Item Metadata as Controls for
            <i>Ex Post</i>
            Harmonization of International Survey Projects

Kołczyńska, Marta; Slomczynski, Kazimierz M.

doi:10.1002/9781118884997.ch46

Cited by 13 publications

(15 citation statements)

References 17 publications

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“…It can hardly be used when there is much diversity in sources and contexts (De Jonge et al, 2017). Stretchingused by the SDR project (Slomczynski, Tomescu-Dubrow, Jenkins et al, 2016;Kolczynska and Slomczynski, 2019;Kwak, 2020) appears to be the most appropriate method.…”

Section: Data Collectionmentioning

confidence: 99%

How to combine and analyze all the data from diverse sources: a multilevel analysis of institutional trust in the world

et al. 2021

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Accumulation of knowledge is central to science in general and certainly to social science. However, scholars who want to perform cross-national comparative research face several issues. They rely on data provided by international survey projects like the Barometers, the Values Survey, the Social Surveys and other regional survey projects.The questions used to measure the same concepts vary in terms of question wording, answer scales used and specific object or focus. They also vary within survey projects as well as between projects, between countries and over time. In addition, each project does not cover all the countries over all the period of interest. Few projects aim at an international coverage; some are conducted yearly, others in different waves covering varying periods. Some regionsfor example, the former soviet republics (Oleksiyenko, 2017) --are under covered if we rely on only one international survey project. These observations are very similar to those put forward by Tomescu-Dubrow and Slomczynski (2016) to introduce the Survey Data Recycling (SDR) project.It is difficult to list all the restrictions that researchers acknowledge when using data produced by the various international and regional survey projects. Authors tend to restrict themselves to one survey project and use only the question(s) asked in the same way in the countries where the data are available over all the period of interest (Catterberg and Moreno, 2006; Schneider, 2017, Tomescu-Dubrow andSlomczynski, 2016). Researchers sometimes run analyses on several surveys but separately (Tomescu-Dubrow and Slomczynski, 2016). This restricts substantially the possibilities for cross-national and longitudinal comparison. The teams responsible for international survey projects devote much attention to harmonization ex ante. They try to make sure that data will be comparable between countries and over time for their specific projects. However, the context of the different countries is not always comparable. In the end, only few measures end up being similar for some of the countries of interest for a short period for a given project. In such

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Section: Data Collectionmentioning

confidence: 99%

How to combine and analyze all the data from diverse sources: a multilevel analysis of institutional trust in the world

et al. 2021

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“…This design was chosen in order to reconstruct trends in church attendance fully and comprehensively, since any new edition of the study provides an updated picture of the population and thereby improves our understanding of change at the aggregate level (Duncan and Kalton 1987). The issue of data quality (Blasius and Thiessen 2012;Groves 1989;Harkness 1999) has not been tackled directly; however, given the specific selection criteria we applied, the data quality of the selected studies, despite some heterogeneity across studies, rounds and countries, is well known in the scientific community and well assessed in the literature (Kołczyńska and Slomczynski 2019;Maineri et al 2017;Oleksiyenko et al 2019). Based on these criteria, five repeated cross-sectional studies were chosen:…”

Section: The Selection Of Studiesmentioning

confidence: 99%

Church Attendance and Religious change Pooled European dataset (CARPE): a survey harmonization project for the comparative analysis of long-term trends in individual religiosity

et al. 2020

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Despite the long-lasting interest in religious change, debates on the topic have been heated and are still far from being settled. In order to provide a reliable data source through which to study these dynamics, the CARPE project harmonizes well-known international surveys containing items concerning religiosity (the ESS, Eurobarometer, EVS, ISSP and WVS). This makes it possible to broaden the available observation window, both across countries and over time. Moreover, the opportunities this provides for comparing different survey programmes also enable researchers to analyse the consistency of the results, minimizing the impact of random fluctuations and providing useful information with respect to the degree of confidence which can be placed on the relevant estimates. The main focus of this cumulative approach is the variable regarding church attendance, which has been harmonized in various ways. All in all, the CARPE dataset contains figures of religious practice for 45 countries spanning the period of 1970–2016 and derived from 1665 national surveys. This results in a sample of approximately 1.8 million individual observations. The aim of this contribution is to present the dataset’s composition, the harmonization procedure adopted, the strategy used to combine the single datasets and the reliability tests which have been performed. Finally, some possible applications of the CARPE dataset will be introduced.

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“…We follow the SDR analytic framework (for an outline, see Slomczynski & Tomescu-Dubrow, 2018) and account for methodological differences present in the original formulation of the trust questions (e.g. Slomczynski et al, 2016; also, Kołczyńska & Slomczynski, 2018) and for differentiation in survey data quality (for operational definition of survey quality in SDR, see Kołczyńska & Schoene, 2018; Slomczynski & Tomescu-Dubrow, 2018; Oleksiyenko et al, 2018) to calculate the best estimate of mean values of trust in each of the political institutions (see the online Supplement A for specifics; also, Kwak & Slomczynski, 2019).…”

Section: Data and Variablesmentioning

confidence: 99%

Youth, Institutional Trust, and Democratic Backsliding

Kwak

Tomescu-Dubrow

Slomczynski

et al. 2020

American Behavioral Scientist

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In recent decades, many countries ranging from quasidemocratic regimes to well-established democracies have faced democratic backsliding. In this study, we draw on Foa and Mounk and other related literature to examine the effects of regime delegitimation on democratic backsliding, focusing on youth’s trust in political institutions—parliament, legal systems, and political parties—relative to trust of the older population. We use an unbalanced panel data set that combines a country-year indicator of liberal democracy from the Varieties of Democracy project with aggregate survey-based measures of absolute and relative institutional trust from the Survey Data Recycling database; the data set covers 46 countries from 2009 to 2017. We find that the ratio of youth’s institutional trust to that of older persons has a substantive effect on the quality of liberal democracy in the future, and that the effect is amplified by the relative size of the youth population.

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Item Metadata as Controls for Ex Post Harmonization of International Survey Projects

Cited by 13 publications

References 17 publications

How to combine and analyze all the data from diverse sources: a multilevel analysis of institutional trust in the world

How to combine and analyze all the data from diverse sources: a multilevel analysis of institutional trust in the world

Church Attendance and Religious change Pooled European dataset (CARPE): a survey harmonization project for the comparative analysis of long-term trends in individual religiosity

Youth, Institutional Trust, and Democratic Backsliding

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