|
on Sociology of Economics |
| By: | Advani, Arun (University of Warwick & IFS); Ash, Elliott (ETH Zurich); Boltachka, Anton (ETH Zurich); Cai, David (LSE); Rasul, Imran (UCL & IFS) |
| Abstract: | An established literature has studied potential biases in the economics publication process based on traits of authors. We complement such work by studying whether the subject matter of study relates to publication outcomes. We do so in the context of race-related research : work that studies economic well-being across racial/ethnic groups. We investigate the implicit career incentives economists have to work on such topics by examining paths to publication for a corpus of 22, 056 NBER working papers (WPs) posted from 1974 to 2015. We use an algorithm to classify whether a given WP studies race-related issues. We then construct paths to publication from WPs to data on published articles, and compare paths for race-related WPs to various counterfactual sets of WPs. We document that unconditionally, race-related NBER WPs are less likely to be published in any journal, in an economics journal, and more likely to publish in lower tier economics journals. Once we condition on observable characteristics including field and author affiliations, differences in paths to publication largely disappear, and such work is actually slightly more likely to publish in top-tier economics journals. Consistent with unconditional differences in paths to publication being salient to researchers, we find evidence of ex ante selection into WPs studying racerelated issues in that they are of higher readability than other WPs. To understand the interplay with selection of researchers, we compare results to paths to publications for 10 306 CEPR WPs posted from 1984 to 2015. We conclude by discussing implications for economists’ incentives to contribute to debates on race and ethnicity in the economy JEL Codes: A11 ; B41 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:wrk:warwec:1549 |
| By: | Lutz Bornmann; Klaus Wohlrabe |
| Abstract: | This study examines how tripartite phrases in academic paper titles affect citation counts. Tripartite phrases consist of three interconnected elements separated by commas and conjunctions such as pattern, perception, and performance. Analyzing comprehensive datasets from economics (235, 330 articles) and medicine and life sciences (93, 713 articles), we found that papers with titles including tripartite phrases receive significantly more citations. Papers with tripartite phrases receive on average 3.5 additional citations in economics and 32 additional citations in medicine and life sciences compared to those without, controlling for paper characteristics, journal characteristics, and publication timing. For medical and life sciences papers, this effect persists when controlling for expert-assessed paper quality. The relative share of tripartite titles among the titles of all papers was stable over time at approximately 9% in economics and 4% in medicine and life sciences, suggesting an established stylistic convention. |
| Keywords: | tripartite phrases, academic writing, bibliometrics, citation analysis, paper titles |
| JEL: | A10 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11671 |
| By: | Shumin Qiu; Claudia Steinwender; Pierre Azoulay |
| Abstract: | We investigate the phenomenon of home bias in scientific citations, where researchers disproportionately cite work from their own country. We develop a benchmark for expected citations based on the relative size of countries, defining home bias as deviations from this norm. Our findings reveal that China exhibits the largest home bias across all major countries and in nearly all scientific fields studied. This stands in contrast to the pattern of home bias for China’s trade in goods and services, where China does not stand out from most industrialized countries. After adjusting citation counts for home bias, we demonstrate that China’s apparent rise in citation rankings is overstated. Our adjusted ranking places China fourth globally, behind the US, the UK, and Germany, tempering the perception of China’s scientific dominance. |
| Keywords: | home bias, China, citations, economics of science, basic research, international spillovers |
| JEL: | I23 O30 O53 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11664 |
| By: | Ras-Carmona, Alvaro; Lafuente, Esther M.; Reche, Pedro A |
| Abstract: | xPromoting gender equality and excellence are key policies in academia. In this work, we studied scientific output and potential gender disparities in faculty positions at the Complutense University of Madrid (UCM), the largest academic institution in Spain. We found that women are clearly underrepresented in full professor positions despite being a majority in lower academic ranks. This gender disparity in full professor positions is however narrowing down in recent years. The scientific output of researches, as judged by the h-index, varied greatly between Faculties, but overall, correlated positively with the academic rank and no significant differences were detected between women and men, although exceptions were noted. Judging by the m-index, the scientific output of women and men in full professor positions were also alike. In sum, there is effective equality between genders within UCM faculty ranks. |
| Date: | 2025–01–03 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:gfecv_v1 |
| By: | Kwiek, Marek; Szymula, Łukasz |
| Abstract: | In this research, we quantify an inflow of women into science in the past three decades. Structured Big Data allow us to estimate the contribution of women scientists to the growth of science by disciplines (N = STEMM 14 disciplines) and over time (1990-2023). A monolithic segment of STEMM science emerges from this research as divided between the disciplines in which the growth was powerfully driven by women – and the disciplines in which the role of women was marginal. There are four disciplines in which 50% of currently publishing scientists are women; and five disciplines in which more than 50% of currently young scientists are women. But there is also a cluster of four highly mathematized disciplines (MATH, COMP, PHYS, and ENG) in which the growth of science is only marginally driven by women. Digital traces left by scientists in their publications indexed in global datasets open two new dimensions in large-scale academic profession studies: time and gender. The growth of science in Europe was accompanied by growth in the number of women scientists, but with powerful cross-disciplinary and cross-generational differentiations. We examined the share of women scientists coming from ten different age cohorts for 32 European and four comparator countries (the USA, Canada, Australia, and Japan). Our study sample was N = 1, 740, 985 scientists (including 39.40% women scientists). Three critical methodological challenges of using structured Big Data of the bibliometric type were discussed: gender determination, academic age determination, and discipline determination. |
| Date: | 2024–10–18 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:w34pr_v1 |
| By: | Pat Pataranutaporn; Nattavudh Powdthavee; Pattie Maes |
| Abstract: | We investigate whether artificial intelligence can address the peer review crisis in economics by analyzing 27, 090 evaluations of 9, 030 unique submissions using a large language model (LLM). The experiment systematically varies author characteristics (e.g., affiliation, reputation, gender) and publication quality (e.g., top-tier, mid-tier, low-tier, AI generated papers). The results indicate that LLMs effectively distinguish paper quality but exhibit biases favoring prominent institutions, male authors, and renowned economists. Additionally, LLMs struggle to differentiate high-quality AI-generated papers from genuine top-tier submissions. While LLMs offer efficiency gains, their susceptibility to bias necessitates cautious integration and hybrid peer review models to balance equity and accuracy. |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2502.00070 |