Computer Terms #4 | Quizalize

Analysis is a method of organizing, sorting, and scrutinizing data in such a way that a research question can be answered or meaningful inferences can be drawn. 4 2. Bibliography is a list of all the sources used in the process of researching. 3. Concept refers to a mental idea of a phenomenon. These are words or terms that symbolize some aspects of reality. e. g. love, pain. 4. Conclusion provides a summary of the research. 5. Data is an information that can be words or numbers. 6. Data Gathering Tools refer to the devices/ instruments used to collect data such as questionnaire or computer- assisted interviewing system. 7. Data Presentation involves the use of a variety of different graphical techniques. 8. Descriptive study is a research design that describes “what is”( e.g. a survey). 9. In-Text Citation is the brief form of the reference included in the body of one’s work. 10. Limitations are restrictions in a study that may decrease the credibility and generalizability of the research findings. 11. Literature review is a critical summary or research on a topic of interest, generally prepared to put a research problem in context or to identify gaps and weaknesses in prior studies so as to justify a new investigation. 12. Plagiarism is the unethical practice of using words or ideas of another author/researcher without proper acknowledgement. 13. Quantitative Research is the process of collecting and analyzing numerical data. 14. Questionnaire is a set of questions used to gather information in a survey. 15. Research Topic is a subject or issue that a researcher is interested in when conducting a research. 16. Respondents are those persons who have been invited to participate in a particular study and have actually taken part in the study. 17. Research Question is the question around which a researcher centers his/ her research. 18. Sample is a part or subset of population selected to participate in the research study. 19. Socio Demographic Profile includes age, sex, education, migration, background and ethnicity, religious affiliation, marital status, household, employment, and income. 20.Variables are attributes or characteristics that can have more than one value, such as height or weight. These are qualities or quantities, properties or characteristics of people, things, or situations that change or vary

New Trends in Agriculture Extension approaches Extension has been, and still is, under attack from a wide spectrum of politicians and economists over its cost and financing. As a result, Extension Systems have had to make changes, by restating the system’s mission, developing a new vision for the future, and formulating plans for the necessary transition to achieve the desired change. 1. Privatization of Agricultural Extension Service Privatization: Process of funding and delivering the extension services by private individual or organization is called Private Extension. Concept: Privatization of extension refers to services rendered in rural area & allied aspects of extension personnel working in private agencies or organization for which farmers are expected to pay a fee & it can be viewed as supplementary or alternative to public extension services (Sarvanan & Shivalinge 1980). Privatization approaches ➢ Share cropping system ➢ Village extension contract system ➢ Public extension through private delivery ➢ Service for vouchers Strengths of Private Extension System ➢ More demand - driven rather than supply – driven ➢ High quality of services in terms of satisfying information needs of clientele, trained manpower, sustained finances and resource allocation ➢ Provides for an information mix and choices available to farmers ➢ Enhanced efficiency of staff ➢ Assure continuous supply and quality agricultural products ➢ More effective because farmer can select an adviser who is the best able to help ➢ Healthy competition among service provider will lead to better quality and lower costs for service Weakness of Private Extension System ➢ Concentrate on area having favorable physical environment ➢ More face-to-face contacts (person oriented) ➢ Increased dependence of farmers and hence exploitation ➢ No education role ➢ Deprivation of small farmers ➢ Hamper the free flow of information 2. Cyber Extension or e-extension Concepts Cyber space: it is the imaginary or virtual space of computers connected with each other on Networks, across the Globe. Cyber extension: it means 'using the power of online networks, computer communications and digital interactive multimedia to facilitate dissemination of agriculture technology. Cyber Extension thus can be defined as the extension over cyber space. Important tools of cyber extension E-Mail, Telnet, File Transfer Protocol (FTP), Gopher, Archie and World Wide Web (WWW) Strengths of Cyber Extension ➢ Access to the astounding information and continuously available ➢ Information rich and instantaneously available of information ➢ Interactive communication ➢ The information is available from any point on the globe ➢ Communication is dynamic ➢ Cut steps from traditional process ➢ Save money, time and effort ➢ Multiplicity of purpose Issues and Concerns of Cyber Extension ➢ Lack of Reliable Telecom Infrastructure in Rural Areas ➢ Erratic or no Power Supply ➢ Lack of ICT Trained manpower (willing to serve) in Rural Areas ➢ Lack of content (locally relevant and in local languages) ➢ Lack of Information Services to Rural Clientele ➢ Low Purchasing power of the Rural communities ➢ Lack of Holistic Approaches ➢ Issues of Sustainability Application of cyber extension ➢ Village information shops Dr. M.S. SwaminathanResearch Foundation, Chennai ➢ Information villagers MANAGE in Ranga Reddy District in Andhra pradesh ➢ Gyandoot net initiative of District Dhar, Madhya Pradesh. ➢ Warna wired village of National Informatics Center (NIC) in Kolhapur- Sangli Districts of Maharashtra 3. Market-Led-Extension (MLE) Concepts Market: A congregation of prospective buyers & sellers with a common motive of trading a particular commodity. Extension: It is the spreading/reaching out to the mass Market-led-extension: Agriculture & economics coupled with extension is the perfect blend for reaching at the door steps of common man with the help of technology. Dimensions of market-led extension ➢ Marketing mix: A planned mix of the controllable elements of a product's marketing plan commonly termed as 4Ps: product, price, place, and promotion. These four elements are adjusted until the right combination is found that serves the needs of the product's customers, while generating optimum income. ➢ Marketing plan: A marketing plan is a comprehensive document that outlines a business and marketing efforts for the coming year. It describes business activities involved in accomplishing specific marketing objectives within a set time frame. A marketing plan also includes a description of the current marketing position of a business, a discussion of the target market and a description of the marketing mix that a business will use to achieve their marketing goals. ➢ Market Intelligence: It is the information relevant to a company’s markets, gathered and analyzed specifically for the purpose of accurate and confident decision making. Market intelligence includes the process of gathering data from the company’s external environment, whereas the business intelligence process is primarily based on internal recorded events – such as sales, shipments and purchases. ➢ Market oriented production ➢ Use of Technology Strengths of market-led extension ➢ SWOT analysis of the market ➢ Organization of Farmers’ Interest Groups (FIGs) ➢ Enhancing the interactive and communication skills of the farmers ➢ Establishing marketing and agro-processing linkages ➢ Advice on product planning ➢ Educating the farming community ➢ Direct marketing ➢ Acquiring complete market intelligence ➢ Publication of agricultural market information Production of video films of success stories ➢ Challenges to market-led extension ➢ Gigantic size of extension system ➢ Information technology Diverse conditions ➢ Market intelligence ➢ Reforms in agricultural extension system Government Initiatives ➢ Central warehousing Corporation-1965 ➢ MSP by Commission for Agricultural Cost and Price (CACP) ➢ Food Corporation of India ➢ Then some others as: Cotton Corporation of India (CCI), Jute Corporation of India (JCI), National Dairy Development Board (NDDB), Agriculture and Processed food Export Development Authority (APEDA) etc. 4. Farmer--Led-Extension (FLE) Farmer--led-extension is defined as 'the provision of training by farmers to farmers, often through the creation of a structure of farmer promoters and farmer trainers' (Scarborough et al., 1997). Philosophy and principles ➢ Farmers and local institutions (e.g. producer organizations or village leaders) should play a key role in selecting farmer-trainers and monitoring and evaluating them. This helps make the programmes more accountable to the community or groups that they serve. ➢ Farmer-trainers are ‘of the community’; they communicate in local languages and are more sensitive to local cultures, mannerisms, farming practices, and farmers’ needs. ➢ Farmer-trainers should be selected on the basis of their skills and interest in sharing information, not just on their farming expertise. ➢ Farmer-trainers need strong linkages with and support from development agents (whether government, non-government organization (NGO), or private), the people who train and backstop them. Farmer-trainers generally serve as a complement to existing extension systems, rather than being a substitute for them. ➢ Facilitating organizations and local institutions need to be proactive in ensuring that women as well as men become farmer-trainers. ➢ Simple and appropriate reference materials should be made available to the farmer trainers. Essential Elements of Farmer--led-extension ➢ The group ➢ The Field ➢ The Facilitator ➢ The curriculum ➢ Programme leader ➢ Financing Special features of Farmer--led-extension ➢ All learning is field based & it is primary venue for learning ➢ FLE group learning constantly over the experimentation period ➢ FLE promotes healthy decisions & quality decisions ➢ Farmers conduct their own field studies with comparisons or treatments ➢ Facilitates Farmer-to-Farmer communication ➢ Field staff serve as facilitators ➢ FLE is a unique way to educate farmers ➢ It is an effective platform for sharing of experiences and collectively solving agriculture related problems. 5. Expert system Expert system is an intelligent computer program that uses knowledge and inferences procedures to solve problems (Daniel Hunt, 1986). Objectives of developing expert system ➢ To enhance the performance of agricultural extension personnel and farmer ➢ To make farming more efficient and profitable ➢ To reduce the time required in solving the problems ➢ To maintain the expert system by continuously upgrading the database Advantages of expert system ➢ Solves critical problems by making logical deductions without taking much time ➢ It combines experimental and conventional knowledge with the reasoning skills of specialists ➢ To enhance the performance of average worker to the level of an expert Limitations of expert system ➢ Expensive computer program ➢ Mostly developed not in regional languages ➢ Requires AC power and internet connection all the time ➢ Complex software requires computer skilled personnel Modules of expert system in agriculture ➢ COMAX: Integrated crop management in cotton ➢ SOYEX: Soybean oil extraction expert system ➢ PLANT/ds: Diagnosis of soybean diseases ➢ MAIZE: Maize expert system for field crop management ➢ SEMAGI: Weed control decision making in sunflowers ➢ Rice Crop Doctor: Developed by National Institute of Agricultural Extension Management (MANAGE) Difference between conventional and expert system of extension Conventional Extension ➢ Universal approachability of same information is a problem ➢ Information is given whatever is available without considering needs and resources ➢ No Cost benefit analysis ➢ Information flow depends on availability of agent ➢ Require users to draw their own conclusion from facts Expert System of Extension ➢ Universal approachability of same information is possible ➢ Information is chosen based on their needs and resources ➢ Cost benefit analysis ➢ Information through Cyber Cafe at any place at any time ➢ Conclusion is drawn based on the decision given by the expert

Revealing personal data can lead to threats like identity theft, fraud, bullying, and blackmail. 1.Identity Theft Definition: Identity theft occurs when someone steals your personal information and uses it without your permission. This can include your name, Social Security number, or bank details. Example: If someone gets your Social Security number, they could open a credit card in your name and run up bills that you would have to pay. 2.Fraud Definition: Fraud is when someone deceives another person to gain something of value, like money or personal information. This is often done through lies or tricks. Example: A person might call you pretending to be from your bank and tell you that you need to confirm your account details. If you give them your information, they may steal your money. 3. Bullying Definition: Bullying is when someone repeatedly hurts, threatens, or picks on another person. This can happen in person or online (cyberbullying). Example: If someone sends hurtful messages or spreads rumors about you on social media, that’s a form of bullying. 4. Blackmail Definition: Blackmail is when someone threatens to reveal harmful or embarrassing information about you unless you give them something they want, usually money or favors. Example: If someone takes a private photo of you and threatens to share it unless you pay them, that’s blackmail. Summary Identity Theft: Stealing personal information for illegal use. Fraud: Deceiving someone for personal gain. Bullying: Repeatedly hurting or threatening someone. Blackmail: Threatening to expose information unless demands are met. Understanding these terms helps you recognize and protect yourself from potential dangers in both real life and online. If you see any signs of these actions happening, it’s important to talk to a trusted adult or authority figure. There are several guidelines for you to be aware of to keep your personal data confidential: •Have strong passwords set on any account that holds personal data. Stronger passwords include characters, numbers and symbols and are not a recognisable word. •Encrypt (scramble text so that it cannot be read without a decryption key) any personal data that you store on your computer. •Have a firewall present, scanning incoming and outgoing data from your computer system. firewall : a security measure that can be implemented to monitor traffic into and out of a computer and prevent external users gaining unauthorised access to a computer system. A firewall is a security measure that helps protect a computer system by monitoring and controlling the traffic that comes into and goes out of the system. Think of it as a barrier between your computer and the outside world. It prevents unauthorized users from accessing your computer while allowing authorized traffic to pass through. •Regularly scan your computer with preventative software, such as an anti-virus package, that is used to identify a virus on a computer and remove it. Anti-virus: software that is used to identify a virus on a computer and remove it •Make use of any biometric devices (devices that measures a person's biological data, such as thumbprints), that are built into technology. biometric devices: Unique physical characteristic of a person that can be used by a computer for identification purposes. https://www.aratek.co/news/biometric-devices-definition-and-examples Biometric devices are tools that use unique physical characteristics of a person for identification purposes. This means they can recognize who you are based on features that are unique to you. Here are some examples of biometric characteristics: Fingerprint Recognition, Facial Recognition, Voice Recognition •Only visit and provide data to websites that are a trusted source. •Do not open any email attachments from a sender you do not recognise. •Check the URL attached to any link requesting data to see if it is genuine. •Be cautious about any pictures or opinions that you post or send to people. •Remove data about your location that is normally attached to your photos and videos that you may post, such as geotags. Geotag: an electronic tag that assigns a geographical location A geotag is an electronic tag that assigns a specific geographical location to a piece of information, like a photo or a video. Geotags can help people understand where a photo was taken or where an event occurred, making it easier to organize and find information based on location. •Do not become friends on social networking sites with people you do not know. •Set all the privacy controls to the most secure setting that are available on social media accounts. •Report and block any suspicious user. •Use a nickname or pseudonym when using the internet for entertainment, for example, playing games. •If it is possible, use a virtual private network (VPN), an encrypted connection that can be used to send data more securely across a network. Virtual private network (VPN) : an encrypted connection that can be used to send data more securely across a network A Virtual Private Network (VPN) is a special way to connect to the internet that keeps your information safe. Imagine you are sending a secret message to a friend. You want to make sure no one else can read it while it travels. A VPN helps you do just that! It creates an encrypted connection, which means it turns your message into a code that only your friend can understand Example: Public Wi-Fi Safety: When you use public Wi-Fi, like in a café, your data can be easily accessed by hackers. If you connect to a VPN while using that public Wi-Fi, your data is encrypted, making it much harder for anyone to steal your information.

“There’s No Such Thing as Sound Science” by By Christie Aschwanden was a lead science writer for FiveThirtyEight. FiveThirtyEight, Science, Dec. 6, 2017 Science is being turned against itself. For decades, its twin ideals of transparency and rigor have been weaponized by those who disagree with results produced by the scientific method. Under the Trump administration, that fight has ramped up again. In a move ostensibly meant to reduce conflicts of interest, Environmental Protection Agency Administrator Scott Pruitt has removed a number of scientists from advisory panels and replaced some of them with representatives from industries that the agency regulates. Like many in the Trump administration, Pruitt has also cast doubt on the reliability of climate science. For instance, in an interview with CNBC, Pruitt said that “measuring with precision human activity on the climate is something very challenging to do.” Similarly, Trump’s pick to head NASA, an agency that oversees a large portion the nation’s climate research, has insisted that research into human influence on climate lacks certainty, and he falsely claimed that “global temperatures stopped rising 10 years ago.” Kathleen Hartnett White, Trump’s nominee to head the White House Council on Environmental Quality, said in a Senate hearing last month that she thinks we “need to have more precise explanations of the human role and the natural role” in climate change. The same entreaties crop up again and again: We need to root out conflicts. We need more precise evidence. What makes these arguments so powerful is that they sound quite similar to the points raised by proponents of a very different call for change that’s coming from within science. This other movement strives to produce more robust, reproducible findings. Despite having dissimilar goals, the two forces espouse principles that look surprisingly alike: Science needs to be transparent. Results and methods should be openly shared so that outside researchers can independently reproduce and validate them. The methods used to collect and analyze data should be rigorous and clear, and conclusions must be supported by evidence. These are the arguments underlying an “open science” reform movement that was created, in part, as a response to a “reproducibility crisis” that has struck some fields of science.1 But they’re also used as talking points by politicians who are working to make it more difficult for the EPA and other federal agencies to use science in their regulatory decision-making, under the guise of basing policy on “sound science.” Science’s virtues are being wielded against it. What distinguishes the two calls for transparency is intent: Whereas the “open science” movement aims to make science more reliable, reproducible and robust, proponents of “sound science” have historically worked to amplify uncertainty, create doubt and undermine scientific discoveries that threaten their interests. “Our criticisms are founded in a confidence in science,” said Steven Goodman, co-director of the Meta-Research Innovation Center at Stanford and a proponent of open science. “That’s a fundamental difference — we’re critiquing science to make it better. Others are critiquing it to devalue the approach itself.” Calls to base public policy on “sound science” seem unassailable if you don’t know the term’s history. The phrase was adopted by the tobacco industry in the 1990s to counteract mounting evidence linking secondhand smoke to cancer. A 1992 Environmental Protection Agency report identified secondhand smoke as a human carcinogen, and Philip Morris responded by launching an initiative to promote what it called “sound science.” In an internal memo, Philip Morris vice president of corporate affairs Ellen Merlo wrote that the program was designed to “discredit the EPA report,” “prevent states and cities, as well as businesses from passing smoking bans” and “proactively” pass legislation to help their cause. The sound science tactic exploits a fundamental feature of the scientific process: Science does not produce absolute certainty. Contrary to how it’s sometimes represented to the public, science is not a magic wand that turns everything it touches to truth. Instead, it’s a process of uncertainty reduction, much like a game of 20 Questions. Any given study can rarely answer more than one question at a time, and each study usually raises a bunch of new questions in the process of answering old ones. “Science is a process rather than an answer,” said psychologist Alison Ledgerwood of the University of California, Davis. Every answer is provisional and subject to change in the face of new evidence. It’s not entirely correct to say that “this study proves this fact,” Ledgerwood said. “We should be talking instead about how science increases or decreases our confidence in something.” The tobacco industry’s brilliant tactic was to turn this baked-in uncertainty against the scientific enterprise itself. While insisting that they merely wanted to ensure that public policy was based on sound science, tobacco companies defined the term in a way that ensured that no science could ever be sound enough. The only sound science was certain science, which is an impossible standard to achieve. “Doubt is our product,” wrote one employee of the Brown & Williamson tobacco company in a 1969 internal memo. The note went on to say that doubt “is the best means of competing with the ‘body of fact’” and “establishing a controversy.” These strategies for undermining inconvenient science were so effective that they’ve served as a sort of playbook for industry interests ever since, said Stanford University science historian Robert Proctor. The sound science push is no longer just Philip Morris sowing doubt about the links between cigarettes and cancer. It’s also a 1998 action plan by the American Petroleum Institute, Chevron and Exxon Mobil to “install uncertainty” about the link between greenhouse gas emissions and climate change. It’s industry-funded groups’ late-1990s effort to question the science the EPA was using to set fine-particle-pollution air-quality standards that the industry didn’t want. And then there was the more recent effort by Dow Chemical to insist on more scientific certainty before banning a pesticide that the EPA’s scientists had deemed risky to children. Now comes a move by the Trump administration’s EPA to repeal a 2015 rule on wetlands protection by disregarding particular studies. (To name just a few examples.) Doubt merchants aren’t pushing for knowledge, they’re practicing what Proctor has dubbed “agnogenesis” — the intentional manufacture of ignorance. This ignorance isn’t simply the absence of knowing something; it’s a lack of comprehension deliberately created by agents who don’t want you to know, Proctor said.2 In the hands of doubt-makers, transparency becomes a rhetorical move. “It’s really difficult as a scientist or policy maker to make a stand against transparency and openness, because well, who would be against it?” said Karen Levy, researcher on information science at Cornell University. But at the same time, “you can couch everything in the language of transparency and it becomes a powerful weapon.” For instance, when the EPA was preparing to set new limits on particulate pollution in the 1990s, industry groups pushed back against the research and demanded access to primary data (including records that researchers had promised participants would remain confidential) and a reanalysis of the evidence. Their calls succeeded and a new analysis was performed. The reanalysis essentially confirmed the original conclusions, but the process of conducting it delayed the implementation of regulations and cost researchers time and money. Delay is a time-tested strategy. “Gridlock is the greatest friend a global warming skeptic has,” said Marc Morano, a prominent critic of global warming research and the executive director of ClimateDepot.com, in the documentary “Merchants of Doubt” (based on the book by the same name). Morano’s site is a project of the Committee for a Constructive Tomorrow, which has received funding from the oil and gas industry. “We’re the negative force. We’re just trying to stop stuff.” Some of these ploys are getting a fresh boost from Congress. The Data Quality Act (also known as the Information Quality Act) was reportedly written by an industry lobbyist and quietly passed as part of an appropriations bill in 2000. The rule mandates that federal agencies ensure the “quality, objectivity, utility, and integrity of information” that they disseminate, though it does little to define what these terms mean. The law also provides a mechanism for citizens and groups to challenge information that they deem inaccurate, including science that they disagree with. “It was passed in this very quiet way with no explicit debate about it — that should tell you a lot about the real goals,” Levy said. But what’s most telling about the Data Quality Act is how it’s been used, Levy said. A 2004 Washington Post analysis found that in the 20 months following its implementation, the act was repeatedly used by industry groups to push back against proposed regulations and bog down the decision-making process. Instead of deploying transparency as a fundamental principle that applies to all science, these interests have used transparency as a weapon to attack very particular findings that they would like to eradicate. Now Congress is considering another way to legislate how science is used. The Honest Act, a bill sponsored by Rep. Lamar Smith of Texas,3 is another example of what Levy calls a “Trojan horse” law that uses the language of transparency as a cover to achieve other political goals. Smith’s legislation would severely limit the kind of evidence the EPA could use for decision-making. Only studies whose raw data and computer codes were publicly available would be allowed for consideration. That might sound perfectly reasonable, and in many cases it is, Goodman said. But sometimes there are good reasons why researchers can’t conform to these rules, like when the data contains confidential or sensitive medical information.4 Critics, which include more than a dozen scientific organizations, argue that, in practice, the rules would prevent many studies from being considered in EPA reviews.5 It might seem like an easy task to sort good science from bad, but in reality it’s not so simple. “There’s a misplaced idea that we can definitively distinguish the good from the not-good science, but it’s all a matter of degree,” said Brian Nosek, executive director of the Center for Open Science. “There is no perfect study.” Requiring regulators to wait until they have (nonexistent) perfect evidence is essentially “a way of saying, ‘We don’t want to use evidence for our decision-making,’” Nosek said. Most scientific controversies aren’t about science at all, and once the sides are drawn, more data is unlikely to bring opponents into agreement. Michael Carolan, who researches the sociology of technology and scientific knowledge at Colorado State University, wrote in a 2008 paper about why objective knowledge is not enough to resolve environmental controversies. “While these controversies may appear on the surface to rest on disputed questions of fact, beneath often reside differing positions of value; values that can give shape to differing understandings of what ‘the facts’ are.” What’s needed in these cases isn’t more or better science, but mechanisms to bring those hidden values to the forefront of the discussion so that they can be debated transparently. “As long as we continue down this unabashedly naive road about what science is, and what it is capable of doing, we will continue to fail to reach any sort of meaningful consensus on these matters,” Carolan writes. The dispute over tobacco was never about the science of cigarettes’ link to cancer. It was about whether companies have the right to sell dangerous products and, if so, what obligations they have to the consumers who purchased them. Similarly, the debate over climate change isn’t about whether our planet is heating, but about how much responsibility each country and person bears for stopping it. While researching her book “Merchants of Doubt,” science historian Naomi Oreskes found that some of the same people who were defending the tobacco industry as scientific experts were also receiving industry money to deny the role of human activity in global warming. What these issues had in common, she realized, was that they all involved the need for government action. “None of this is about the science. All of this is a political debate about the role of government,” she said in the documentary. These controversies are really about values, not scientific facts, and acknowledging that would allow us to have more truthful and productive debates. What would that look like in practice? Instead of cherry-picking evidence to support a particular view (and insisting that the science points to a desired action), the various sides could lay out the values they are using to assess the evidence. For instance, in Europe, many decisions are guided by the precautionary principle — a system that values caution in the face of uncertainty and says that when the risks are unclear, it should be up to industries to show that their products and processes are not harmful, rather than requiring the government to prove that they are harmful before they can be regulated. By contrast, U.S. agencies tend to wait for strong evidence of harm before issuing regulations. Both approaches have critics, but the difference between them comes down to priorities: Is it better to exercise caution at the risk of burdening companies and perhaps the economy, or is it more important to avoid potential economic downsides even if it means that sometimes a harmful product or industrial process goes unregulated? In other words, under what circumstances do we agree to act on a risk? How certain do we need to be that the risk is real, and how many people would need to be at risk, and how costly is it to reduce that risk? Those are moral questions, not scientific ones, and openly discussing and identifying these kinds of judgment calls would lead to a more honest debate. Science matters, and we need to do it as rigorously as possible. But science can’t tell us how risky is too risky to allow products like cigarettes or potentially harmful pesticides to be sold — those are value judgements that only humans can make.

Understanding the Features of Finance: A Guide for Newbies Finance is a broad field that involves managing money, including activities such as investing, borrowing, lending, budgeting, saving, and forecasting. As a beginner, understanding the basic features of finance is crucial. This guide will relate these features to blockchain technology, cryptocurrency, and decentralized finance (DeFi). 1. Basic Financial Concepts Investing: Putting money into assets like stocks, bonds, or real estate with the expectation of earning a return. In the blockchain world, this translates to investing in cryptocurrencies like Bitcoin, Ethereum, or various DeFi projects. Borrowing and Lending: Traditional finance involves banks and financial institutions providing loans. In the DeFi space, platforms like Aave and Compound allow users to borrow and lend cryptocurrencies without intermediaries. Budgeting: Planning how to allocate your income to cover expenses, save, and invest. Using blockchain technology, you can utilize smart contracts to automate budgeting and savings processes. 2. Blockchain Technology Blockchain is a decentralized ledger that records transactions across multiple computers. It is the technology behind cryptocurrencies and has several key features: Transparency: All transactions are recorded on a public ledger, making them visible to anyone. Security: Cryptographic techniques ensure that data on the blockchain is secure and tamper-proof. Decentralization: No single entity controls the blockchain, reducing the risk of centralized control and failure. 3. Cryptocurrencies Cryptocurrencies are digital or virtual currencies that use cryptography for security. They operate on blockchain technology and offer several advantages: Lower Transaction Costs: Sending money across borders is cheaper with cryptocurrencies compared to traditional banking methods. Accessibility: Anyone with an internet connection can access cryptocurrencies, promoting financial inclusion. Ownership and Control: Users have complete control over their funds without relying on banks. 4. Decentralized Finance (DeFi) DeFi is a movement that uses blockchain technology to recreate and improve traditional financial systems in a decentralized manner. Key features of DeFi include: Smart Contracts: Self-executing contracts with the terms directly written into code, enabling trustless and automated transactions. Liquidity Pools: Users can provide their assets to a pool and earn interest or rewards, promoting liquidity in the DeFi ecosystem. Yield Farming: A strategy where users move their assets between different DeFi platforms to maximize returns. 5. Applications in DeFi and Blockchain HaloFi Save: A platform that leverages blockchain technology to help people save money efficiently and securely. It encourages users to save larger amounts for longer durations, offering higher interest rates compared to traditional banks. Non-Custodial Savings: Users have full control over their funds, reducing the risk of losing their money to institutional failures or fraud. Access to DeFi: Integrating with DeFi platforms like Moola Market, HaloFi Save provides additional opportunities to earn interest on savings, promoting financial growth and stability. Practical Example: A Farmer's Journey Imagine a farmer in a remote village in Africa. Traditionally, this farmer might not have access to banking services, making it difficult to save money, get loans, or invest in better farming equipment. With platforms like HaloFi Save, the farmer can: Save money securely and earn interest. Access microloans through DeFi platforms integrated with Celo. Participate in educational programs to learn more about blockchain and DeFi. Conclusion Blockchain technology, through platforms like HaloFi Save and initiatives by Celo Africa DAO, has the potential to drive significant social change by promoting financial inclusion, transparency, and access to resources. By empowering individuals and communities with the tools and knowledge to participate in the digital economy, blockchain can help address global issues and foster sustainable development.

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