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Deviant interviewer behavior is a potential hazard of interviewer-administered surveys, with interviewers fabricating entire interviews as the most severe form. Various statistical methods (e.g., cluster analysis) have been proposed to detect falsifiers. These methods often rely on falsification indicators aiming to measure differences between real and falsified data. However, due to a lack of real-world data, empirical evaluations and comparisons of different statistical methods and falsification indicators are scarce. Using a large-scale nationally representative refugee survey in Germany with known fraudulent interviews, this study tests, evaluates, and compares statistical methods for identifying falsified data. We investigate the use of new and existing falsification indicators as well as multivariate detection methods for combining them. Additionally, we introduce a new and easy-to-use multivariate detection method that overcomes practical limitations of previous methods. We find that the vast majority of used falsification indicators successfully measure differences between falsifiers and nonfalsifiers, with the newly proposed falsification indicators outperforming some existing indicators. Furthermore, different multivariate detection methods perform similarly well in detecting the falsifiers.

Seit Kriegsbeginn sind mehr als eine Million Menschen aus der Ukraine nach Deutschland geflohen. Erste repräsentative Erkenntnisse über deren Lebenssituation und Zukunftspläne ermöglicht die Studie „Geflüchtete aus der Ukraine in Deutschland (IAB-BiB/FReDA-BAMF-SOEP-Befragung)“, eine gemeinsame Studie des Instituts für Arbeitsmarkt- und Berufsforschung (IAB), des Bundesinstituts für Bevölkerungsforschung (BiB), des Forschungszentrums des Bundesamts für Migration und Flüchtlinge (BAMF-FZ) und des Sozio-oekonomischen Panels (SOEP) am Deutschen Institut für Wirtschaftsforschung (DIW Berlin). Es wurden für diese Studie 11.225 geflüchtete Ukrainerinnen und Ukrainer in der Zeit zwischen August und Oktober 2022 befragt.

Survey data are important for establishing new insights in many disciplines such as sociology, economics, and others. This chapter provides a broad overview of statistical methods for identifying interviewer falsification and demonstrating promising statistical identification strategies using data from a large-scale refugee survey in Germany that includes confirmed falsifications. In practice, non-statistical strategies for detecting falsifications are usually part of standard quality control methods. Some approaches are used during the field period, while others are used after all interviews have been conducted. Interview monitoring, mainly applied in telephone surveys, is another commonly used procedure for identifying falsifiers, which also serves as a deterrent to interviewers. To illustrate the statistical identification tools, the following indicators are considered: acquiescent response style, extreme response style, interview duration, middle response style, recency effects, semi-open responses, and stereotyping. Statistical identification methods have been demonstrated to be effective and are becoming increasingly popular tools for identifying falsified interviews in surveys.

The OECD is one of the key players in global education policy advice, informing education governance reforms around the globe with the PISA test. At the same time, it is part of the edu-business network comprised of companies, philanthropies, consulting agencies and think tanks profiting from educational governance reforms and large-scale testing. In order to exert influence on national educational reforms, different types of complementary expertise and collaborations between different types of actors must be coordinated. To analyze this form of collaboration between different actors and to map the global edu-business and global policy advisor networks having emerged around the OECD’s PISA-tests, we make use of a combination of Habitus-Field Theory and Social Network Theory. We introduce the concepts of boundary-spanning actors and field-transcending social capital and apply our concepts to a two-level network analysis to investigate the embeddedness of the OECD in different social fields and the global field of power. The first layer is based on official collaborations among organizational actors situated in different sectors of the field of power. The second layer comprises of individual collaborations such as scientific cooperation, board interlocks and multiple affiliations. Furthermore, we look at network closure and density to investigate the exclusion of competing actors from taking part in the global edu-business. Our findings indicate that the OECD draws on experts and actors located in different fields to exert influence on national educational reforms. Finally, the global network of policy advisors is able to coordinate the different forms of expertise by installing a system of patronage, consisting of a small number of key players and large numbers of organizations and individuals that are needed to set education reforms in motion but are excluded from the core of the collaboration network.