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on Sociology of Economics |
| By: | Donna K. Ginther; Shulamit Kahn; Daria Milakhina |
| Abstract: | Using data from Academic Analytics 2009-2022 linked to publications and multiple approaches of identifying race, we examine gender and racial/ethnicity differentials in promotion of economists in economics and non-economics departments. Results are mixed. The share of Black economists remains at 3%. Huge gender penalties in promotion to both associate and full not explained by productivity continue in economics departments. There are no gender penalties in promotion to associate for economists in non-economics departments, although some in promotion to full. There are hardly any significant racial penalties in promotion to either rank, although statistical significance is difficult with such small samples. |
| JEL: | J15 J16 J4 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33538 |
| By: | Asanov, Anastasiya-Mariya; Asanov, Igor; Buenstorf, Guido; Kadriu, Valon; Schoch, Pia |
| Abstract: | Doctoral dissertations provide evidence about research practices in early career-stage research. We examine reporting bias by manually collecting over 94, 000 test statistics from a random sample of German dissertations and their follow-up papers worldwide. We observe selective reporting, as only a fraction of the tests in the dissertations is reported in follow-up papers. Unexpectedly, we find no increase in reporting bias in follow-up papers compared to dissertations nor, generally, reporting bias in dissertations or papers. Self-selection into higher-impact journals based on statistical significance may reconcile our finding of selective yet "unbiased" reporting with prior evidence suggesting pervasive reporting bias. |
| Keywords: | research transparency, reporting bias, higher education, young researchers |
| JEL: | A14 A23 C12 I23 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:i4rdps:225 |
| By: | Nicklisch, Andreas; Bock, Olaf; Lauer, Thomas |
| Abstract: | We analyse the availability of source data of experimental data in a sample of highly respected economic journals. We test whether publication strategies of journals have an effect for the publication of data. The results for the sample of journals we investigated indicate a large variety of publication patterns. Even mandatory publication of experimental data leads in many cases to sources which are only available upon request. Thus, transparency and replicability of experimental results currently depend to a large extend on the good will of the journals and the stringency by which editors follow the research data availability policies. |
| Keywords: | experimental results, data availability, repositories |
| JEL: | C91 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:uhhwps:316437 |
| By: | Heesen, Remco; Bright, Liam Kofi |
| Abstract: | It might seem obvious that the scientific process should not be biased. We strive for reliable inference, and systematically skewing the results of inquiry apparently conflicts with this. Publication bias—which involves only publishing certain types of results—seems particularly troubling and has been blamed for the replication crisis. While we ultimately agree, there are considerable nuances to take into account. Using a Bayesian model of scientific reasoning we show that a scientist who is aware of publication bias can (theoretically) interpret the published literature so as to avoid acquiring biased beliefs. Moreover, in some highly specific circumstances she might prefer not to bother with policies designed to mitigate or reduce the presence of publication bias—it would impose a cost in time or effort that she would not see any benefit in paying. However, we also argue that science as a social endeavour is made worse off by publication bias. This is because the social benefits of science are largely secured via go-between agents, various non-experts who nonetheless need to make use of or convey the results of scientific inquiry if its fruits are to be enjoyed by society at large. These are unlikely to be well-informed enough to account for publication bias appropriately. As such, we conclude, the costs of having to implement policies like mandatory pre-registration are worth imposing on scientists, even if they would perhaps not view these costs as worth paying for their own sake. The benefits are reaped by the go-between agents, and we argue that their perspective is quite properly favoured when deciding how to govern scientific institutions. |
| Keywords: | replication crisis; philosophy of statistics; publication bias; preregistration; filedrawer effect; REF fund |
| JEL: | C1 |
| Date: | 2025–04–30 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:127420 |
| By: | Cong William Lin; Wu Zhu |
| Abstract: | Large Language Models (LLMs), such as ChatGPT, are reshaping content creation and academic writing. This study investigates the impact of AI-assisted generative revisions on research manuscripts, focusing on heterogeneous adoption patterns and their influence on writing convergence. Leveraging a dataset of over 627, 000 academic papers from arXiv, we develop a novel classification framework by fine-tuning prompt- and discipline-specific large language models to detect the style of ChatGPT-revised texts. Our findings reveal substantial disparities in LLM adoption across academic disciplines, gender, native language status, and career stage, alongside a rapid evolution in scholarly writing styles. Moreover, LLM usage enhances clarity, conciseness, and adherence to formal writing conventions, with improvements varying by revision type. Finally, a difference-in-differences analysis shows that while LLMs drive convergence in academic writing, early adopters, male researchers, non-native speakers, and junior scholars exhibit the most pronounced stylistic shifts, aligning their writing more closely with that of established researchers. |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.13629 |
| By: | Gianni De Fraja |
| Abstract: | The labour force in the university sector of many countries is extremely international. I propose a theoretical model to study cross border academic mobility, where academics bargain with institutions over pay and choose the countries where they live and work to maximise their lifetime utility. I then test the model on a sample of well over 900, 000 research active academics over 33 years. The model predicts how academics respond both to changes in external conditions, including exchange rate fluctuations, and to changes in their record, measured by their publications and their citations. The theoretical predictions are confirmed by the empirical analysis. |
| Keywords: | Academic migration, university, international academic mobility, research, higher education |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:not:notgep:2025-03 |