English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

India locked down 1.3 billion people on March 25, 2020 in the wake ofCOVID-19 pandemic. The economic cost of it was estimated at USD 98 billion,while the social costs are still unknown. This study investigated howgovernment formed reactive policies to fight coronavirus across its policysectors. Primary data was collected from the Press Information Bureau (PIB) inthe form press releases of government plans, policies, programme initiativesand achievements. A text corpus of 260,852 words was created from 396 documentsfrom the PIB. An unsupervised machine-based topic modelling using LatentDirichlet Allocation (LDA) algorithm was performed on the text corpus. It wasdone to extract high probability topics in the policy sectors. Theinterpretation of the extracted topics was made through a nudge theoretic lensto derive the critical policy heuristics of the government. Results showed thatmost interventions were targeted to generate endogenous nudge by using externaltriggers. Notably, the nudges from the Prime Minister of India was critical increating herd effect on lockdown and social distancing norms across the nation.A similar effect was also observed around the public health (e.g., masks inpublic spaces; Yoga and Ayurveda for immunity), transport (e.g., old trainsconverted to isolation wards), micro, small and medium enterprises (e.g., rapidproduction of PPE and masks), science and technology sector (e.g., diagnostickits, robots and nano-technology), home affairs (e.g., surveillance andlockdown), urban (e.g. drones, GIS-tools) and education (e.g., onlinelearning). A conclusion was drawn on leveraging these heuristics are crucialfor lockdown easement planning.

India nudges to contain COVID-19 pandemic: a reactive public policy analysis using machine-learning based topic modelling