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With 43.2 million coronavirus cases and 525,000 deaths in 2022, India ranked second worldwide, after the United States (84.6 million cases and 1 million deaths), according to the latest available June 2022 COVID-19 impact data.

Amid people’s growing mistrust in the government, India’s news media enhanced the nation’s distinguished designation as the world’s largest and most populous democracy. India’s news media inform, educate, empower, and entertain a surging population of 1.4 billion people, which is roughly one-sixth of the world’s people.

Drawing upon the media agendamelding theoretical framework, we conducted a case study research into interplay between two prominent democratic institutions, the media and the government, to analyze the role of the COVID-19 pandemic in redefining India’s networked society.

India’s COVID-19 pandemic aggravated internecine tensions between media and government relating to four key freedom issues: (1) world’s largest COVID-19 lockdown affecting 1.3 billion Indians from March 25, 2020 to August 2020 with extensions and five-phased re-openings, to restrict the spread of COVID-19; (2) Internet shutdowns; (3) media censorship during the 1975–1977 “Emergency”; and (4) unabated murders of journalists in India.

Although the COVID-19 pandemic caused deleterious problems debilitating the tensions between the media and the government, India’s journalists thrived by speaking truth to power. This study delineates key aspects of India’s media agendamelding that explicates how the people of India form their media agendas. India’s news audiences meld media messages from newspapers, television, and social media to form a picture of the issues, insights, and ideas that define their lives and times in the 21st century digital age.

This chapter examines the University of Connecticut (UConn) Neag School of Education's efforts to improve the recruitment of students of colour through an Early College Experience (ECE) Programme. During the pandemic, the School of Education and the ECE Programme collaborated to train and certify high school teachers to instruct the UConn's lower level undergraduate courses. The programme exposed many students of colour to teaching as a career.

This chapter of the book seeks to use famous mathematical functions (statistical distribution functions) in evaluating and analyzing supply chain network data related to supply chain management (SCM) elements in organizations. In other words, the main purpose of this chapter is to find the best-fitted statistical distribution functions for SCM data. Explaining how to best fit the statistical distribution function along with the explanation of all possible aspects of a function for selected components of SCM from this chapter will make a significant attraction for production and services experts who will lead their organization to the path of competitive excellence. The main core of the chapter is the reliability values related to the reliability function calculated by the relevant chart and extracting other information based on other aspects of statistical distribution functions such as probability density, cumulative distribution, and failure function. This chapter of the book will turn readers into professional users of statistical distribution functions in mathematics for analyzing supply chain element data.