Antonia Velicu’s research while affiliated with University of Zurich and other places
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While publication bias has been widely documented in the social sciences, it is unclear whether the problem aggravated over the last decades due to an increasing pressure to publish. We provide an in-depth analysis of publication bias over time by creating a unique data set, consisting of 12340 test statistics extracted from 571 papers published in 1959-2018 in the Quarterly Journal of Economics. We, further, develop a new methodology to test for discontinuities at the thresholds of significance. Our findings reveal, that, first, in contrast to our expectations, publication bias was already present many decades ago, but that, second, bias patterns notably changed over time. As such, we observe a transition from bias at the 10 percent to bias at the 5 percent significance level. We conclude that these changes are influenced by increasing computational possibilities as well as changes in the acceptance rates of scientific top journals.
The persistent “leaky pipeline”, i.e. women remaining underrepresented in advanced academic roles, often links to the adverse impact of parenthood on women’s careers compared to men’s. This study delves into how the struggle to balance academic success and family life might be pushing female scientists out of academia, and how the less-studied concept of homogamy - here, the forming of heterosexual relationships between individuals with the same profession - influences academic careers. Drawing on data from the 2021 “Academic career, partnership, and family” survey by swissuniversities, this research pursues two objectives: assessing whether homogamous partnerships help mitigating career challenges faced by mothers, and investigating the broader impact of homogamy on academic careers and work-life balance. The findings show that homogamy is common among Swiss scientists. Homogamous women, especially when their partner works in the same institution, perceive parenthood as posing fewer career obstacles. Conversely, male scientists in such relationships state the opposite. Additionally, homogamous couples report benefiting from stimulating discussions and partner support while encountering greater mobility constraints. This research offers insights into how homogamy affects academic careers, providing a nuanced understanding of how academics navigate their pursuit of successful careers alongside personal lives.
The persistent “leaky pipeline”, i.e. women remaining underrepresented in advanced academic roles, often links to the adverse impact of parenthood on women’s careers compared to men’s. This study delves into how the struggle to balance academic success and family life might be pushing female scientists out of academia, and how the less-studied concept of homogamy - here, the forming of heterosexual relationships between individuals with the same profession - influences academic careers. Drawing on data from the 2021 “Academic career, partnership, and family” survey by swissuniversities, this research pursues two objectives: assessing whether homogamous partnerships help mitigating career challenges faced by mothers, and investigating the broader impact of homogamy on academic careers and work-life balance. The findings show that homogamy is common among Swiss scientists. Homogamous women, especially when their partner works in the same institution, perceive parenthood as posing fewer career obstacles. Conversely, male scientists in such relationships state the opposite. Additionally, homogamous couples report benefiting from stimulating discussions and partner support while encountering greater mobility constraints. This research offers insights into how homogamy affects academic careers, providing a nuanced understanding of how academics navigate their pursuit of successful careers alongside personal lives.
This research analyzes the effectiveness of the list experiment and crosswise model in measuring self-plagiarism and data manipulation. Both methods were implemented in a large-scale survey of academics on social norms and academic misconduct. As the results lend little confidence about the effectiveness of the methods, researchers are best advised to avoid them or, at best, to handle them with care.
The Zurich Survey of Academics is a large-scale and representative web survey among scientists at universities in Switzerland, Germany, and Austria (DACH region). The survey was conducted in 2020 and includes N=15,972 scientists from 236 universities. The survey is motivated by recent developments, such as the significant increase of team work in science and problems of how to organize fair and sustainable collaborations. It also reflects recent discussions around the replication crisis, problems of scientific integrity, and the apparently increasing pressures in scientific work. The aim of the survey is to obtain in-depth insights from researchers in Europe. The survey includes a number of new measurements, such as vignettes, factorial surveys, behavioral games, an Implicit Association Test on misconduct, indirect questioning techniques for eliciting scientific misconduct, randomized survey experiments on selective publishing behavior, and more. These measurements are applied to elicit, among others, selfish versus prosocial behavior of scientists, authorship norms, and provisions of collective goods in science. This document describes the most innovative elements of the survey and the core item batteries, questions, games, behavioral tasks, and how permission to record linkage with individual bibliometric data was obtained. In addition, the specifics of the sampling and data cleaning are described. The document serves as a companion for informing about the questionnaire and the data for data analysts, interested researchers, reviewers and those interested in learning more about the specifics of the survey contents and the data structure. The document further entails links to additional material and documents, such as the codebook, ethics approval, and data protection. The survey is part of the larger-scale SNF/ERC Starting grant project “Social Norms, Cooperation and Conflict in Scientific Collaborations”.
Survey respondents tend to present themselves in a more favorable light, especially when being asked unpleasant questions. This so-called social desirability bias introduced by sensitive questions often distorts survey responses. As a remedy research draws on indirect questioning formats that aim to protect respondents’ privacy and ensure their anonymity. Two prominent examples of such techniques are the Crosswise Model (CM) and the Item Count Technique (ICT). Both methods follow unconventional structures using group answers or known distributions to mask individual answer but that also require long, complex and dense instructions. Previous research has suggested that ICT and CM produce more truthful answers, however they impose a higher cognitive burden on respondents. Although, it is commonly believed that respondents fully understand and follow these more demanding instructions, recent research suggests that this is not always the case. To further investigate this notion, I conduct a meta-analysis of the ICT and CM and analyze the instructions of these methods to answer two core questions: First, how do the implementations of the Item Count Technique and the Crosswise Model differ across studies? Second, how do specific characteristics (i.e., the instruction) of the techniques affect their performance? The meta-analysis indicates mixed results on the performance of the techniques. The CM tends to perform better than the ICT. ICT works best when asked in face-to-face interviews, the sensitive item phrased as a socially undesirable one, and the non-sensitive items chosen from the same contextual background. ICT instructions with too many words and not many word repetitions appear to have a negative influence on its outcome. The results of this research have implications for researchers and practitioners working with these techniques, but also for the broader field measuring and analyzing sensitive characteristics in surveys. Keywords: Item Count Technique; Crosswise Model; Meta-Analysis; Cognitive Burden; Survey Methodology; Instructions
Citations (3)
... Fourth, we discarded the list experiment results because the implementation was deficient in several respects, which we cannot adequately explain. The decision is supported by similar challenges faced in other surveys on integrity [99]. Fifth, we changed the reported regression model to one not preregistered to ease interpretation, noting that results under the preregistered model are similar. ...
... Whenever this is not the case, one or several problems may occur. For example, the recurrent collaboration problem of fairness (e.g., Berlemann and Haucap, 2015;Bozeman et al., 2016;Johann et al., 2020) can be well-explained in terms of club theory: In the production and use of the club good, an appropriate reciprocity of input and output by and for everyone must be guaranteed. However, in a research team, there are also incentives for participants to limit their input at the expense of others or to take advantage of others. ...
... Authors are likely to suspect that reviewers are still expecting to see significant results that support hypotheses. For instance, in the Zurich Survey of Academics (Rauhut et al., 2020), when asked how often manuscripts are rejected by editors because the results have not been statistically significant, nearly two-thirds (64%) of scientists answered that this occurs in 50% of the cases, or even more. About as many researchers (61%) further assumed that it is unlikely or very unlikely that the review process results in the detection of manipulated data (Rauhut et al., 2020). ...
