This study examines four potential drivers of corruption using a large administrative data set. These potential drivers have been previously tested and confirmed in experimental game studies or studies that used aggregated macro data. In contrast to these previous studies, the dataset used in this study comprises real individual data that classifies whether a public servant was dismissed due to corruption or not. The data were compiled from various sources referring to the Federal District of Brazil. The relative number of corruption cases is small compared to the number of cases classified as not corrupt. To account for the rare event property of the data, two regression techniques were applied to address the infrequency of corruption events in the dataset. The analysis reveals that an increase in salary and disruptions of social relations with public officials decrease the probability of corruption. Conversely, an increase in private business connections or an expansion of a public servant's discretionary power makes corruption more likely. While these results coincide with findings from previous studies, it is essential to interpret them with caution due to the specific properties and limitations of administrative data.

The theoretical framework for considering the impact of economic freedom on corruption and the shadow economy can be traced back to early roots in economic and social theory. In this framework, economic freedom reduces corruption and activities in the shadow economy because it abolishes incentives for such crimes. Empirical studies find a rather robust decreasing effect of economic freedom on corruption and the shadow economy, but only when overall indices of economic freedom are applied. When subcomponents of the overall indices are used in empirical research or when short- and long-term effects are considered, economic freedom can lead to an increase in such crimes. The measured impact of economic freedom depends on the operationalization and the data. Most empirical results, however, are in accordance with propositions made by economic theories.

The excellence and integrity of Rationality and Society depends on the dedication and expertise of volunteer reviewers who evaluate submissions for their contribution to the discipline, soundness of research, writing clarity, and general interest. With apologies to any inadvertently omitted reviewers, the editors of Rationality and Society extend sincere thanks to the following reviewers for providing highly valuable comments on papers submitted in 2020 and 2021:

Der Begriff „digitale Daten“ ist unprazise, weil in den Sozialwissenschaften spatestens seit den 1960ern Daten nicht nur digital erhoben, verarbeitet und analysiert wurden, sondern in der Forschungspraxis auch oft parallel analoge und digitale Daten erhoben wurden. Am Beispiel der quantitativen Sozialforschung scharft der Beitrag den Begriff der „digitalen Daten“ durch die Unterscheidung zwischen forschungsinduzierten, klassischen und neuartigen prozessproduzierten Daten („Big Data“). Auf dieser Basis zeigen wir, dass klassische Modelle der empirischen Sozialforschung zur Beurteilung der Datenqualitat und Selektivitaten von prozessproduzierten Daten – wie etwa das sogenannte Bick-Muller-Modell – auch auf neuartige prozessproduzierte Daten ubertragen konnen, deren Besonderheit es ist, dass sie meist im Kontext des Web 2.0 entstehen und i.d.R. ausschlieslich digital sind. Mit Hilfe des Bick-Muller-Modells lassen sich die spezifischen Starken und Schwachen von neuartigen prozessproduzierten Daten aufzeigen. Allgemein lasst sich festhalten, dass Web 2.0-Daten blinde Flecken aufweisen, insofern dass sowohl im nationalstaatlichen Rahmen, als auch im globalen Kontext grose Teile der Bevolkerung keinerlei digitale Spuren hinterlassen. Diese digitalen Ausschlusse folgen weitgehend herkommlichen Mustern sozialer Ungleichheit: Im Gegensatz zu jungen, hochgebildeten Mannern aus der oberen Mittelschicht in Grosstadten des globalen Nordens hinterlassen altere, geringgebildete Arbeiterfrauen aus dem landlichen Afrika praktisch keinerlei digitale Spuren. Verwendet man Web 2.0-Daten in der Forschung, besteht damit die Gefahr, dass keinerlei, unvollstandige oder verzerrte Informationen uber die Personenkreise, die am starksten sozial benachteiligt werden, gewonnen werden. Weiterhin kommt es zu einer Machtverschiebung hinsichtlich Dateneigentumerschaft vom Staat und der Bevolkerung hin zu multinationalen Konzernen. Dies heist aber nicht, dass Web 2.0-Daten nicht fur die Forschung geeignet sind. Vielmehr werden durch die Anwendung des Bick-Muller-Modells verschiedene analoge und digitale Datensorten miteinander vergleichbar, was wichtig ist, weil – wie die Analyse zeigt – sich nicht allgemein, sondern nur in Bezug auf eine spezifische Forschungsfrage zeigen lasst, welche Daten besser, weniger oder gar nicht geeignet sind.

In this study, we examine volunteer firefighters' inclination toward a "code of silence". The likelihood of not reporting fellow group members' deviant behavior is increased by group standards such as loyalty, but this comes at the cost of violating the law. A factorial survey was conducted with volunteer firefighters in Germany to test the influence of several factors in determining whether whistleblowing or conforming to a "code of silence" was more likely. The results show that the question of whether a firefighter will disclose a deviant action depends on the severity (e.g. the forcefulness) of the team's or the team member's wrongdoing. External threats turn out to have a significant opposite effect and foster the "code of silence". Our results suggest that the factors that influence volunteer firefighters in this regard are similar to those that previous studies on the code of silence postulate as influencing professional working groups such as the police.

Are Catholics more inclined to violate social norms than Protestants? A tentative answer is yes due to this confession's attitude towards absolution of sins. Opportunities existed for Christians around Reformation times, for example as sales of indulgences. Catholics and Protestants arguably differed historically in their understanding of whether penitence is feasible or not, resulting in different conditions under which Catholics and Protestants decide in situations of social exchange. This is illustrated by ethical game theory and exemplified by historical data. The analysis points to the tentative suggestion that religious socialisation can affect social payoffs of crime and social trust in a long-term perspective.

"Die Qualitat von Big Data. Entwicklung, Probleme und Chancen der Nutzung von prozessgenerierten Daten im digitalen Zeitalter". The paper introduces the HSR Forum on digital data by discussing what big data are. The authors show that big data are not a new type of social science data but actually one of the oldest forms of social science data. In addition, big data are not necessarily digital data. Regardless, current methodological debates often assume that "big data" are "digital data." The authors thus also show that digital data have a big drawback concerning data quality because they do not cover the whole population - due to so-called digital divides, not everybody is on the internet, and who is on the internet, is socially structured. The result is a selection bias. Based on this analysis, the paper concludes that big data and digital data are data like any other type of data - they have both advantages and specific blind spots. So rather than glorifying or demonising them, it seems much more sensible to discuss which specific advantages and drawbacks they have as well as when and how they are better suited for answering specific research questions and when and how other types of data are better suited - these are the questions that are addressed in this HSR Forum.

In the digital age, new data types have become available that can, potentially, be used in social science research. Besides data that were originally created for scientific purposes (research-elicited data), administrative mass data (traditional-type big data) and data from digital devices (new-type big data) have become more and more relevant for research processes. Both data types can be subsumed under the term "big data." In this paper, we scrutinize the quality of administrative mass data on corruption in contrast to research-elicited data (e.g., survey data). Since data quality is crucial for the measurement of a social phenomenon such as corruption, we pose the question of how a social phenomenon can be measured by means of data from these different sources. As a first step, we refer to the so-called Bick-Mueller-Model. It was developed in the 1980s for observing the special features and particularities of administrative mass data (traditional-type big data). We contrast this model with the so-called Error-Approach that is typically applied in survey research. In order to account for new trends in data generation and application, we show the progress that has been made since Bick and Mueller introduced their model and discuss new features of digitalism and new technologies. We conclude that the features of the so-called Bick-Mueller are useful for tackling the particularities of administrative data and also - to some degree - new-type big data. The "error" perspective that is inherent both in the classical survey research and in the so-called Bick-Mueller model also applies to new-type big data when it comes to assessing their quality. Moreover, it is possible that the data from these different sources can complement each other. For this, researchers must be aware of the fact that neither data source actually measures corruption directly. For answering specific research questions, it is crucial to consider the advantages and disadvantages of using specific data types.

Korruption tritt in unserer Gesellschaft in unterschiedlichen Formen und in verschiedenen Bereichen auf. Wer sich mit der Frage beschäftigt, was Korruption ist, wird in der wissenschaftlichen Forschung auf viele Antworten treffen. Dieses Buch gibt einen Überblick über die wichtigsten Antworten in komprimierter, leicht verständlicher Form und geordnet nach Disziplinen, die sich mit diesem Thema beschäftigen: Ökonomie, BWL/Managementwissenschaft, Strafrecht, Privatrecht, Geschichtswissenschaft, Verwaltungswissenschaft, Politikwissenschaft, Soziologie, Psychologie und Kriminologie. Es genügt aber nicht, bei einer fachdisziplinären Definition von Korruption stehen zu bleiben. Insbesondere dann, wenn es um die Bekämpfung von Korruption oder den Aufbau von korruptionsfreien gesellschaftlichen Strukturen und Beziehungen geht, ist eine transdisziplinäre Analyse unabdingbar.

The illicit sale of prescription drugs for enhancing cognitive performance is a criminal act which has hardly been studied although the consumption of these drugs by healthy people has numerous negative individual and social consequences. In this study, we scrutinize the decision to sale those drugs based on assumptions of various criminological rational choice models, self-control theory, social norms, as well as the Model of Frame Selection (MFS) and the Situational Action Theory (SAT). Thereby, we also consider interactions between instrumental incentives, self-control and norms. To investigate decisions regarding the illegal sale of performance enhancing drugs, we used a web-based survey among students at four German universities (N=1,698). Each respondent received randomly one out of 900 vignettes, in each case describing a hypothetical sales situation concerning the illegal and financially rewarding transmission of medications to enhance concentration between students. The descriptions have been randomly varied with respect to the sales profits and the severity of punishments and their respective probabilities. Moreover, the degree of self-control and internalized norms regarding illegal sales have been assessed. The results, that are derived from double hurdle models, show that, especially, internalized norms as well as the severity of punishment reduce the willingness of selling, while low self-control and increasing profits increase this willingness. In addition, a negative interaction effect between low self-control and the severity of punishment shows that a more severe punishment leads to more deterrence when self-control is lower (respectively that with more sever punishments, the impact of self-control decreases). Although the results support the theoretical assumptions only partially, we can show that internalized norms significantly influence the perception of criminal behavior while the benefits of such behavior and self-control seem to operate in a downstream deliberation process.

This paper investigates the ways in which cost-benefit considerations influence entrepreneurs' propensity to engage in corruption. It further investigates how the effects of these considerations are fostered by entrepreneurs' adherence to legal standards (norm internalization) and the degree to which they ponder the pros and cons of an ethically challenging business situation (deliberation). In order to deduce the causal effects and reduce social desirability bias, this study uses a vignette-based factorial survey. A multi-level analysis of 740 vignettes from 148 entrepreneurs indicates that the propensity of entrepreneurs to participate in acts of corruption is driven by expected economic gains and a high probability that the corruption will be successful. The impact of these factors increases when entrepreneurs have a higher tendency to ponder the pros and cons of an opportunity to commit corruption. However, the probability of detection does not affect their propensity for corruption.

The illicit sale of prescription drugs for enhancing cognitive performance is a criminal act which has hardly been studied although the consumption of these drugs by healthy people has numerous negative individual and social consequences. In this study, we scrutinize the decision to sale those drugs based on assumptions of various criminological rational choice models, self-control theory, social norms, as well as the Model of Frame Selection (MFS) and the Situational Action Theory (SAT). Thereby, we also consider interactions between instrumental incentives, self-control and norms. To investigate decisions regarding the illegal sale of performance enhancing drugs, we used a web-based survey among students at four German universities (N=1,698). Each respondent received randomly one out of 900 vignettes, in each case describing a hypothetical sales situation concerning the illegal and financially rewarding transmission of medications to enhance concentration between students. The descriptions have been randomly varied with respect to the sales profits and the severity of punishments and their respective probabilities. Moreover, the degree of self-control and internalized norms regarding illegal sales have been assessed. The results, that are derived from double hurdle models, show that, especially, internalized norms as well as the severity of punishment reduce the willingness of selling, while low self-control and increasing profits increase this willingness. In addition, a negative interaction effect between low self-control and the severity of punishment shows that a more severe punishment leads to more deterrence when self-control is lower (respectively that with more sever punishments, the impact of self-control decreases). Although the results support the theoretical assumptions only partially, we can show that internalized norms significantly influence the perception of criminal behavior while the benefits of such behavior and self-control seem to operate in a downstream deliberation process.