FORMATION OF STUDENT YOUTH’S SOCIAL ACTIVITY IN THE SPACE OF HIGHER EDUCATION INSTITUTION

the problem of the formation of student youth’s social activity in the space of a higher education institution is considered. Taking into account the modern vectors of development of society due to digitalization, it is necessary to have a positive social development of students as future leaders. The formation of their social activity, as a significant social quality, needs a favorable space and socio-pedagogical direction. Since the leading activity of student youth is educational, it is proposed to consider the space of the institution of higher education for the formation of their social activity.

The Case of Brazil

This article analyzes the impacts of the COVID-19 pandemic on the lives of the Amazonian populations of Brazil. Following the social quality approach, it inquires into how COVID-19 intertwined with and reinforced underlying trends and inequalities in different life domains expressed in long-term societal complexities, urban–rural dynamics, and environmental transformations. The article finds that the pandemic, following coloniality of power patterns, has been instrumentalized as a necropolitical tool, and has disproportionately impacted certain peoples and territories based on ethnoracial bias. The collapse of the local health system in the State of Amazonas is a systemic burden, not serendipity. A dialogue is proposed between decolonial and social quality approaches to analyze, unveil, and denounce the interplay between the coloniality of power patterns in non-Western contexts.

The Case of India

A segmented healthcare system evolved in India by 1990s, whereby the rich population depended on private hospitals while the people at the bottom of the economic pyramid went to the poor-quality public hospitals. In a democracy of equals, unequal access to services became political when COVID-19 began to put pressure on the health system. Corruption that was normalized in a segmented healthcare system could no longer be ignored. To advance the framework of social quality, we examine the corruption that unfolded during the pandemic in India from the perspective of moral foundation theory. We study the issues raised by political parties during the pandemic and court directives responding to citizen grievances. The evidence shows there was inequality of access and that courts had to intervene to try to rectify the situation. In the absence of effective governmental intervention during the pandemic, moral norms become a useful explanatory factor for social quality.

The Case of Pakistan

This article represents a qualitative investigation of the vulnerabilities of displaced households in Pakistan caused by the COVID-19 pandemic. The analyses are conducted through the lens of social quality theory and the social quality approach according to four societal dimensions that condition household life chances. Our findings reveal that these households reflect a reversal of the sustainable development cycle. They are at risk of being economically unstable, being unable to gain new skills, falling into absolute poverty, increased morbidity rates, and disrupted education. The most severe form of deprivation is the disruption of their networks of social cohesion, leading to greater isolation and marginalization; this is especially true for women and children. The Pakistani government must take immediate and substantive action to improve the situations of these most vulnerable of households.

The COVID-19 Pandemic and Climate Change

In these reflections, instead of just summarizing the contributions on the societal impact of COVID-19 in the countries discussed in this thematic issue, we develop considerations on the nature of its substance and various related methodological issues. This is based especially on the outcomes of Working Paper 17 of the International Association on Social Quality (IASQ 2019) and the study about the conditions for interdisciplinary research in the natural sciences, in the human sciences, and between both fields of knowledge (Westbroek et al. 2020). Both documents were available for the authors of this issue’s articles. For understanding the overwhelming COVID-19 pandemic as well the increasing challenges caused by climate change, bio-degeneration, and the ongoing pollution of nature, new steps for bridging the natural and the human sciences are a conditio sine qua non for understanding the complexity of the multidimensionality of critical situations that demand comprehensive approaches.

The Case of the United Kingdom

This article explores the determinants of local resilience in the form of local COVID-19 mutual aid groups. These groups were formed to offer mutual help to those who had experienced a loss of social quality. We test a series of hypotheses, considering which conditional factors are most connected to the formation of these groups, particularly focusing on those that influenced the earliest and most resilient local response to the pandemic. The presence of radical environmentalist activists is a better predictor of resilient community responsiveness than either the activity of the local state or the activity of more moderate community-based environmental civil society organizations. Conclusions are presented on the implications of these findings for the future of localism, social quality, and public policy in the United Kingdom.

The Case of Italy

The present article makes use of aspects of social quality theory and the social quality approach to assess the impact of the Italian government’s efforts to counter the COVID-19 pandemic. The federal government has a critical role in mitigating the effects of the pandemic; however, the scope and efficacy of its interventions depend on the interplay of processes in four main dimensions: (1) sociopolitical and legal; (2) socioeconomic and financial; (3) sociocultural and welfare; and (4) socioenvironmental and ecological. By analyzing relevant processes in these four dimensions, I aim to understand whether the social quality in Italy has increased or decreased due to the pandemic. The fragmentation in the labor market, in healthcare governance, as well as in societal protection have strongly constrained the government interventions, leaving intact and crystallizing existing societal inequalities.

The Case of Australia

Government responses to COVID-19 have dramatically altered the social quality of daily circumstances. Consequently, theoretical questions about social cohesion require recalibration as we explore new models of social quality. Central to this article is trust, one of the fundamental tenets of social cohesion. We present data from interviews with 40 women in midlife (45–64 years) regarding their everyday experiences of “life in lockdown” during the pandemic. Key themes focus on women’s (dis)trust in individuals (e.g., politicians, public health experts, family, themselves) and systems (e.g., politics, medicine, the media). This study provides insights into the differential impact of the pandemic in shaping public trust and hence social cohesion—in authority, institutions, and “each other”—with important lessons for how future efforts can rebuild trust in post-pandemic times.

Kinematic-Based Classification of Social Gestures and Grasping by Humans and Machine Learning Techniques

The affective motion of humans conveys messages that other humans perceive and understand without conventional linguistic processing. This ability to classify human movement into meaningful gestures or segments plays also a critical role in creating social interaction between humans and robots. In the research presented here, grasping and social gesture recognition by humans and four machine learning techniques (k-Nearest Neighbor, Locality-Sensitive Hashing Forest, Random Forest and Support Vector Machine) is assessed by using human classification data as a reference for evaluating the classification performance of machine learning techniques for thirty hand/arm gestures. The gestures are rated according to the extent of grasping motion on one task and the extent to which the same gestures are perceived as social according to another task. The results indicate that humans clearly rate differently according to the two different tasks. The machine learning techniques provide a similar classification of the actions according to grasping kinematics and social quality. Furthermore, there is a strong association between gesture kinematics and judgments of grasping and the social quality of the hand/arm gestures. Our results support previous research on intention-from-movement understanding that demonstrates the reliance on kinematic information for perceiving the social aspects and intentions in different grasping actions as well as communicative point-light actions.