Forced Displacement from Ukraine’s War-Torn Territories: Intersectionality and Power Geometry

Kuznetsova, Irina; Mikheieva, Oksana

doi:10.1017/nps.2020.34

Cited by 16 publications

(7 citation statements)

References 49 publications

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“…An important body of scholarship has emerged around this topic, addressing the humanitarian crisis(Bulakh, 2017;Kuznetsova and Mikheieva, 2020) and providing a gendered analysis of IDPs (Khrystova and Uvarova, 2020).…”

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confidence: 99%

A Long-Term View of Refugee Flows from Ukraine: War, Insecurities, and Migration

Lloyd

Sirkeci

2022

Migration Letters

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This article examines the exodus of migrants from Ukraine in the context of the Russian invasion, making use of the conflict model of migration. We argue that Ukraine has long been characterized by insecurities which have already fueled large waves of emigration from the country. Indeed, the most recent phase of Ukrainian emigration should be seen as a continuation of the ongoing tendency of people residing in the country to seek escape from the overarching conditions of insecurity there. Earlier migrations from Ukraine have also established a culture of migration which has mediated the outflow of Ukrainians during the current crisis. Ukrainians who had already harboured inclinations to leave the country and who were possessed of the necessary capabilities (i.e. social capital, financial capital, human capital and physical ability) became mobile at the onset of the invasion in February, while many others were left behind. At the same time, the welcoming attitude of many European states has been key to the fast and safe exodus of Ukrainian migrants thus far.

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confidence: 99%

A Long-Term View of Refugee Flows from Ukraine: War, Insecurities, and Migration

Lloyd

Sirkeci

2022

Migration Letters

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“…As Mikheeva and Kuznetsova have shown in their recent research, displaced people face different problems with housing, employment, and receiving financial support from the state, as well as mental health issues and coping with traumatic experience (Kuznetsova et al 2018; Kuznetsova and Mikheieva 2020). At the same time, IDPs may find themselves searching for a new identity as a “displaced person,” creating a personal story of war and displacement to fit themselves into a new context.…”

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confidence: 99%

“…Integration and adaptation of internally displaced people, as shown by Kuznetsova (2020) and Lazarenko (2020), is linked to the sense of place, feeling of home, and sense of belonging or not-belonging, as well as the rethinking of spatial identities. Hence, it might be assumed that the ongoing process of renaming urban spaces in Ukraine, which started in 2015 and is still ongoing at the municipal level, may jeopardize the process of integration of the IDPs.…”

Section: Introductionmentioning

confidence: 99%

Renaming and Reclaiming Urban Spaces in Ukraine: The Perspective of Internally Displaced People

Lazarenko¹

2021

Nationalities Papers

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For more than six years, Ukrainian society has been constantly searching for ideas as to how to write a new “national biography.” In a society divided by armed conflict, the so-called decommunization process is considered to be an idea capable of uniting a nation. This process started back in 2015, with the passing of a specific law that required not only the deconstruction of Soviet-time monuments in public spaces, but also a huge decommunization of place names. The article will explore the main practices of place (re-)naming during the different stages of the decommunization (but not de-ideologization) of spaces, as well as describing the problems that may emerge in society as a result of a rapid transition from one narrative to another. Based on a case study of spatial identities of internally displaced people, I am going to answer the question of how people perceive renamed spaces, and how they reclaim and re-appropriate these spaces in the midst of an identity crisis.

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“… 12 Kuznetsova, I. and Mikheieva, O. (2020) Forced displacement from Ukraine’s war-torn territories: intersectionality and power geometry.…”

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confidence: 99%

Predicting refugee flows from Ukraine with an approach to Big (Crisis) Data: a new opportunity for refugee and humanitarian studies

Jurić

2022

Preprint

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Background: This paper shows that Big Data and the so-called tools of digital demography, such as Google Trends (GT) and insights from social networks such as Instagram, Twitter and Facebook, can be useful for determining, estimating, and predicting the forced migration flows to the EU caused by the war in Ukraine. Objective: The objective of this study was to test the usefulness of Google Trends indexes to predict further forced migration from Ukraine to the EU (mainly to Germany) and gain demographic insights from social networks into the age and gender structure of refugees. Methods: The primary methodological concept of our approach is to monitor the digital trace of Internet searches in Ukrainian, Russian and English with the Google Trends analytical tool (trends.google.com). Initially, keywords were chosen that are most predictive, specific, and common enough to predict the forced migration from Ukraine. We requested the data before and during the war outbreak and divided the keyword frequency for each migration-related query to standardise the data. We compared this search frequency index with official statistics from UNHCR to prove the significations of results and correlations and test the models predictive potential. Since UNHCR does not yet have complete data on the demographic structure of refugees, to fill this gap, we used three other alternative Big Data sources: Facebook, Twitter and Instagram. Results: All tested migration-related search queries about emigration planning from Ukraine show the positive linear association between Google index and data from official UNHCR statistics; R2 = 0.1211 for searches in Russian and R2 = 0.1831 for searches in Ukrainian. It is noticed that Ukrainians use the Russian language more often to search for terms than Ukrainian. Increase in migration-related search activities in Ukraine such as граница (Rus. border), кордону (Ukr. border); Польща (Poland); Германия (Rus. Germany), Німеччина (Ukr. Germany) and Угорщина and Венгрия (Hungary) correlate strongly with officially UNHCR data for externally displaced persons from Ukraine. All three languages show that the interest in Poland is the highest. When refugees arrive in nearby countries, the search for terms related to Germany, such as crossing the border + Germany, etc., is proliferating. This result confirms our hypothesis that one-third of all refugees will cross into Germany. According to Big Data insights, the estimate of the total number of expected refugees is to expect 5,4 Million refugees. The age group most represented is between 24 and 45 years (data for children are unavailable), and over 65% are women. Conclusion: The increase in migration-related search queries is correlated with the rise in the number of refugees from Ukraine in the EU. Thus this method allows reliable forecasts. Understanding the consequences of forced migration from Ukraine is crucial to enabling UNHCR and governments to develop optimal humanitarian strategies and prepare for refugee reception and possible integration. The benefit of this method is reliable estimates and forecasting that can allow governments and UNHCR to prepare and better respond to the recent humanitarian crisis.

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Forced Displacement from Ukraine’s War-Torn Territories: Intersectionality and Power Geometry

Cited by 16 publications

References 49 publications

A Long-Term View of Refugee Flows from Ukraine: War, Insecurities, and Migration

A Long-Term View of Refugee Flows from Ukraine: War, Insecurities, and Migration

Renaming and Reclaiming Urban Spaces in Ukraine: The Perspective of Internally Displaced People

Predicting refugee flows from Ukraine with an approach to Big (Crisis) Data: a new opportunity for refugee and humanitarian studies

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