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Regular version of the site
Of all publications in the section: 8
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Article
Sircova A., van de Vijver F., Osin E. N. et al. Sage Open. 2014. Vol. 4.

In this article we assess the structural equivalence of the Zimbardo Time Perspective Inventory (ZTPI; Zimbardo & Boyd, 1999) across 26 samples from 24 countries (N = 12,200). The ZTPI is proven to be a valid and reliable index of individual differences in time perspective across five temporal categories: Past-Negative, Past-Positive, Present-Fatalistic, Present-Hedonistic, and Future. We obtained evidence for invariance of 36 items (out of 56) and also the five-factor structure of ZTPI across 23 countries. The short ZTPI scales are reliable for country-level analysis, whereas we recommend the use of the full scales for individual-level analysis. The short-version of ZTPI will further promote integration of research in the time perspective domain in relation to many different psycho-social processes.

Added: Nov 13, 2013
Article
Shmatko N. A., Volkova G. Sage Open. 2020. Vol. 10. No. 3. P. 1-13.

This article focuses on the demand for skills of highly qualified scientific and technical professionals (engineers and researchers) in robotics, on both a global and national level. Information is collected using the text-mining of open-access vacancies for understanding the global trends and in-depth interviews with experts for a more detailed study of national trends. The study explores the combination of hard and soft skills, as well as interdisciplinary skills. Soft skill requirements play an important role in the demanded skill set of the specialist, but the claims for hard skills (including digital) are not becoming less strict. Programming and the knowledge of specialized software packages are the most important skills, but must be combined with practical skills (assembly, welding, soldering). The broad range of application areas for robotic systems creates demand for new multidisciplinary skills (knowledge of artificial intelligence, new materials, and biology). Rapid technological development underlines the growing importance of soft skills, such as communication skills, self-motivation, and a willingness to learn. Lists of the most demanded skills in different countries principally coincide. Results can be applied for developing policies aimed at eliminating the skill gap in prospective technological areas.

Added: Oct 16, 2019
Article
Inna F. Deviatko, Gavrilov K. A. Sage Open. 2020. Vol. 10. No. 4. P. 1-13.

Cognitive factors are known to influence lay assessments of causality and blame for negative side effects of intentional actions but specific social determinants of such assessments remain relatively unexplored. In a full-factorial, intraindividual experiment using two blocks of analogous vignettes constructed for two particular institutional action domains (“medical” and “corporate dress code”), we tested the propositions that causality and blame judgments differ between (a) domains and depend on (b) the type of action originator; (c) the type of damage; and (d) the “remoteness” of damage from the originator. Our data demonstrate a significant difference between two institutional action domains: actors in “medical”-related vignettes are generally estimated to be more causally effective and blameworthy than actors in “dress code”–related vignettes. In addition to the pronounced main effects of institutional domain as a factor influencing cause and blame judgments, we revealed few significant interaction effects of the latter with other experimental factors used for vignettes construction.  

Added: Nov 11, 2020
Article
Bogolyubova O., Upravitelev Philipp, Churilova A. et al. Sage Open. 2018. P. 1-9.

People have been using images to express ideas, share stories, and communicate since early history. The advent of social media has made sharing images an important part of everyday life. Among other things, social networks can be used to express psychological distress; however, research on this topic is limited. The goal of this study was to explore representations of psychological distress in the Russian-speaking segment of Instagram. The study involved contrasting images labeled with hashtags in Russian with images marked by analogous Anglophone hashtags in a data set of 1,512 images. Quantitative content analysis revealed significant differences between images labeled with Russian and Anglophone hashtags. Images containing depictions of texts were significantly less frequent among images with Russian hashtags, while inanimate object depictions were more prevalent. Hashtags for fear in both languages were related not to psychological distress but to the “scary” in popular culture. Images of alcohol were associated with stress hashtags in both languages and with hashtag for depression in Russian only. Images of food were significantly more prevalent among images with Russian hashtag for stress. Current study highlights the need for culturally and linguistically appropriate online mental health interventions.

Added: Feb 18, 2019
Article
Stukal D., Sanovich S., Bonneau R. et al. Sage Open. 2019. Vol. 9. No. 2. P. 1-16.

Computational propaganda and the use of automated accounts in social media have recently become the focus of public attention, with alleged Russian government activities abroad provoking particularly widespread interest. However, even in the Russian domestic context, where anecdotal evidence of state activity online goes back almost a decade, no public systematic attempt has been made to dissect the population of Russian social media bots by their political orientation. We address this gap by developing a deep neural network classifier that separates pro-regime, anti-regime, and neutral Russian Twitter bots. Our method relies on supervised machine learning and a new large set of labeled accounts, rather than externally obtained account affiliations or orientation of elites. We also illustrate the use of our method by applying it to bots operating in Russian political Twitter from 2015 to 2017 and show that both pro- and anti-Kremlin bots had a substantial presence on Twitter.

Added: Oct 1, 2020
Article
Littrell R., Edvardson I., Minelgaite Snaebjornsson I. Sage Open. 2017. Vol. 7. No. 2. P. 1-15.

This article contributes to cross-cultural management literature, by providing empirical data from two underresearched countries, to serve in the future as benchmark cultural shift research. Furthermore, it illustrates not only the insufficiency of mare statement of cultural dimension difference/similarities but also a need to contextualize them. Results indicate that Icelandic and Lithuanian societal cultures are different on three out of seven of Hofstede's dimensions; however, these differences have considerable effect on management practices …

Added: Oct 2, 2018
Article
Littrell R., Minelgaite I., Urboniene L. et al. Sage Open. 2018. Vol. 8. No. 2. P. 1-11.

This article presents a study of desired leadership behavior in the educational sector in Iceland. This sector has been undergoing major challenges during recent years, including restructuring and mergers of schools, strikes of teachers’ professional unions, and increasing dropout rates. This situation requires exceptional leadership together with the understanding that leadership is a culture and context contingent phenomenon. However, research on managerial leadership in the education sector in Iceland is virtually nonexistent, presenting a gap in literature as well as failure to contribute to solving issues in practice. This article contributes to closing this gap by investigating the desired leader profile from a follower-centric perspective. The results indicate that the most desired leader behaviors in this sector tend to be relationship orientated, suggesting a need to focus on the “soft” side of leadership and reconsider overemphasis on bureaucracy. Effects of gender and demographic differences are minimal, suggesting coherence with structural theory. Managerial leadership implications and future research directions are discussed.

Added: Nov 14, 2019
Article
Bogolyubova O., Panicheva P., Ledovaya Y. et al. Sage Open. 2020. Vol. 10. No. 2. P. 1-8.

Positive mental health is considered to be a significant predictor of health and longevity; however, our understanding of the ways in which this important characteristic is represented in users’ behavior on social networking sites is limited. The goal of this study was to explore associations between positive mental health and language used in online communication in a large sample of Russian Facebook users. The five-item World Health Organization Well-Being Index (WHO-5) was used as a self-report measure of well-being. Morphological, sentiment, and semantic analyses were performed for linguistic data. The total of 6,724 participants completed the questionnaire and linguistic data were available for 1,972. Participants’ mean age was 45.7 years (SD = 11.6 years); 73.4% were female. The dataset included 15,281 posts, with an average of 7.67 (SD = 5.69) posts per participant. Mean WHO-5 score was 60.0 (SD = 19.1), with female participants exhibiting lower scores. Use of negative sentiment words and impersonal predicates (“should statements”) demonstrated an inverse association with the WHO-5 scores. No significant correlation was found between the use of positive sentiment words and the WHO-5 scores. This study expands current understanding of the association between positive mental health and language use in online communication by employing data from a non-Western sample.

Added: May 23, 2020