The COVID-19 Pandemic In US And World History Sample Paper

A coronavirus is a group of viruses that cause infections in both human beings and animals. The strain of the virus experienced globally was known as acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This virus is associated with coronavirus disease 19(COVID-19). Coronavirus pandemic was a global health crisis that the world had felt in ages since World War Two. With different hypotheses on where the virus would have originated, some suggested it spread through bats and pangolins. The first human case of the virus was first tested in Wuhan, China, in December 2019 (Yuki et al.) The virus affected the respiratory organs making it hard for the individual to breathe normally, and hence, were induced to the life support machine. On March 11, 2020, World Health Organization (WHO) declared the virus a global pandemic (Yuki et al.). Ever since, the virus had spread all over the world, causing detrimental economic crises globally.

Precautional measures such as sanitizing, maintaining social distance, avoiding crowded places, and sanitizing alcohol-based solutions were advised to the public, but people still died even after practicing these procedures. The virus caused more deaths to have been recorded worldwide, and more people were dying daily. The health sector tried to develop different vaccines to curb the virus, whereby some were effective, and others failed. The pandemic had paralyzed every industry of each nation health-wise, economically, politically, and religiously. According to Flecknoe et al., the other virus that had such damage was the Spanish flu, also known as Influenza Pandemic of 1918, which lasted for two years, claiming over 500 million people (66).

The coronavirus pandemic had caused havoc for the period it lasted, leaving long-lasting scars in the social, political, and economic sectors of the country it touched. Every day people were losing loved ones, jobs and they were unsure of when the virus would end. The government, non-governmental organizations, and people came to the frontline to help people affected severely by the pandemic, especially in African nations. People lived in fear as they never knew who the virus would attack next and when it would end. This inculcated fear even in the officials in the government as it had taken more people in the leadership position than any other virus.

It was estimated that older adults were at a high risk of contracting the pandemic as their immune systems were weak. Hence, some health officials advised people to lessen visitations. Countries were put under lockdown and curfew hours stipulated to minimize movement. This affected the nation economically as businesses had to close at given hours, making it hard for them to work as they used to before. Politically, many campaign and voting processes had to be changed or not conducted at all. Some nations like the United States advocated for electric voting, which was practiced in certain states like Georgia.

From the time the virus was declared a global pandemic by WHO, people observed precautional measures displayed on different platforms, including social media and television. Even with all these measures, people continued to die, others losing their jobs, and governments turning to ask for help from lenders to borrow loans to stabilize their economy. With the efforts of different medical practitioners and highly enhanced technological equipment in the medicine sector, doctors and scientists came up with other vaccines that worked with fewer side effects. In conjunction with WHO, various organizations looked for safer and effective ways the vaccine could reach billions of people worldwide. The pandemic taught people a viable lesson in terms of hygiene and the need for economic stability in a country.

Work Cited

Flecknoe, Daniel, Benjamin Charles Wakefield, and Aidan Simmons. “Plagues & wars: the ‘Spanish Flu’pandemic as a lesson from history.” Medicine, Conflict and Survival, vol. 34 no. 2, 2018, 61-68.

Yuki, Koichi, Miho Fujiogi, and Sophia Koutsogiannaki. “COVID-19 pathophysiology: A review.” Clinical Immunology, 2020, 108427.

Employee Training And Development

Effective Training Needs Analysis

Training needs analysis refers to the identification process of employees’ development and training needs to enable them to carry out their tasks more efficiently to realize personal and organizational goals. Based on the scenario, the components of an effective training needs analysis include information regarding the sets of skills that the employees have, assessing the skills of current workers, and underscoring employees’ skill gaps. The components allow the company to identify required training that its employees desire to accomplish the organizational goals on safety (Noe, 2020). Training needs analysis provokes numerous queries regarding the analysis like a type of training required, need for specialized training, target persons for the training, cost, course of training, and training outcome.

Based on Noe (2020) basic parts for a successful training program include the following:

  • A program reflective of the strategic plan of the organization to ensure that the program is value-added and addresses the outcomes, programs, and essential issues of the organization directly.
  • Set of values and philosophy that is well-thought-out.
  • Multiple mechanisms and delivery system.
  • Evaluation strategy and design to improve development and training aids constantly.

A plan to warrant the transfer of learning and communication plan to ensure workforce comprehend what activities are available for development and training and how they are associated to enhanced performance.

How to Deliver Training

The organization can create its training program and plan based on ADDIE (Analysis, Design, Development, Implementation, and Evaluation) model. ADDIE model focuses primarily on reflection and iteration, and it is among the most common training needs analysis and design models (Noe, 2020). The stages involved include:


The organization can evaluate the training needs of the workforce by identifying performance gaps or observing the mistakes. Further analysis can be done by identifying learning resources, environment, and characteristics of employees such as their motivation, level of experience, current skills, and knowledge.


The company identifies learning objectives, instructional plans, and assessments. The technique can be done in a manner that reflects the logical flow, and the assessment offer employees feedback on their progress in achieving the training objectives.


The organization develops a performance solution by creating and assembling the content specified in the design stage, review, and validate any required revisions. In this stage, the company can integrate technology during training and associated testing to check for employees’ understanding of the learning content and process.


The training will deliver the performance solution by developing a training framework such as learning space, outcomes, and course curricula. The employees can use any relevant tools and technology for training and remain engaged in the program.


After the training, employees will be evaluated for results concerning the training objectives. The training can first include an interim assessment before implementation to ascertain if the learning resources meet the design requirements followed by summative evaluation once implementation has been done. Summative evaluation determines the effectiveness of training on employee satisfaction, learning, and performance.

In the case study, need theories are selected motivational theory that supports the ADDIE model of training to enhance the organization’s performance. Need theories posit that every person can face needs that are deficient in their expectations (Noe, 2020). In the training program, the needs of trainees should be identified and sessions designed based on the requirements to give better results of the training program. Need theories assist in explaining the value that an individual puts on particular outcomes, and as a result, it motivates them to behave in a manner that satisfies the deficiency (Noe, 2020). Since need theories encourage learning when employees’ needs are fulfilled and safety guaranteed, the ADDIE model effectively promotes organization performance. Effective training is achieved when the employees choose training programs to attend which match their needs.


Noe, R. A. (2020). Employee training and development (8th ed.). McGraw-Hill Education.

Bitcoin And Ethereum: Authority Of Algorithms


In this research paper, the author expands on the Algorithmic authority concept used in day-to-day life. Algorithmic authority is essential to power in algorithms that direct human beings’ actions to affect the information perceived to be right. The author concentrates more on theories behind blockchain’s algorithmic technology and the importance of commonality throughout purchases in the blockchain realm, specifically looking at transactional methods. Tying the power of algorithmic authority with cryptocurrency, specifically bitcoin and ethereum, the study deeply explores the algorithmic authority concept in transactions. In this study, the data used are from interviews, surveys, and the bitcoin community information. The focus is on the bitcoin community that prefers algorithmic authority to the integration of bitcoin into the institution.

The author chooses bitcoin as an example because it is purely managed by algorithms and not banks or governments, thus giving a clear understanding of algorithmic authority. The bitcoin algorithms were established by the Bitcoin source community and applied in the decentralized network of bitcoin. He also used ethereum because it supports all computational methods and is considered better than the blockchain structure. Ethereum symbolizes a blockchain with built-in Turing-complete programming language.


In this paper, the research is about algorithms, bitcoin, and ethereum, how they function in transactions, why they are important to Algorithmic authority, and the power of commonality in blockchain technology cryptocurrency. Algorithmic authority is “the fundamental entity with which computer scientists operate” (Gillespie, Boczkowski, and Foot 2014). Algorithms play not only critical roles in software but also in economic, social, and political development. Algorithmic authority is all about trust that the people controlling the coding can act in the right way (Yavuz et al. 2018). In simple terms, algorithmic authority is about authenticating information and controlling humans’ actions by algorithms relying on the authority of humans.


This research uses data from the survey conducted, interviews, and the information obtained from articles, blogs, and posts from the bitcoin community forum. The formal and informal interviews conducted availed much data on bitcoin technology and ethereum and how they function in transactions (Yavuz et al. 2018). The data obtained from blogs and articles provided much information on the importance of bitcoin and ethereum authority of algorithms and the power of commonality and theories behind the algorithmic authority.

The survey was conducted on two reputable sites, and /r/Bitcoin, which are popular among bitcoin users. 30 questions were posted on reasons for using bitcoin and ethereum, government regulations, and the future of bitcoin and ethereum (Bach, Mihaljevic, and Zagar 2018). Some questions were open-ended on the anonymity of bitcoin. Since there was an option for participants to leave their contacts, 100 out of 400 people that participated in the survey left their contacts for the interview.

Using information from the survey, interview questions that linked to the obtained responses were drafted. The method applied was a combination of semi-structured and exploratory interviews to acquire more information on the use of bitcoin and ethereum. Avoiding participants who gave short replies to queries and those that never attempted long queries, interviewed half of the participants took part in the interview (Bach, Mihaljevic, and Zagar 2018). Mediums such as emails, telephone, Skype, and messaging based on participants’ choice were used.

During the study, observation was also used by reading several posts, blogs, and articles on the Bitcoin Community. The blogs and posts read focused on what bitcoin and ethereum are and how they function in transactions. Articles that addressed the views of bitcoin and ethereum users were read as well. The study also focused on the theories behind algorithmic authority and the power of commonality. The articles also availed data on bitcoin uses in payment, including illegal use of bitcoin. An attempt to mine bitcoin failed because of a lack of appropriate software.

Attending a seminar on the use and future of bitcoin hosted by Orange Count Tech hour, where additional information on bitcoins’ function in transactions was gathered, was also useful for the research. Collected data was through screenshots, emails, messages, videos, and photographs. The methodology applied in this study enabled the gathering of relevant, necessary, and enough information concerning bitcoin, algorithm authority, and ethereum.


Bitcoin is a computer folder in a wallet that is digital or digital money and payment platform with no transaction fees and functions in micro-transactions. Bitcoin was created to function as cash in digital design. The development of bitcoin occurred during the Great Recession in 2008 (Gillespie and Seaver 2016). According to Bach, Mihaljevic, and Zagar (2018), there was a higher unemployment rate arising from the financial crisis experienced during that time. The housing cost and stock market made many Americans negative.

Gillespie (2010) said that bitcoin’s introduction first occurred in a white paper by Satoshi Nakamoto, who is believed to be bitcoin’s first creator. He was inspired to create digital currency due to the challenges experienced by electronic commerce. Satoshi claimed that electronic commerce was associated with a lack of privacy to its users and high operation cost (Gillespie 2010). Satoshi wanted to reduce the double-spending cost related to the external party in electronic commerce. There was high transaction cost incurred through double-spending, lack of privacy, and a high probability of money reversal by the third parties. Bitcoin was designed to be digital and managed by distributed and decentralized P2P network.

Why Bitcoin

Bitcoin was chosen for this study because it is more of an algorithm that is heteromated, open-source, and regionalized than critical algorithms studies that are recommender, online search, or targeted advertising (Gillespie and Seaver 2016). Below are the described weaknesses of critical algorithms study over open-source algorithms such as bitcoin. Open source algorithms aid in the easy understanding of algorithmic authority. The following are some of the weaknesses related to critical algorithm research.

First, it does not provide information on the development of algorithms. It is not clear how the researchers in the required algorithm field explain powerful algorithms but do not concentrate on developing the algorithms. Open source algorithms such as bitcoin provide detailed information on algorithms’ power and development (Fuller 2008). Second, critical algorithms do not explain the behaviors of workers when operating the algorithmic systems. Lack of this behavioral understanding limits researchers’ study to assist the algorithm users (Fuller 2008). These critics support the use of open algorithms such as bitcoin in this study.

How Bitcoin Functions in Transactions

Peer software checks if the amount transacted has not been double spent by checking the ledger when a transaction is done. The ledger contains all the transaction records or information. Transactions that have been verified are assembled into blocks through the blockchain then appear in the public ledger (Bach, Mihaljevic, and Zagar 2018). It is difficult to fake the blocks since cryptographic hash algorithm functions connect them. Each block has a specific position marked by the harsh preventing fake currency fraud. The blockchain creates a fork to differentiate the mined blocks within a short period or at the same time. The longest part of the fork becomes the immediate blockchain while the rest is rejected.

Greenspan (2015) describes bitcoin mining as a means of regeneration of new bitcoins, and whenever it occurs, the blocks are formed and added to the blockchain. The mining of bitcoins controls its growth rate. Moreover, the mining of bitcoins helps in eliminating the distribution of currency from a centralized organization. The current bitcoin code shows that 21million bitcoins exist, but the number can be increased by changing the code. Havening of bitcoins occurs after every four years of mining. It is estimated that the 21million will have been mined by 2040 (Greenspan 2015).

Several attacks are discussed on bitcoins, such as majority attack and 25% mining power attack. In the majority attack, double spending, reversing transactions, or barring transactions can occur in the case of fast mining. Mining power centralization seemed a key concern to the participants, but mining has been more integrated over the years. Blockchain also functions as smart contracts and records of ownership storage platforms (Grinberg 2011). Furthermore, transactions for buying and selling products between individuals can be carried out by bitcoin. Blockchain is widely applied in the healthcare sector to keep records such as transactions (Gregory 2000).


Among the most popular cryptocurrency, Ethereum is the second in popularity ranking immediately after Bitcoin (Mingxiao et al. 2017). Thus, it is important to know how the Ethereum platform operates and to distinguish between Bitcoin and Ethereum themselves. It will also be relevant to go deeper and study the design features of Ethereum together with its various applications (Mingxiao et al. 2017).

On the fast interaction, one may ask the meaning of Ethereum. In summary, Ethereum is one of the blockchain technology-based computing podiums, where designers can build and deploy a decentralized application (Mingxiao et al. 2017). In other words, Ethereum is a computing platform that does not depend on a centralized authority to function. Ethereum enables creating a decentralized application giving authority of deciding to the members of that application (Vujičić, Jagodić, and Ranđić 2018).

Ethereum Features

Ethereum has five main features: Ether, smart contract, Ethereum virtual machine, decentralized application, and decentralized autonomous organization (Vujičić, Jagodić, and Ranđić 2018).


The mode of payment in Ethereum cryptocurrency is known as ether. It has several uses since it is the main fuel source that operates the platform network (Vujičić, Jagodić, and Ranđić 2018). One of the uses of Ethereum is to reward for computational resources and charge any transaction that is carried out within the network of Ethereum (Fairley 2018). Another medium used to pay for computation transactions within the Ethereum network is gas purchased using ether. Therefore, ether is the core center of Ethereum because it is used to construct smart contracts, create decentralized applications, and make systematic peer-peer expenses (Dannen 2017).

Smart Contracts

Within Ethereum, a smart contract is a computerized program that can facilitate converting goods or assets from one party to another (Vujičić, Jagodić, and Ranđić 2018). These asserts for exchange are different depending on the parties, and they include shares, money, property, even digital asserts. The contracts are the standings and conditions in the process of creating the platform that both parties have agreed on (Vujičić, Jagodić, and Ranđić 2018).

The smart contracts cannot be changed immediately after the contract is put in place. The transactions that are done on the smart contracts are also stored enduringly (Dannen 2017). It is impossible to alter or edit the smart contract transaction even in future modification because of these features.

The smart contract implementation is decentralized because centralized authority is not required during smart contract verification since the process is done by anonymous parties of the network (Gillespie, Boczkowski, and Foot 2014). With the smart contract, trust between the two parties is created. Every transaction operated within the platform is transparent and trusted with the parties’ identities locked within the network. In a smart contract, trust is also created by immediately updating the accounts of the parties doing the transaction (Fairley 2018).

Ethereum Virtual Machine

EVM is the sector of Ethereum that recognizes the language of smart contracts, and this language is always written in the solidity for Ethereum (Gregory 2000). It functions mainly in a sandbox environment. The smart contract programing language is assembled into the bytecode, and this is the language that EVM understands. The smart contract is Witten in Solidity, which is then converted into bytecode and operated on EVM. EVM helps to protect Ethereum from cyber hackers (Gregory 2000).

Decentralized Applications (Dapps)

It is a composite of a backing code that goes through and across the peer-to-peer network. Dapps is software formed to operate without the centralized authority within the Ethereum network (Greenspan 2015). Dapps provides a platform for direct interaction between the end-users and its providers. An application is qualified to be a Dapps as long as its code is Github and can utilize a public blockchain to operate the application. For the Dapp to operate, fuel is required, and the token is always used as fuel (Aung and Tantidham 2017).

Decentralized Autonomous Organizations (DAOs)

A DAO functions in a decentralized and democratic way because it is a digital organization that even without ordered supervisions (Gillespie 2010). In the organization, the decision-making is done by appointed authorities or even assigned people or groups but never is the decision-making centralized. The smart contract protocols control DAO; hence, it depends on the contracts to function (Yavuz et al. 2018). Because of the dependency, every decision made within the organization is going through the voting procedure.

Applications of Ethereum to the Real World

Most countries’ voting systems have changed due to adopting the uses of DAO of Ethereum. In these nations, the voting results are made available to the public; this enables the voting process to be a transparent and fair electoral process, eliminating election violations (Gillespie, Boczkowski, and Foot 2014). Most of the banking system has also adopted the use of Ethereum to decentralize their banking system. With this kind of structure, unauthorized access by cyber hackers is drastically reduced (Gillespie, Boczkowski, and Foot 2014). Banks that have adopted Ethereum also use it as a mode of making payments on Ethereum networks.

Bitcoin versus Ethereum

Bitcoin blockchain and ethereum are similar, with slight differences in block composition. Ethereum is the most recent blockchain which has block number, transaction list, nonce, and difficulty (Al-Jaroodi and Mohamed 2019). To get the current state, the former state is applied. The main distinction between Bitcoin, the most popular, and Ethereum is the hashing algorithm. Bitcoin uses the SHA-256 hashing algorithm, while the Ethash hashing algorithm is used for Ethereum (Gillespie and Seaver 2016). In Ethereum, it only takes an average of about 12 to 15 seconds for mining a block which takes 10mins for mining in the case of Bitcoin. The value of Bitcoin is higher than that of Ether that is one Bitcoin is equivalent to $5249.03 while one ether is $180.89 as per April 2019 (Gillespie, Boczkowski, and Foot 2014).

Bitcoin and Ethereum as an Example of Emergent Algorithmic Authority

Humans facilitated algorithmic authority, and many bitcoin users have turned to it (Gillespie, Boczkowski, and Foot 2014). The algorithmic authority has some difficulties and strains from the gathered information. From the interview and surveys, many bitcoin users prefer algorithmic authority to institutions due to trust issues. Many participants viewed bitcoin as apolitical, giving it a higher preference to government banks. Algorithms that govern bitcoin are considered as not partial and lacking corruption.

According to Gillespie and Seaver (2016), Ethereum applies Proof-of-work (PoW) algorithm to achieve its operations. PoW algorithm has several challenges, and fraud is one of them due to the inability to do reverse transactions (Al-Jaroodi and Mohamed 2019). Suppose someone transacts with a wrong person or gets conned; it is impossible to reverse such transactions. Sealing of blocks in PoW authority requires recognized signers (Al-Jaroodi and Mohamed 2019). No hash minings are required, as in the case of bitcoins. By using signers, there a gap since the signers can be changed, added, or removed from the list in case of suspected malicious activity. Despite the few downsides of PoW, its most reliability and security are ensured for the users (Gillespie 2010).


Further research should be done on how algorithmic authority can be upgraded to empower users. Moreover, transparency, decentralization, and openness should be further studied as bitcoin aspects that can solve the closed algorithm weaknesses. Such studies could better audit algorithm biasness. Further studies in critical algorithms should be done to broaden the range of algorithmic authority understanding.

This paper studied the algorithmic authority concept and how bitcoin and ethereum are important to the authority. Bitcoin blockchain and ethereum are similar, with slight differences in block composition. It found that most bitcoin users believe in their judgments as well as the code. Algorithmic authority is not just found in a code but diverse socio technical actants. Most participants’ opinions were that a disruptive authority would result from bitcoin; institutions’ centralization does not hinder bitcoin appeal.

With the evolution in bitcoin, understanding centralization will require more studies to solve the opposition it is facing by the bitcoin users. These studies will as well help in understanding algorithmic authority decentralization. Little research has been carried out on bitcoin users in the current world; more research is necessary. Several changes have occurred in the bitcoin community over the years; thus, research has to be updated to understand algorithmic applications to bitcoin by the current users.


Al-Jaroodi, Jameela, and Nader Mohamed. 2019. “Blockchain in Industries: A Survey.” Web.

Aung, Yu Nandar, and Thitinan Tantidham. 2017. “Review of Ethereum: Smart Home Case Study.” 2017 2nd International Conference on Information Technology (INCIT) (November): 1-4. Web.

Bach, Leo Maxim, Branko Mihaljevic, and Mario Zagar. 2018. “Comparative Analysis of Blockchain Consensus Algorithms.” 2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO): 1545-1550. Web.

Dannen, Chris. 2017. Introducing Ethereum and Solidity. Berkeley: Apress.

Fairley, Peter. 2018. “Ethereum will Cut Back its Absurd Energy Use.” IEEE Spectrum 56, no. 1: 29-32. Web.

Fuller, Matthew. 2008. Software Studies: A Lexicon. Cambridge: MIT Press.

Gillespie, Tarleton, and Nick Seaver. 2016. “Critical Algorithm Studies: A Reading List.” Social Media Collective.

Gillespie, Tarleton, Pablo J. Boczkowski, and Kirsten A. Foot, eds. 2014. Media Technologies: Essays on Communication, Materiality, and Society. Cambridge: MIT Press.

Gillespie, Tarleton. 2010. “The Politics of ‘Platforms’.” New Media & Society 12, no. 3: 347-364.

Greenspan, Gideon. 2015. “Smart Contracts: The Good, the Bad and the Lazy.” Multichain.

Gregory, Judith. 2000. “Sorcerer’s Apprentice: Creating the Electronic Health Record, Re-inventing Medical Records and Patient Care.” PhD diss., University of California.

Grinberg, Reuben. 2011. “Bitcoin: An Innovative Alternative Digital Currency.” Hastings Science & Technology Law Journal 4, no. 1: 160. Web.

Mingxiao, Du, Ma Xiaofeng, Zhang Zhe, Wang Xiangwei, and Chen Qijun. 2017. “A Review on Consensus Algorithm of Blockchain.” 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC): 2567-2572. Web.

Vujičić, Dejan, Dijana Jagodić, and Siniša Ranđić. 2018. “Blockchain Technology, Bitcoin, and Ethereum: A Brief Overview.” 2018 17th International Symposium Infoteh-jahorina (infoteh): 1-6. Web.

Yavuz, Emre, Ali Kaan Koç, Umut Can Çabuk, and Gökhan Dalkılıç. 2018. “Towards Secure e-Voting Using Ethereum Blockchain.” 2018 6th International Symposium on Digital Forensic and Security (ISDFS), :1-7. Web.

error: Content is protected !!