Thesis: The migration of Russian academics is influenced by their socialization. Understanding the mobility of academic labor can augment the attractiveness of countries or regions to which immigrants are drawn. Migration patterns were derived from an empirical web survey (level of significance >95%) of 500 Russian academics who migrated to Germany. The results indicated that their decisions were based on their specific values, which determined their perceptions of the transaction costs and benefits involved in international labor markets. New Institutional Economics (NIE) serves as a theoretical framework through which to understand academics’ decisions to migrate and illustrates that peripheral regions and small enterprises can attract well-educated workers. InterviewEigenständig auszufüllender Fragebogen Self-administered questionnaireInterview Russian academics migrating to Germany and having applied for scholarships from German scientific foundations in Russia in the years 2001 to2006. An online survey conducted in Russia (n = 485 conducted from 2/2007 to 4/2007) provided the database regarding the migration of Russian academics.

Abstract

The Migration Cost Surveys (MCS) project is a joint initiative of the Global Knowledge Partnership on Migration and Development (KNOMAD) and the International Labor Organization (ILO). The project was initiated to support methodological work on developing a new Sustainable Development Goal (SDG) indicator (10.7.1) on worker-paid recruitment costs. The surveys of migrant workers conducted in multiple bilateral corridors between 2015 and 2017 provide new systematic evidence of financial and some non-financial costs incurred by workers to obtain jobs abroad. The compiled dataset is divided into two waves (2015 and 2016) based on the questionnaire version used in the surveys. This document describes surveys conducted using the 2016 version of the MCS questionnaire.

Geographic coverage

Multinational coverage - India - Philippines - Nepal - Uzbekistan - Kyrgyz Republic - Tajikistan - Countries in Western Africa

Analysis unit

KNOMAD-ILO Migration Costs Surveys (KNOMAD-ILO MCS) have the following unit of analysis: individuals

Universe

Surveys of migrants from the following corridors are included: • India-Saudi Arabia • Philippines to Saudi Arabia • Nepal to Malaysia, Qatar and Saudi Arabia • Kyrgyzstan, Tajikistan, Uzbekistan to Russia • West African countries to Italy

Kind of data

Sample survey data [ssd]

Sampling procedure

All surveys conducted for this project used either convenience or snowball sampling. Sample enrollment was restricted to migrants primarily employed in low-skilled positions. There is variation in terms of when migrants were interviewed in their migration life-cycle. Two surveys of recruited workers - that is workers who are recruited in their home countries for jobs abroad - namely Filipinos and Indians to Saudi Arabia, were conducted with migrants returning to their origin countries (for visits or permanently). The surveys of non-recruited migrants - Central Asian migrants to Russia and West African migrants to Italy - were administered in the destination countries, which permitted multiple bilateral migration channels to be documented (at cost of smaller sample sizes in some corridors, particularly with Italy as destination). The survey instruments for non-recruited migrants were worded in present tense for various aspect of stay in the destination country. The content of the variables remains analogous to the surveys of returnees. Finally, the survey of Nepalese migrants was conducted with migrants who were departing to their destination countries within a two-week period. Please refer to Annex Table 1 of the 2016 KNOMAD_ILO MCS Guide for a summary description of the samples included in the 2016 KNOMAD-ILO MCS dataset.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The 2016 KNOMAD-ILO Migration Costs Surveys consists of 7 survey modules: A. Respondent information B. Information on costs for current job C. Borrowing money for the foreign job D. Job search efforts and opportunity costs E. Work in foreign country F. Job environment G. Current status and contact information

Sampling error estimates

n/a

Data appraisal

n/a

The stereotype content model (SCM), originating in the United States and generalized across nearly 50 countries, has yet to address ethnic relations in one of the world’s most influential nations. Russia and the United States are somewhat alike (large, powerful, immigrant-receiving), but differ in other ways relevant to intergroup images (culture, religions, ideology, and history). Russian ethnic stereotypes are understudied, but significant for theoretical breadth and practical politics. This research tested the SCM on ethnic stereotypes in a Russian sample (N = 1115). Study 1 (N = 438) produced an SCM map of the sixty most numerous domestic ethnic groups (both ethnic minorities and immigrants). Four clusters occupied the SCM warmth-by-competence space. Study 2 (N = 677) compared approaches to ethnic stereotypes in terms of status and competition, cultural distance, perceived region, and four intergroup threats. Using the same Study 1 groups, the Russian SCM map showed correlated warmth and competence, with few ambivalent stereotypes. As the SCM predicts, status predicted competence, and competition negatively predicted warmth. Beyond the SCM, status and property threat both were robust antecedents for both competence and warmth for all groups. Besides competition, cultural distance also negatively predicted warmth for all groups. The role of the other antecedents, as expected, varied from group to group. To examine relative impact, a network analysis demonstrated that status, competition, and property threat centrally influence many other variables in the networks. The SCM, along with antecedents from other models, describes Russian ethnic-group images. This research contributes: (1) a comparison of established approaches to ethnic stereotypes (from acculturation and intergroup relations) showing the stability of the main SCM predictions; (2) network structures of the multivariate dependencies of the considered variables; (3) systematically cataloged images of ethnic groups in Russia for further comparisons, illuminating the Russian historical, societal, and interethnic context.

Within the framework of the Immigrant German Election Study (IMGES), for the first time in Germany exclusively persons with a Turkish migration background or an origin from countries of the former Soviet Union were interviewed about political attitudes and behaviour. One of the main objectives of the study was to investigate whether the voting behaviour of German citizens with a migration background can be explained by established theories of electoral research or whether it is more dependent on migration-specific characteristics. The survey was conducted after the 2017 federal elections and was conducted simultaneously with the post-election survey of the German Longitudinal Election Study (GLES). The project was funded by the German Research Foundation (DFG) between October 2016 and March 2020. Migration background of the respondent and the partner: Political interest; born in Germany; country of birth; month and year of moving close to Germany; acquisition of German citizenship at birth or later; year of acquisition of German citizenship; previous citizenship; dual citizenship; second citizenship; reason for migration; parents born in Germany, country of birth of father and mother; Year when father and mother moved to Germany; nationality of father and mother; region of origin in Turkey, Russia, Kazakhstan and Ukraine; marital status; living together with a partner; partner born in Germany, country of birth of partner; country of birth of father and mother of partner 2. Germany - political problems, goals, economic situation: currently most important and second most important problem in Germany; most suitable party to solve the problems; most important problem in Germany for one´s own migration group; most suitable party to solve this problem; most important and second most important goal of the Federal Republic of Germany in the next 10 years (Inglehart Index) assessment of the general economic situation in Germany; assessment of the current economic situation of one´s own migration group; turnout in the last Bundestag election; postal vote; election decision Bundestag election (first and second vote); hypothetical turnout and election decision (respondents under 18 years of age); date of election decision; recall Bundestag election 2013: Voter participation and decision (first and second vote). 3. Political orientation and assessment of political actors: Sympathy Scale for the parties CDU, CSU, SPD,FDP, Die Linke, Grüne and AfD; Sympathy Scale for selected top politicians (Angela Merkel, Martin Schulz, Christian Lindner, Sahra Wagenknecht, Dietmar Bartsch, Horst Seehofer, Cem Özdemir, Katrin Göring-Eckardt, Alice Weidel and Alexander Gauland); satisfaction with the performance of the federal government from CDU/CSU and SPD (Scale); left-right classification of the above-mentioned parties; left-right self-classification; satisfaction with democracy; address during the election campaign for the 2017 Bundestag elections; address during the election campaign by which party; address during the election campaign as a migrant; address during the election campaign on German politics by various organisations; assessment of the current own economic situation; state elections Voter turnout at the last state elections in NRW; election receipt at the state elections (first vote and second vote). 4. Political issues: agreement on various statements: demand for a legally established women´s quota for the supervisory boards of large companies, government should take measures to reduce income disparities, registered same-sex partnerships should be given equal status to marriage; too much influence of foreign governments (Turkey or Russia) on politics in Germany; opinion on religious instruction at state schools in Germany; opinion on voting rights in local elections for foreigners living permanently in Germany who do not come from an EU member state; political knowledge First vote/ second vote, 5% hurdle; party positions and own position on the topic of taxes and welfare state benefits (socio-economic dimension); personal importance of the topic of taxes and welfare state benefits (salience socio-economic dimension); party positions and own position on the topic of facilitated or limited opportunities for foreigners to move to Germany (libertarian-authoritarian dimension); personal importance of the topic of opportunities for foreigners to move to Germany; party positions regarding their relationship to the respondent´s country of origin; importance of the relationship of German parties to the country of origin. 5. Religion and affiliation: self-assessment of religiousness; denomination or faith community; frequency of participation in religious meetings; denomination of the partner; social identity: group membership; strongest group membership; important for identity as a German/German (being born in Germany, sharing German values and traditions, being able to speak German, having German ancestors); refusal to marry a person of German origin without a migration background, Syrian origin, Russian-German origin, Turkish origin, Christian faith or Muslim faith 6. Political opinions: attitude towards politics: Voter participation as a civic duty, politicians only represent interests of the rich and powerful, political issues often difficult to understand, strong political leader good for Germany, even if he bends the laws; attitude towards the immigration of different groups of people to Germany (workers from EU countries, workers from non-EU countries, refugees from war zones, politically persecuted refugees, economic refugees); type of political participation in the last 12 months (e.g. establishing contact with a politician, working in a political party or grouping, etc.); supported party; participation in activities of various organisations in the last 12 months (e.g. employers´ organisations, religious/church groups, sports and leisure club, etc.); at least half of the members of the participants of this organisation with a migration background; institutional trust Germany (parliament, judiciary, government, police, political parties, media); general social trust; likelihood of voting for the following parties: CDU, CSU, SPD, Die Linke, Grüne, FDP and AfD; frequency of discussions about politics in the past week; party affiliation; strength of party identification; type of party identification (e.g. party means a lot to me, party in itself means less to me, but it makes the better politics); frequency of visits to the country of origin; direct family members in the country of origin; home ownership in the country of origin; frequency of use of different media for information about the country of origin (German newspapers, German television, Turkish/Russian newspapers or television, newspapers or television of the country of origin); frequency of contact with relatives in the country of origin; political interest in relation to the country of origin; voter participation in the last national election in the country of origin; voting decision in the last election in the country of origin; dual citizens: intended voting decision in parliamentary elections in the country of origin; hypothetical voting decision in parliamentary elections in the country of origin; institutional trust in the country of origin; membership of a foreign party or Donation of money to that party; participation in activities of a foreign party in the last two years; opinion on Turkey´s membership of the EU; participation in a referendum on constitutional reform in Turkey; decision for or against constitutional reform; hypothetical decision concerning that referendum; sympathy scale for politicians of foreign origin (Turkish President Erdogan/Russian President Putin); support or rejection of the Russian Federation´s approach to the integration of Crimea. 7. Discrimination and social network: identity as a member of a group disadvantaged in Germany; reasons for discrimination (e.g. foreign descent, etc.); areas of discrimination (e.g. finding accommodation, etc.) Social trust with regard to one´s own migrant group; composition of circle of friends and colleagues (proportion with migrant background); self-assessment of language skills (German, Turkish, Kurdish, Russian, other language of origin); language mainly used at work, with friends and in the family; frequency of discussions about Turkish/Russian policy with the family; family member present with positive and negative evaluation of the current policy of the Turkish/Russian government; number of family members with positive and negative evaluation. Demography: sex; age (year of birth; household size; age of persons in the household; country of last school attendance (Germany or other country); highest school leaving certificate; years of school attendance abroad; vocational training completed in Germany or in another country; type of vocational training certificate; type of vocational training abroad; current or previous employment; current or previous employment; current or previous occupational status; job title; temporary work; current or previous employment sector; fear of unemployment or loss of business; self-assessment of shift membership; union member in household; net household income (categorised); education and occupation of partner: country of schooling; years of schooling abroad; school-leaving certificate; current or previous employment; current or previous job. Additionally coded: timestamp modules 1 - 15 incoming; timestamp modules 1 - 15 outgoing; sequential number; date of interview (day, month, year); state; sample: subsample after onomastics/ subsample after screening; data collection mode (CAPI or CASI); language of data collection (CAPI German, CASI Turkish, CASI Russian); consent to interview; control questions; willingness to re-interview; PSU: point number; weighting factors; return code; screening questions: origin; German citizenship; end of interview (no

Dataset used for the exploratory study on how xenophobic discourses have been articulated as "truth" by media outlets and think tanks in France, Germany, Netherlands, Russia, and United Kingdom

Data collection:

Using the official twitter account of prominent far-right parties as a point of departure (National Rally, NR - France; Alternative für Deutschland, AfD - Germany; Forum voor Democratie, FvD - Netherlands; Liberal Democratic Party of Russia, LDPR - Russia; and UK Independent Party, UKIP - United Kingdom), media outlets and think tanks explicitely committed to a far-right agenda (displaying overt discriminatory views towards immigrants) were identified in June 2021.

News pieces and reports available on their website or YouTube Channel between June and July 2021 had their titles copied and pasted on the dataset, serving as a basis for a critical discourse analysis aiming at identifying similarities in terms of (a) "truths" targeting immigrants and their alleged supporters and (b) legitimation techniques.

All data was anonymised. As a joint exploratory study not involving human beings and with fully anonymised data, this research did not require Ethical approval.