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Srl | Item |
1 |
ID:
116544
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Publication |
2012.
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Summary/Abstract |
Since the late 1990s, a little-known wave of Chinese migrants has been making its way to France. Coming from regions with no tradition of international mobility, it differs from classic migratory flows in that it consists mainly of urban middle-class women in their forties who are affected by the reform policy. Drawing on the point of view of these female migrants regarding developments in the job market, their economic resources, and changes in family relations, this article examines the transformations in social norms and gender roles that affected these people before their departure. It considers whether these developments have had an impact beyond China's borders, and whether they may have influenced the gender configuration of this migratory flow making its way to Europe.
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2 |
ID:
128488
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Publication |
2013.
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Summary/Abstract |
Actual position of the investigation of this territory was expressed in academician V. V. Radloff's words: "Importance of the investigation of the Turkic tribes' remains in the far east is unquestionable because these
countries have never been visited by experts of the Turkic languages. And we have only odd bits of information collected by outside observers who were not specially prepared for aimobjective".' In 1891 N. F. Katanov was sent by Imperial Saint-Petersburg Academy of Science and Imperial Russian Geographic Society to Eastern Turkestan as the most prepared specialist in the Turkic languages. The investigation of the territory was held in the framework of an investigation project of the Turkic tribes in Eastern Siberia, Mongolia and Northern China to analyse the Turkic tribes' language and household activities. At that time Eastern Turkestan or Uigurstan was a part of China as its northern region - Xinjiang which included Kashgaria (southern part) and Dzungaria (northern part). Population of this region comprised of different Turkic groups: the Turcomen- Uygurs and Kazakhs-Kirghiz worshiping Islam, the Mongolians-Oirats and Chinese Turcomen worshiping Buddhism, etc.
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3 |
ID:
124550
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Publication |
2013.
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Summary/Abstract |
This paper aims at an important gap in the literature, which has not modeled the effect of social learning in a real option context and examined uncertainty-reduction measures through social learning. This paper addresses the gap by modeling social learning as a way of reducing parameter uncertainty, thus facilitating technology adoption and shortening the waiting time in irreversible investments. We use household-level data on intermediate-technology greenhouse adoption in northern China to test the predictions in both a linear probability model and a duration analysis. Our empirical findings support the hypothesis. We also find that market volatility and insecure land property rights discourage adoption.
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4 |
ID:
096126
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Publication |
2010.
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Summary/Abstract |
In order to investigate vehicle fuel quality in northern China, the sulfur content of fuels purchased from the market has been studied. 235 samples from urban areas and highway service stations were collected and tested with energy dispersive X-ray fluorescence spectrometry. 88% of the gasoline samples contained sulfur below 500 ppm, the limit then in effect, and 92.5% of the diesel fuel samples were below 2000 ppm, the required limit. China's Ministry of Environmental Protection recommend lower sulfur to assure that the vehicles using the fuels comply with the China III emission standards-those limits are 150 ppm sulfur for gasoline and 350 ppm for diesel fuel. The recommended limits were not often met: in Jinan, Shanghai, Changchun and Xi'an, 0%, 11%, 46% and 60% of the gasoline sampled were below 150 ppm sulfur. For samples from highway stations, only 14-58% of gasoline was under the 150 ppm sulfur and only 0-67% of diesel samples below 350 ppm in different regions. This mismatch, between fuel sulfur levels that would enable vehicle emission controls to operate effectively, and the actual fuel sulfur levels at service stations, results in unnecessarily high pollution from potentially cleaner vehicles.
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