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on Sociology of Economics |
| By: | Kaltenbrunner, Wolfgang; Chiarelli, Andrea; Elizondo, Andrea Reyes; Pinfield, Stephen; Waltman, Ludo; Brasil, André |
| Abstract: | We analyse focus group discussions and free-text survey responses from a multi-stakeholder consultation conducted after the October 2023 publication of the proposal Towards Responsible Publishing by cOAlition S. The proposal calls for a systemic reform of scholarly communication by reducing barriers to knowledge dissemination, promoting early sharing of outputs through preprints, and shifting peer review to an open, post-publication model. We focus on how different stakeholder groups –such as researchers, infrastructure providers, academic institutions, and publishers –perceive obstacles to the large-scale, coordinated reform envisioned in the proposal. We interpret these accounts as articulations of collective action problems, shaped by entrenchment of many actors in existing academic reward systems and established commercial revenue models that make transitions toward a more economically sustainable scholarly communication system difficult, even where many actors see the principal need for change. This approach highlights the extent to which stakeholder perspectives align or conflict. It also underscores the performative nature of discourse about collective action problems in scholarly communication: by articulating challenges to reform, participants simultaneously construct, reinforce, or contest their own roles within the system, which directly influences their collective capacity to act. |
| Date: | 2026–01–31 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:p9vrt_v1 |
| By: | J. Ignacio Conde-Ruiz; Miguel Díaz Salazar; Juan José Ganuza |
| Abstract: | This paper combines artificial intelligence with economic modeling to design evaluation committees that are both efficient and fair in the presence of gender differences in economic research orientation. We develop a dynamic framework in which research evaluation depends on the thematic similarity between evaluators and researchers. The model shows that while topic balanced committees maximize welfare, this researchneutral-gender allocation is dynamically unstable, leading to the persistent dominance of the group initially overrepresented in evaluation committees. Guided by these predictions, we employ unsupervised machine learning to extract research profiles for male and female researchers from articles published in leading economics journals between 2000 and 2025. We characterize optimal balanced committees within this multidimensional latent topic space and introduce the Gender-Topic Alignment Index (GTAI) to measure the alignment between committee expertise and female-prevalent research areas. Our simulations demonstrate that AI-based committee designs closely approximate the welfare-maximizing benchmark. In contrast, traditional headcount-based quotas often fail to achieve balance and may even disadvantage the groups they intend to support. We conclude that AI-based tools can significantly optimize institutional design for editorial boards, tenure committees, and grant panels. |
| Keywords: | machine learning, artificial intelligence, Topic Modeling, evaluation committees, committee quotas, research orientation |
| JEL: | D72 D82 J16 J78 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:upf:upfgen:1937 |
| By: | Zhuang Liu; Wenwei Peng; Shaoda Wang |
| Abstract: | Honesty is perceived as fundamental to societal functioning, motivating education systems worldwide to enforce strict oversight and heavy penalties for dishonest behavior. Yet much academic misconduct remains unexposed, and its broader consequences are further obscured by the sorting of individuals into careers based on probity. Applying advanced plagiarism-detection algorithms to half a million publicly available graduate dissertations in China, we uncover hidden misconduct and validate it against incentivized measures of honesty. Linking plagiarism records to rich administrative data, we document four main findings. First, plagiarism is pervasive and predicts adverse political selection: plagiarists are more likely to enter and advance in the public sector. Second, plagiarists perform worse when holding power: focusing on the judiciary and exploiting quasi-random case assignments, we find that judges with plagiarism histories issue more preferential rulings and attract a greater number of appeals — effects partly mitigated by trial livestreaming. Third, plagiarizing judges generate spillovers onto other judges and lawyers. Fourth, exploiting the staggered adoption of detection tools, we demonstrate that enforcing academic integrity leads to modest improvements in future professional conduct. |
| JEL: | M5 P00 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34747 |
| By: | Stansbury, Anna; Rodriguez, Kyra |
| Abstract: | Unlike gender or race, class background is rarely a focus of research on career progression, or of DEI efforts in elite occupations. Should it be? In this paper we document a large class gap in career progression in one occupation—U.S. tenure-track academia—using parental education to proxy for class background. First-generation college graduates are 10% less likely to be tenured at an R1, are tenured at institutions ranked 11% lower, earn 3% less, and report 5% lower job satisfaction, than their former Ph.D. classmates (from the same institution and field) with a parent with a non-Ph.D. graduate degree. Neither selection out of academia nor different preferences explain this gap; differential research productivity also plays little role. Instead, likely drivers are differences in cultural and social capital. We also find a class gap in career progression for Ph.D.s who work in industry, suggesting this phenomenon generalizes outside academia. (Stone Center on Socio-Economic Inequality Working Paper) |
| Date: | 2026–02–02 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:ugdjf_v1 |