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Abstract

Ile czasu potrzebuje przedmiot wrzucony do rzeki, by płynąc z prądem, dotrzeć do określonego miejsca? O coraz bardziej złożonych modelach tego pozornie prostego zagadnienia rozmawiamy z prof. Ianem Guymerem z Uniwersytetu w Sheffield

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Authors and Affiliations

Ian Guymer
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Abstract

Pod koniec XX w. dzięki wykorzystaniu metod fizycznych ludzkość uzyskała możliwość wykonywania dokładnych pomiarów czasu minionego za pomocą niezwykle czułych urządzeń.

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Authors and Affiliations

Zbigniew Jan Czupyt
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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.
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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.

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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
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Abstract

In the contemporary world, where globalization and industrialization are progressing, there are no large cities that do not generate noise. Noise is usually connected with industrial areas, airports, circulation spaces or city centres. However, it is increasingly felt in places that have previously been associated with peace and quiet, such as suburban housing estates, recreational areas, urban forests, and parks. Noise penetrates public space, robbing this landscape of silence, pleasant sounds or positive sounds. The negative impact of noise on the life processes of humans and animals is worrying. Sound quality should be treated as an element of landscape quality, therefore it should be considered in planning processes or urban space development projects. The aim of this paper is to present an analysis of the soundscape in city space and of the level of noise in Centralny Park in Olsztyn, Poland. Guidelines were also drawn up for the proper management of park space in terms of reducing noise impact, and a model (recommendation) for analysed areas was formulated. The study consisted of:
– measurements of sound pressure levels (SPL) at selected points in two periods,
– interviews with park users and the preparation of a mental map,
– preparing a design scheme for a redesign of the park.
The results confirmed the difference between SPL in the leafless and leafy period. They also showed a clear relationship between the perception of sounds and well-being in the park.
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Authors and Affiliations

Agnieszka Jaszczak
1
ORCID: ORCID
Ewelina Pochodyła
2
ORCID: ORCID
Beata Dreksler
3
ORCID: ORCID

  1. University of Warmia and Mazury in Olsztyn Department of Landscape Architecture Bioeconomy Research Institute, Kaunas, Lithuania Vytautas Magnus University, Lithuania
  2. University of Warmia and Mazury in Olsztyn Department of Landscape Architecture
  3. American University of Beirut, Lebanon Department of Landscape Design and Ecosystem Management
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Abstract

Jednym z podstawowych celów realizacji sondaży o charakterze porównawczym jest wnioskowanie o międzykulturowych różnicach opartych na pomiarze pewnych konstruktów latentnych. Porównania takie są uzasadnione, jeśli tylko owe konstrukty mierzą w każdym kraju to samo oraz w taki sam sposób. Celem tego artykułu jest weryfikacja hipotezy o ekwiwalentności pomiaru skali zaufania politycznego w dwudziestu krajach uczestniczących w siódmej rundzie Europejskiego Sondażu Społecznego. Analiza stopnia dopasowania modeli pomiarowych opartych na równaniach strukturalnych pozwoliła przyjąć hipotezę o konfiguralnej oraz metrycznej ekwiwalentności pomiaru skali zaufania politycznego. Jednocześnie odrzucono hipotezę o pełnej inwariancji skalarnej tego konstruktu, przy czym najbardziej problematyczny okazał się pomiar wskaźnika zaufania do systemu prawnego. Na zakończenie ukazano możliwości wnioskowania o międzykrajowych różnicach w poziomie zaufania politycznego, pomimo odrzucenia hipotezy o pełnej inwariancji pomiarowej tego konstruktu.
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Authors and Affiliations

Piotr Jabkowski
ORCID: ORCID

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