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News
June 4, 2026
Machine Learning Models Can Help Reduce Volatility and Boost Stock Market Returns
The use of machine learning models makes it possible to achieve greater accuracy in predicting risks in the Russian stock market compared to classical econometric approaches. The predictive power of these models increases by 23%, while the average investor’s return can reach up to 13% per annum. These conclusions were drawn by Nikita Lysenok from the Department of Financial Market Infrastructure at the HSE Faculty of Economic Sciences. The paper has been published in Fundamental and Applied Mathematics.
June 3, 2026
Pocket Money, Personal Interest, and Family Practices: What Shapes Students Economic Literacy?
University students' economic literacy depends not only on their field of study but also on their interest in economics, the learning environment, and family financial practices. For example, students who received pocket money irregularly tend to perform better on economic literacy tests than their peers who received financial support on a regular basis. These findings come from a study conducted by HSE University involving more than 1,100 students from five Russian universities. The findings have been published in Cakrawala Pendidikan.
June 3, 2026
Creative Work as a Remedy for Burnout
The creative, supportive atmosphere and innovative methods at the Centre for Sociocultural Research make it appealing to early-career scholars. Over years of working at HSE University, they grow into researchers and lecturers recognised both in Russia and abroad. Chief Research Fellow Zarina Lepshokova and Leading Research Fellow Ekaterina Bushina spoke about their journey at the centre and at HSE, their research, and the role of mentors in their academic success.

 

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Communication clarity in calls for papers issued by journal special issues: First impressions matter

Learned Publishing. 2021. Vol. 34. No. 2. P. 156–163.
Plakhotnik M. S.

The purpose of this study was to examine communication clarity in calls for papers issued by peer reviewed journals for special issues. I wanted to explore what could hinder and help guest editors to communicate their intent to potential contributors. I searched peer reviewed journals in the field of human resource management published by five leading publishers, including Emerald, Sage, Wiley, Taylor & Francis, and Elsevier. Forty-seven journals were identified, and the sample included 33 calls for papers that I examined using content analysis. The results showed that many guest editors include a problem statement; purpose statement including explicative statements and specifications; and research questions, topics, or themes. Based on this result, I created a composite profile that describes how guest editors typically craft their calls, including the average number of sources, topics, and paragraphs. I also identified eight additional tools guest editors use to increase clarity of their calls. Additionally, my analysis indicated that guest editors vary greatly in their approaches to crafting calls for papers. I identified a number of inconsistencies, inaccuracies, omissions, and redundancies that could confuse or discourage potential contributors. Journal editors could use the results of this study to examine their editorial strategies and practices and revise and improve their guidelines and templates related to special issues and their calls. Special issue guest editors might use the study results to increase the chances of receiving quality submissions.

Research target: Media and Communications
Priority areas: management
Language: English
Full text
DOI
Text on another site
Keywords: human resource managementcommunication strategypublishing industryjournal strategic development
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