The effects of migration on urban space: An example of Sultanbeyli
2021
0 views
0 downloads
Advisor: Doç. Dr. Pelin Pınar Giritlioğlu
Abstract (EN)
The international and mass migration in the wake of 2011 Syrian crisis has had a great deal of consequences in global extent. With this migration wave going beyond millions of people in quantative density, Turkey allowed immigrants from neighbouring country Syria at the rate that it experienced for the first time in its history. In this study, I aimed to pursue what sort of impacts migration that unites refugees with cities, has on space. To observe the effects of migration powerfully, I preferred Sultanbeyli/ Mehmet Akif district as an example, which has the highest number of refugees in Istanbul Anatolian side. While going after this curiosity, I grounded on Lefebvre's reading that indicates space is continously reproduced and it is the struggle field between social groups. In this respect, I employed a Marxist oriented work, Lefebvre's spacial triad theory to ascertain the position of Syrian refugees in Mehmet Akif's reproduction. Additionally, by interviews with neighborhood residents, home visits and participant observation, I tried to understand how spatial separation/unity and spatial belonging have transformed with migration.
Author
Dr. Ece Denizler
Institution
How to Cite
Ece Denizler (Master Thesis). The effects of migration on urban space: An example of Sultanbeyli, 2021, İstanbul University.
Keywords
License
Tüm Hakları Saklıdır
This work is shared under the specified license terms.
More theses from İstanbul University
- In the covid 19 pandemic of female employees at a university hospital attitudes and affecting factors in nutrition of 9 months-6 years old children(2022)
- The perception of the right-wing movements in Turkey as to the 27 May Coup: 1960-1980(2020)
- Economic and social life in the Ottoman Empire according to the 1890 year's news of La Turquie Newspaper(2022)
- Land regime in the Umayyads period(2022)
- Merkel hücreli karsinomda tanısal ve prognostik belirteçler(2022)
- Use of machine learning methods in classification of respiratory system diseases(2021)