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The impact of the Covid-19 pandemic on social inequalities in international student mobility: A scoping review.

Almeida, J., Netz, N., Nika, D., Krzaklewska, E., Aguiar, J., ... & Malet Calvo, D. (2025).
The impact of the Covid-19 pandemic on social inequalities in international student mobility: A scoping review. Comparative Migration Studies, 13(1), 27. https://doi.org/10.1186/s40878-025-00436-0
Abstract

This systematic literature review sheds light on social inequalities in students’ access to and experiences of international student mobility (ISM) in the context of the Covid-19 pandemic. Following a scoping approach based on the 2020 PRISMA guidelines, it synthesises 48 empirical studies published in the most intense phase of the Covid-19 pandemic, namely between January 2020 and June 2022.

Revolutionary synergy: The fusion of data mesh and data fabric for strategy analytics in GRAPHYP knowledge graph.

Azeroual, O., Fabre, R., & Störl, U. (2025).
Revolutionary synergy: The fusion of data mesh and data fabric for strategy analytics in GRAPHYP knowledge graph. In Coenen, F. et al. (Hrsg.), Knowledge Discovery, Knowledge Engineering and Knowledge Management. IC3K 2023. Communications in Computer and Information Science (S. 277-295). Cham: Springer. https://doi.org/10.1007/978-3-031-87569-4_13

AutoML meets hugging face: Domain-aware pretrained model selection for text classification.

Safikhani, P., & Broneske, D. (2025).
AutoML meets hugging face: Domain-aware pretrained model selection for text classification. In A. Ebrahimi, S. Haider, E. Liu, M. L. Pacheco, & S. Wein (Hrsg.), Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 4: Student Research Workshop). Albuquerque, USA: Association for Computational Linguistics.
Abstract

The effectiveness of embedding methods is crucial for optimizing text classification performance in Automated Machine Learning (AutoML). However, selecting the most suitable pre-trained model for a given task remains challenging. This study introduces the Corpus-Driven Domain Mapping (CDDM) pipeline, which utilizes a domain-annotated corpus of pre-fine-tuned models from the Hugging Face Model Hub to improve model selection. Integrating these models into AutoML systems significantly boosts classification performance across multiple datasets compared to baseline methods. Despite some domain recognition inaccuracies, results demonstrate CDDM’s potential to enhance model selection, streamline AutoML workflows, and reduce computational costs.

How Does Taking Parental Leave Affect the Wages of Highly Educated Parents?

Jaksztat, S., Goldan, L., & Gross, C. &. (2025).
How Does Taking Parental Leave Affect the Wages of Highly Educated Parents? Journal of Marriage and Family (online first). https://doi.org/10.1111/jomf.13109

Inequality at the Transition to Higher Education in Germany: Social Differences by Prior Educational Pathways.

Quast, H., Spangenberg, H., Mentges, H., Ordemann, J., & Buchholz, S. (2025).
Inequality at the Transition to Higher Education in Germany: Social Differences by Prior Educational Pathways. Social Inclusion, 2025(13). https://doi.org/10.17645/si.8766

A CRISP-DM and predictive analytics framework for enhanced decision-making in research information management systems.

Azeroual, O., Nacheva, R., Nikiforova, A., & Störl, U. (2025).
A CRISP-DM and predictive analytics framework for enhanced decision-making in research information management systems. Informatica, 2025(49), 67-86. https://doi.org/10.31449/inf.v49i18.5613

Reference coverage analysis of OpenAlex compared to Web of Science and Scopus.

Culbert, J. H., Hobert, A., Jahn, N., Haupka, N., Schmidt, M., Donner, P., & Mayr, P. (2025).
Reference coverage analysis of OpenAlex compared to Web of Science and Scopus. Scientometrics (online first). https://doi.org/10.1007/s11192-025-05293-3
Abstract

OpenAlex is a promising open source of scholarly metadata, and competitor to established proprietary sources, such as the Web of Science and Scopus. As OpenAlex provides its data freely and openly, it permits researchers to perform bibliometric studies that can be reproduced in the community without licensing barriers. However, as OpenAlex is a rapidly evolving source and the data contained within is expanding and also quickly changing, the question naturally arises as to the trustworthiness of its data. In this report, we will study the reference coverage and selected metadata within each database and compare them with each other to help address this open question in bibliometrics. [...]

Lehrbezogene Selbstwirksamkeitserwartung von Lehrenden an Hochschulen und ihre Entwicklung infolge von hochschuldidaktischer Qualifizierung.

Hartz, S., Beuße, M., & Aust, K. (2025).
Lehrbezogene Selbstwirksamkeitserwartung von Lehrenden an Hochschulen und ihre Entwicklung infolge von hochschuldidaktischer Qualifizierung. Zeitschrift für Erziehungswissenschaft, 2025 (online first). https://doi.org/10.1007/s11618-025-01295-2

离开学术界? ———基于追踪调查的德国博士职业状况分析 (Leaving academia? An analysis oft the career outcomes of PhD-Graduates in Germany based on a long-term follow-up study).

Briedis, K. (2025).
离开学术界? ———基于追踪调查的德国博士职业状况分析 (Leaving academia? An analysis oft the career outcomes of PhD-Graduates in Germany based on a long-term follow-up study). Peking University Education Review, 2024(22), 87-99.

Öffentliche Sachen im Anstalts- und Einrichtungsgebrauch.

Eisentraut, N. (2025).
Öffentliche Sachen im Anstalts- und Einrichtungsgebrauch. In W. Kahl & M. Ludwigs (Hrsg.), Handbuch des Verwaltungsrechts Band VII: Aufgaben, Organisation und öffentliche Sachen (S. 1261-1299). Heidelberg: C.F. Müller.
Abstract

Das Recht der öffentlichen Sachen im Anstalts- und Einrichtungsgebrauch sieht sich - wie das Recht der öffentlichen Sachen in Gänze - dem Problem seiner fehlenden abschließenden Konturierung, dogmatischen Erfassung und Nutzbarmachung ausgesetzt. Der Beitrag unternimmt eine Konstruktion der Figur der öffentlichen Sachen im Anstalts- und Einrichtungsgebrauch, die der Bedeutung des Rechtsbereichs für das Gemeinwesen gerecht zu werden versucht.

VerbCraft: Morphologically-aware Armenian text generation using LLMs in low-resource settings.

Avetisyan, H., & Broneske, D. (2025).
VerbCraft: Morphologically-aware Armenian text generation using LLMs in low-resource settings. In ¦. A. Holdt, N. Ilinykh, B. Scalvini, M. Bruton, I. N. Debess, & C. M. Tudor (Hrsg.), Proceedings of the Third Workshop on Resources and Representations for Under-Resourced Languages and Domains (RESOURCEFUL-2025) (S. 111-119). Tallinn: University of Tartu Library, Estonia.

Stata tip 160: Drop capture program drop from ado-files.

Klein, D. (2025).
Stata tip 160: Drop capture program drop from ado-files. The Stata Journal, 2025(1), 252-253. https://doi.org/10.1177/1536867X251322974
Abstract

I explain that -capture program drop- is useless in ado-files. While it prevents errors in do-files when redefining programs in memory, it either isn't executed or results in an error in ado-files. Moreover, in ado-files with local subroutines, -capture program drop- can mistakenly remove unrelated programs from memory.

" Den DAAD-geförderten Publikationen liegt ein hoher Anteil an internationalen Kooperationen zugrunde " .

Möller, T., & Dittmann, P. (13. März 2025).
"Den DAAD-geförderten Publikationen liegt ein hoher Anteil an internationalen Kooperationen zugrunde" [Blogbeitrag]. Abgerufen von https://www.wissenschaft-weltoffen.de/de/2025/03/13/den-daad-gefoerderten-publikationen-liegt-ein-hoher-anteil-an-internationalen-kooperationen-zugrunde/

Tell me more! Using multiple features for binary text classification with a zero-shot model.

Broneske, D., Italiya, N., & Mierisch, F. (2025).
Tell me more! Using multiple features for binary text classification with a zero-shot model. In IEEE Institute of Electrical and Electronic Engineers (Hrsg.), 2024 International Conference on Machine Learning and Applications (ICMLA) (S. 1613-1620). Jacksonville, Florida, USA: IEEE Xplore. https://doi.org/10.1109/ICMLA61862.2024.00249

Empowering IT-Supported Research Management: Leveraging Data Science Methods for Informed Decisions.

Azeroual, O. (2025).
Empowering IT-Supported Research Management: Leveraging Data Science Methods for Informed Decisions. In Tallón-Ballesteros, A.J. (Hrsg.), Digitalization and Management Innovation III (S. 39-51). Amsterdam: IOS Press. https://doi.org/10.3233/FAIA250006

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