The Ethics of COVID-19 Vaccine Allocation: Don't Forget the Trade-Offs!

The issue of COVID-19 vaccine allocation is still highly controversial on the international as well as on the national level (particularly in many low- and middle-income countries), and policy-makers worldwide struggle in striking a fair balance between different ethical principles of vaccine allocation, in particular maximum benefit, reciprocity, social justice and equal respect. Any political decision that implements these principles comes at a cost in terms of loss of lives and of loss of life years that could potentially have been prevented by a different vaccination strategy. This article illustrates these trade-offs using quantitative analysis and shows how this approach can contribute to providing a rational and transparent grounding of political decisions on COVID-19 vaccine allocation.

A Machine Learning Resource Allocation Solution to Improve Video Quality in Remote Education

The current global pandemic crisis has unquestionably disrupted the higher education sector, forcing educational institutions to rapidly embrace technology-enhanced learning. However, the COVID-19 containment measures that forced people to work or stay at home, have determined a significant increase in the Internet traffic that puts tremendous pressure on the underlying network infrastructure. This affects negatively content delivery and consequently user perceived quality, especially for video-based services. Focusing on this problem, this paper proposes a machine learning-based resource allocation solution that improves the quality of video services for increased number of viewers. The solution is deployed and tested in an educational context, demonstrating its benefit in terms of major quality of service parameters for various video content, in comparison with existing state of the art. Moreover, a discussion on how the technology is helping to mitigate the effects of massively increasing Internet traffic on the video quality in an educational context is also presented. IEEE

Adapting to online teaching in software engineering courses

The COVID-19 worldwide pandemic caused sudden and unexpected changes in how we teach software engineering and other university courses. This paper presents an empirical study that aims to improve our understanding on how the assessment of student learning changed, in response to the transition from in-class to online courses. A questionnaire was distributed to instructors across the globe. The results indicate that the evaluation methodologies for most reported learning objectives have changed. Not surprising, in-class oral presentations and in-class exams are no longer used by the instructors for evaluations. We observed a trend of having fewer exams and more project-related evaluations after the transition. Not all instructors changed the way they evaluated student learning after the transition, however the majority reported their effort in student learning assessment increased after the transition, whether they made changes in methodologies or not. © 2020 ACM.

Securitization of the COVID-19 pandemic by metaphoric discourse during the state of emergency in Hungary

Purpose: Politicians' response to the coronavirus disease 2019 (COVID-19) pandemic worldwide relied on war scenarios having a tradition in disease management. The study contrasts how the political measures introduced during the state of emergency were presented by the Prime Minister of Hungary in his social media posts and his speeches and announcements broadcast by public media. Design/methodology/approach: A computer-assisted content analysis was conducted to extract data on war and military metaphors, followed by a qualitative analysis of the metaphor scenarios used for explaining the situation and justifying action. The role of the prime minister (PM) indicated by the social media posts and by his transcripted speeches was compared with the suggestion of the visual illustrations. Findings: The study’s findings were that verbal communication shifted between war-related metaphoric to military-related realistic. The third conceptual domain identified was fear. Messages were mostly about national cohesion, however, visually, the PM was the protagonist of the events. The communication proved efficient according to opinion polls. Originality/value: The research revealed how the securitization of the pandemic took place via the political discourse constructed both for Internet users and traditional media consumers. Metaphors of fear, war and military action created the justification of the declaration of a state of emergency. The PM as a capable and responsible leader was placed in focus of the events. Although verbal messages by the PM were centred on a sense of community and joint action, the personalization of political action was remarkable by indirect means, such as visual messages. The personalization of politics throughout the period researched served the purpose of securitization of the pandemic with the PM as a charismatic leader attracting attention and giving credit to the severity of the threat along with the introduction of extraordinary measures. © 2020, Emerald Publishing Limited.