adherence rate is enough to place a region in the “significant/established church” category (see the map of Indonesian New Guinea below).

Papua Religion MapThe map’s most basic pattern is clearly evident: Joshua Project outreach has made almost no progress in areas of Muslim, Hindu, or Buddhist heritage, and has fared poorly across most of Europe and Russia. Although unnoted on the map, areas in Muslim countries marked as having been successfully evangelized, such as parts of Egypt and Indonesia, almost certainly indicate missionary activities among local Christian (or, in the case of Indonesia, animist) minorities, not among the Muslim majorities. Many of the areas mapped as evangelized in Egypt, moreover, are essentially unpopulated. The manner in which the Joshua Project subdivides the world for its mapping purposes is specified elsewhere on the website. The basic unit is labeled the “people group,” and is defined as follows:

For evangelization purposes, a people group is the largest group within which the Gospel can spread as a church planting movement without encountering barriers of understanding or acceptance” (Source: 1982 Lausanne Committee Chicago meeting.)… In most parts of the world lack of understandability acts as the main barrier and it is appropriate to define people group primarily by language, with the possibility of sub-divisions based on dialect or cultural variations. Such a list may be referred to as an ethno-linguistic list of peoples. In other parts of the world, most notably in portions of South Asia, acceptance is a greater barrier than understandability. In these regions, caste, religious tradition, location, and common histories and legends may be used to identify the primary boundary of each “people group.

Papua Religion Language MapA close analysis of another map on the website, that showing the Indonesian part of the island of New Guinea, reveals that in this area “people groups” are indeed defined on a linguistic basis, more specifically as mapped by the Ethnologue, a standard reference source that is also associated with Christian missionary efforts. As can be seen in the paired maps posted here, the Ethnologue depiction of the east-central portion of this area is close to but not identical with that found on the Joshua Project map. It is unclear whether the discrepancy is due to the use of older Ethnologue maps by Joshua Project cartographers, or whether the Joshua Project actually defines Papuan “people groups” independently of the Ethnologue in some circumstances.

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Punjabi and the Problems of Mapping Dialect Continua

Dialects Sometimes Called Punjabi MapThe Wikipedia list of the world’s most widely spoken languages, by mother tongue, puts Punjabi in tenth place, with its roughly 100 million native speakers exceeding the figures given for German, French, Italian, Turkish, Persian and many other well-known languages. The Wikipedia article on the Punjabi language stresses its growing appeal, noting that, “The influence of Punjabi as a cultural language in Indian Subcontinent is increasing day by day mainly due to Bollywood. Most Bollywood movies now have Punjabi vocabulary mixed in, along a few songs fully sung in Punjabi.”

But despite Punjabi’s obvious importance, it is extremely difficult to find a map of the language on the internet. Partly this is due to the fact that Punjabi spans the India-Pakistan border, and most maps of individual languages are country-based. One can thus find many language maps of India that depict Punjabi, and virtually all language maps of Pakistan do so as well. But on Pakistani language maps, the area covered by Punjabi has been diminishing in recent years. Maps made in earlier decades typically showed virtually all of northeastern quadrant of the country as Punjabi-speaking, whereas many recent maps retain the Punjabi label only for the core zone of this region. On these maps, what used to be the southern Punjabi area is now typically mapped as Saraiki-speaking, whereas the north is depicted as Hindko-speaking. Saraiki and Hindko, moreover, are sometimes merged together as the Lahnda language, sometimes called “Western Punjabi.” This linguistic reclassification scheme, however, is quite controversial, especially in Pakistan. Here Punjabi partisans are often irritated by the diminution of their language, whereas locally based scholars are happy to see their own speech-forms elevated to the status of separate languages.

Such controversies stem from the fact that Punjabi forms a dialect continuum, which means that adjacent dialects may be virtually identical, but the farther one travels, the more distinctive they become. As a result, dialects on the opposite sides of such a continuum may be non-mutually intelligible, and hence separate languages by standard linguistic criteria, yet no clear language boundaries can actually be located. The Punjabi dialect continuum is further complicated by the fact that it merges with the Hindi dialect continuum in northern India and with the Sindhi dialect continuum in southern Pakistan. To a certain extent, one can thus imagine a much larger dialect continuum stretching across most of northern South Asia. The standardized form of Hindi is a completely different languages from standardized Punjabi, but on the margins the situation is not always so clear-cut. The presence of Urdu adds yet another layer of complexity.

A relatively new Wikipedia language map (dated January 31, 2013) deals with these issues by mapping local dialects in the Punjabi-speaking area in both Pakistan and India. The caption of this map found on the “Punjabi Language” Wikipedia article (but not on other Wiki articles that use it) is delightfully honest: “Dialects Sometimes called Punjabi.” Note that on this map “Hindko” is highly restricted, whereas “Saraiki” does not appear at all. One must wonder how much sub-dialectal variation is found in some of these mapped dialect areas, particularly in the elongated Derawali zone (colored red on the map).

The Wikipedia article on Derawali  indicates that a certain degree of linguistic convergence is now occurring: “Today like all other dialects in Punjab, a process of unification and getting closer to Standard Pakistani Punjabi (Urdu influenced Majhi written in Shahmukhi) has made it [Derawali] quite similar morphologically, syntactically and mutually intangible with Standard Punjabi.” The lexical table provided in the same article, however, makes Derawali seen quite different from standard Punjabi. Whereas in the latter, the English words “boy, girl, woman, and man” are rendered “Munda, Kuri, Znaani, Aadmi,” in Derawali they are given as “Chohr, Chohir, Aurat, Mard.”

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