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Record W6950046050 · doi:10.5281/zenodo.5336250

Study of the Negative & the Positive Impact of Coronavirus Pandemic on Different Types of Industry, Businesses & the Society

2021· article· en· W6950046050 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typearticle
Languageen
FieldHealth Professions
TopicDiverse Scientific Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicnobodyPopulationCoronavirus disease 2019 (COVID-19)Public healthCoronavirusGovernment (linguistics)

Abstract

fetched live from OpenAlex

<strong>Wesleyan Journal of Research, UGC Care-listed | ISSN: 0975-1386 | Peer-reviewed Journal</strong> <em>Vol. 13 No. 69 (March 2021)</em> <strong>Research Article: </strong>Management <em><strong>Study of the Negative &amp; the Positive Impact of Coronavirus Pandemic on Different Types of Industry, Businesses &amp; the Society</strong></em> <em><strong>Shubham Parsoya </strong>and <strong>Dr. Asif Perwej</strong></em> School of Management Studies (SOMS), Sangam University (SU), Bhilwara, Rajasthan, India <strong>Abstract:</strong> <em>In the background of unforeseen occurrence scenario of COVID-19 nationwide pandemic, this paper has created an endeavour to study the impact of coronavirus pandemic (COVID-19) on differing kinds of companies and industries in numerous ways. Once the emergence of Corona pandemic in India introduced, the matter of public health condition has become core issue of the people in India and it's been on the forefront in conjunction with alternative and related serious issues of migrant labour, loss of employment, economic and industrial instability etc., and on the other side with the massive population size and its ever growing rate over the last 3 decades, the general public health scenario has been deteriorated significantly, and the occurrence of COVID-19 since 2019 has changed the entire world’s functioning accordingly. Internationally the Pandemic of COVID-19 has affected all sections of the economy and nobody will specifically predict when the pandemic is going to be over and everything are going to be like our past days. With the beginning of the unfold of COVID-19, business and various other industries, such as; region trade, transport industry, food industry, agriculture industry, housing industry, education industry, cinema industry, energy industry, producing industry, music industry, mining trade, were straightaway clean up, and the outside travelling and domestic travel activities were also withheld for the unknown length on such moment. The impact of Covid-19 on all such industries was very big. Globally all business and industry are witnessing serious threat with the spreading of COVID-19. All the countries have the first preference of the protection of the people, interference of unfold and health care of the infected folks. However, there are some types of industries that are becoming some extreme number of advantages from such COVID-19 pandemic conditions in some direct or indirect ways. Such industries are; Education (EdTech) industries, E-retail industries, Banking, financial services and insurance industries (BFSI). Medical sector, Information technology and knowledge Technology Enabled Services, Etc.</em> <em><strong>Keywords:</strong></em> <em>Pandemic, COVID-19, Industries, Businesses, Impact, Problems, World, Economy</em> <em><strong>Conference Details:- </strong></em> <em><strong>International Conference on Analytical &amp; Interdisciplinary Research – 2021 (ICAIR-2021)</strong><br> 05th - 06th February, 2021</em><br> <em>https://www.sangamuniversity.ac.in/inner-pages/ICAIR-2021.php</em> <strong>Description about the author: </strong>-<br> <strong><em>Mr. Shubham Parsoya,</em></strong><br> <em>Ex-Assistant Professor,<br> School of Management Studies</em> <br> <em><strong>Ph.D.</strong> Doctoral Researcher (Business &amp; Management)</em><br> <em>Master of Business Administration (<strong>MBA</strong>) in (Human Resources Management and<br> Marketing Management) from Guru Gobind Singh Indraprastha University, New Delhi, India</em><br> <em>Bachelor of Commerce (<strong>B.Com</strong>.)</em> <br> <em>Lean Six Sigma Champion Certified Professional (<strong>LSSCCP</strong>),<br> School of Business Leadership Colorado, United States</em><br> <em>Six Sigma Yellow Belt Certified Professional (<strong>SSYBCP</strong>),<br> Project Management Institute</em><br> <em>Accounting Fundamentals Certified Professional (<strong>AFCP</strong>),<br> Corporate Finance Institute, Vancouver, Canada, United States</em>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.795
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.221
GPT teacher head0.429
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it