How to search?
advanced search

Search results

Filters

  • Journals
  • Authors
  • Keywords
  • Date
  • Type

Search results

Number of results: 5
items per page: 25 50 75
Sort by:

Brexit and Beyond: Transforming Mobility and Immobility

Majella Kilkey Aneta Piekut Louise Ryan
Central and Eastern European Migration Review | 2020 | vol. 9 | No 1 | 5-12
Keywords Brexit migration mobility bordering EU
Download PDF Download RIS Download Bibtex

Abstract

This Guest Editorial introduces a special issue entitled Brexit and Beyond: Transforming Mobility and Immobility. The unfolding story of Brexit provided the backdrop to a series of events, organised in 2018 and 2019, which were the result of a collaboration between migration researchers in Warsaw and the UK, funded by the Noble Foundation’s Programme on Modern Poland. The largest event – held in association with IMISCOE – was an international conference, arising from which we invited authors to contribute papers to this special issue on the implications of Brexit for the mobility and immobility of EU citizens, particularly – but not exclusively – from Central and Eastern Europe, living in the UK. As we outline in this Editorial, collectively, the papers comprising the special issue address three key themes: everyday implications and ‘living with Brexit’; renegotiating the ‘intentional unpredictability’ status and settling down; and planning the future and the return to countries of origin. In addition, we include an interview with Professor Nira Yuval-Davis, based on the substance of her closing plenary at the conference – racialisation and bordering. Her insightful analysis remains salient to the current situation – in June 2020, as the UK enters the final months of the Brexit transition period – in the unexpected midst of a global pandemic and an imminent recession.

Go to article

Authors and Affiliations

Majella Kilkey
Aneta Piekut
Louise Ryan

Migration and Modernisation – an Alternative. Polemic essay withMarek Okólski’s article “Modernising Impacts of Emigration”

Aneta Piekut
Studia Socjologiczne | 2014 | No 1
Download PDF Download RIS Download Bibtex

Authors and Affiliations

Aneta Piekut
ORCID: ORCID

You've got Starbucks and Coffee Heaven... I Can Do This! Spaces of Social Adaptation of Highly Skilled Migrants in Warsaw

Aneta Piekut
Central and Eastern European Migration Review | 2013 | Vol. 2 | No 1
Download PDF Download RIS Download Bibtex

Authors and Affiliations

Aneta Piekut
ORCID: ORCID

Merlin Schaeffer (2014), Ethnic Diversity and Social Cohesion. Immigration, Ethnic Fractionalization and Potentials for Civic Action

Aneta Piekut
Central and Eastern European Migration Review | 2014 | Vol. 3 | No 1
Download PDF Download RIS Download Bibtex

Authors and Affiliations

Aneta Piekut
ORCID: ORCID

Struktura gospodarstwa domowego a skłonność respondentów do uchylania się od odpowiedzi na pytanie o całkowity dochód netto w Europejskim Sondażu Społecznym, 2008–2018

Piotr Jabkowski Aneta Piekut
Studia Socjologiczne | 2022 | No 2 | 165-189 | DOI: 10.24425/sts.2022.141427
Keywords Europejski Sondaż Społeczny unikanie odpowiedzi błąd nielosowy pomiar dochodu
Download PDF Download RIS Download Bibtex

Abstract

Poza brakami danych, wynikającymi z niechęci ludzi do udziału w badaniu lub ich niedostępnością w trakcie badań terenowych, istotnym składnikiem całkowitego błędu pomiaru sondaży są braki danych będące efektem unikania przez respondentów odpowiedzi na niektóre pytania kwestionariuszowe. Wykorzystując dane Europejskiego Sondażu Społecznego z lat 2008–2018, analizujemy braki odpowiedzi na pytanie o całkowity dochód netto gospodarstwa domowego. Głównym celem było sprawdzenie, czy złożoność struktury gospodarstwa domowego skłania respondentów do uchylania się od odpowiedzi na pytanie o dochód. Modelując prawdopodobieństwa unikania odpowiedzi wykorzystaliśmy wielopoziomowe modele regresyjne przyjmując, iż na skłonność jednostek do nieodpowiadania wpływ ma również kontekst krajowy. W artykule pokazaliśmy, że większą skłonnością do nieodpowiadania charakteryzują się osoby zamieszkujące bardziej liczne gospodarstwa domowe, posiadające dochody z mniej stabilnych źródeł oraz o bardziej złożonej strukturze rodzinnej.
Go to article

Bibliography

1. Ananyev, Maxim, Sergei Guriev. 2016. Effect of income on trust: Evidence from the 2009 crisis in Russia. Pobrane z: https://ssrn.com/abstract=2542001. Dostęp 12.04.2021.
2. Bishop, George F., Robert W. Oldendick, Alfred J. Tuchfarber, Stephen E. Bennett. 1986. Opinions on Fictitious Issues: The Pressure to Answer Survey Questions. Public Opinion Quarterly, 50, 2: 240–250. DOI: 10.1086/268978.
3. Bethlehem, Jelke G. 2002. Weighting nonresponse adjustments based on auxiliary information. In: R. M. Groves, D. A. Dillman, J. L. Eltinge, R. J. A. Little, eds. Survey nonresponse. London: Wiley, 275–287.
4. Bjørnskov, Christian, Gert T. Svendsen. 2013. Does social trust determine the size of the welfare state? Evidence using historical identification. Public Choice, 157, 1-2: 269–286. DOI: 10.1007/s11127-012-9944-x.
5. Brandt, Mark J., Geoffrey Wetherell, PJ Henry. 2015. Changes in income predict change in social trust: A longitudinal analysis. Political Psychology, 36, 6: 761–768. DOI: 10.1111/pops.12228.
6. Beullens, Koen, Geert Loosveldt, Caroline Vandenplas, Ineke Stoop. 2018. Response rates in The European Social Survey: Increasing, decreasing, or a matter of fieldwork efforts? Survey Methods: Insights from the Field. Pobrane z: https://surveyinsights.org/?p=9673. Dostęp 12.04.2022.
7. Callens, Marloes, Geert Loosveldt. 2018. ‚Don’t Know’ Responses to Survey Items on Trust in Police and Criminal Courts: A Word of Caution. Survey Methods: Insights from the Field. Pobrane z: https://surveyinsights.org/?p=9237. Dostęp: 12.04.2022.
8. D’Hernoncourt, Johanna, Pierre-Guillaume Méon. 2012. The not so dark side of trust: Does trust increase the size of the shadow economy? Journal of Economic Behavior & Organization, 81, 1: 97–121. DOI: 10.1016/j.jebo.2011.09.010.
9. Daniele, Gianmarco, Benny Geys. 2015. Interpersonal trust and welfare state support. European Journal of Political Economy, 39: 1–12. DOI: 10.1016/j.ejpoleco.2015.03.005.
10. ESS. 2018. ESS Round 9 Source Questionnaire. Pobrane z: https://www.europeansocialsurvey.org/docs/round9/fieldwork/poland/ESS9_questionnaires_PL.pdf. Dostęp 30.08.2021.
11. Fitzgerald, Rory. 2015. Sailing in unchartered waters: structuring and documenting cross-national questionnaire design. GESIS Papers, 2015/05, 1–24.
12. Fitzgerald, Rory, Roger Jowell. 2010. Measurement equivalence in comparative surveys: the European Social Survey (ESS)—from design to implementation and beyond. In: J. A. Harkness, ed. Survey Methods in Multinational, Multiregional, and Multicultural Contexts. London: Wiley, 485–495.
13. Frick, Joachim R, Markus Grabka. 2014. Missing income data in the German SOEP: Incidence, imputation and its impact on the income distribution. SOEP Survey Papers No. 225.
14. Gorodzeisky, Anastasia, Moshe Semyonov. 2018. Competitive threat and temporal change in anti-immigrant sentiment: Insights from a hierarchical age-period-cohort model. Social Science Research, 73: 31–44. DOI: 10.1016/j.ssresearch.2018.03.013.
15. Hansen, Kirstine, Dylan Kneale. 2013. Does how you measure income make a difference to measuring poverty? Evidence from the UK. Social Indicators Research, 110, 3: 1119–1140. DOI: 10.1007/sl 1205-011 -9976-5.
16. Hariri, Jacob Gerner, David Dreyer Lassen. 2017. Income and outcomes. Social desirability bias distorts measurements of the relationship between income and political behavior. Public Opinion Quarterly, 81, 2: 564–576. DOI: 10.1093/poq/nfw044.
17. Heck, Ronald H., Scott Thomas, Lynn Tabata. 2013. Multilevel modeling of categorical outcomes using IBM SPSS. London: Routledge.
18. Herda, Daniel. 2013. Too many immigrants? Examining alternative forms of immigrant population innumeracy. Sociological Perspectives, 56, 2: 213–240. DOI: 10.1525/sop.2013.56.2.213.
19. Hershey, Douglas A, Kène Henkens, Hendrik P van Dalen. 2010. What drives retirement income worries in Europe? A multilevel analysis. European Journal of Ageing, 7, 4: 301–311. DOI: 10.1007/s10433-010-0167-z.
20. Hox, Joop J, Mirjam Moerbeek, Rens Van de Schoot. 2010. Multilevel analysis: Techniques and applications. London: Routledge.
21. Iannacchione, Vincent G. 2003. Sequential weight adjustments for location and cooperation propensity for the 1995 national survey of family growth. Journal of Official Statistics, 19, 1: 31–43.
22. Jabkowski, Piotr. 2015. Reprezentatywność badań reprezentatywnych. Analiza wybranych problemów metodologicznych oraz praktycznych w paradygmacie całkowitego błędu pomiaru. Poznań: Wydawnictwo Naukowe UAM.
23. Kaminska, Olena, Peter Lynn. 2017. Survey-based cross-country comparisons where countries vary in sample design: issues and solutions. Journal of Official Statistics, 33, 1: 123–136.
24. Kim, Jae K., Jay J. Kim. 2007. Nonresponse weighting adjustment using estimated response probability. Canadian Journal of Statistics, 35, 4: 501–514. DOI: 10.1002/cjs.5550350403.
25. Kim, Jibum, Jaesok Son, Peter K. Kwok, Jeong-han Kang, Faith Laken, Jodie Daquilanea, Hee-Choon Shin, Tom W. Smith. 2015. Trends and Correlates of Income Nonresponse: Forty Years of the US General Social Survey (GSS). Journal of Korean Official Statistics, 20, 1: 1–23.
26. Koch, Achim, Michael Blohm. 2009. Item Non-response in the European Social Survey. ASK Research & Methods, 18, 1: 45–65.
27. Kolarz, Peter, Jelena Angelis, Adam Krčál, Paul Simmonds, Vincent Traag, Martin Wain. 2017. Comparative impact study of the European Social Survey (ESS) ERIC. Brussels: Technopolis Group.
28. Krosnick, John A. 1991. Response strategies for coping with the cognitive demands of attitude measures in surveys. Applied Cognitive Psychology, 5, 3: 213–236. DOI: 10.1002/acp.2350050305.
29. Krosnick, John A., Allyson L. Holbrook, Matthew K. Berent, Richard T. Carson, W. Michael Hanemann, Raymond J. Kopp, Robert Cameron Mitchell, Stanley Presser, Paul A. Ruud, V. Kerry Smith, Wendy R. Moody, Melanie C. Green, Michael Conaway. 2002. The impact of „no opinion” response options on data quality: non-attitude reduction or an invitation to satisfice? Public Opinion Quarterly, 66, 3: 371–403. DOI: 10.1086/341394.
30. Lahtinen, Hannu, Pekka Martikainen, Mikko Mattila, Hanna Wass, Lauri Rapeli. 2019. Do Surveys Overestimate or Underestimate Socioeconomic Differences in Voter Turnout? Evidence from Administrative Registers. Public Opinion Quarterly, 83, 2: 363–385. DOI: 10.1093/poq/nfz022.
31. Lelkes, Orsolya. 2006. Knowing what is good for you: Empirical analysis of personal preferences and the “objective good”. The Journal of Socio-Economics, 35, 2: 285–307. DOI: 10.1016/j.socec.2005.11.002.
32. Lepkowski, James, Graham Kalton, Daniel Kasprzyk. 1989. Weighting adjustments for partial nonresponse in the 1984 SIPP panel. Pobrane z: http://www.asasrms.org/Proceedings/papers/1989_050.pdf. Dostęp 10/09/2021.
33. Lynn, Peter, Sabine Häder, Siegfried Gabler, Seppo Laaksonen. 2007. Methods for achieving equivalence of samples in cross-national surveys: the European Social Survey experience. Journal of Official Statistics, 23, 1: 107–124.
34. Lynn, Peter, Annette Jakle, Stephen P. Jenkins, Emanuela Sala. 2006. The Effects of Dependent Interviewing on Responses to Questions on Income Sources. Journal of Official Statistics, 22, 3: 357–384.
35. Piekut,Aneta.2019.Survey nonresponse in attitudes towards immigration in Europe. Journal of Ethnic and Migration Studies, 1–26. DOI: 10.1080/1369183x.2019.1661773.
36. Pleis, John R., James Dahlhamer. 2003. Family Income Nonresponse in the National Health Interview Survey (NHIS): 1997-2000. Paper presented at the Proceedings of the 2003 Joint Statistical Meetings.
37. Reeskens, Tim, Marc Hooghe. 2008. Cross-cultural measurement equivalence of generalized trust. Evidence from the European Social Survey (2002 and 2004). Social Indicators Research, 85, 3: 515–532. DOI: 10.1007/s11205-007-9100-z.
38. Riphahn, Regina T., Oliver Serfl. 2005. Item non-response on income and wealth questions. Empirical Economics, 30, 2: 521–538. DOI: 10.1007/s00181-005-0247-7.
39. Schräpler, Jörg-Peter. 200). Respondent behavior in panel studies: A case study for income nonresponse by means of the German Socio-Economic Panel (SOEP). Sociological Methods & Research, 33, 1: 118–156. DOI: 10.1177/0049124103262689.
40. Schräpler, Jörg-Peter. 2006. Explaining Income Nonresponse – A Case Study by means of the British Household Panel Study (BHPS). Quality & Quantity, 40, 6: 1013–1036. DOI: 10.1007/s11135-005-5429-z.
41. Schuman, Howard, Stanley Presser. 1996. Questions and answers in attitude surveys: Experiments on question form, wording, and context. London: Sage.
42. Sicinski, Andrzej. 1970. „Don’t Know” Answers in Cross-National Surveys. The Public Opinion Quarterly, 34, 1: 126–129. DOI: http://www.jstor.org/stable/2747891.
43. Skelton, Vincent C. 1963. Patterns behind “Income Refusals”. Journal of Marketing, 27, 3: 38–41. DOI: 10.1177/002224296302700308.
44. Snijders, Tom A.B., Roel J Bosker. 2011. Multilevel analysis: An introduction to basic and advanced multilevel modelling. London: Sage.
45. Zhu, Jian-Hua. 1996. ‘I don’t know’ in public opinion surveys in China: Individual and contextual causes of item non-response. Journal of Contemporary China, 5, 12: 223–244. DOI: 10.1080/10670569608724251.

Go to article

Authors and Affiliations

Piotr Jabkowski
1
ORCID: ORCID
Aneta Piekut
2
ORCID: ORCID
  1. Uniwersytet im. Adama Mickiewicza w Poznaniu
  2. University of Sheffield, UK

This page uses 'cookies'. Learn more