The Digital Divide

Education and the workplace have been revolutionized by information technology. The jobs of tomorrow will depend heavily on people's literacy with computers and the Internet. Forecasts are that by the year 2010, 25% of all of the new jobs created in the private and public sectors will be â€Å"technologically oriented† (American Association of University Women Educational Foundation Commission on Technology, Gender and Teacher Education, 2000). In both economic upturns and downturns, access to jobs will require training and competency in technology (McClelland, 2001).Yet, access to training in IT is not equitable and some people have greater access than others with the likelihood depending on the income, racial, and gender categories of which people are members. White Americans are more likely to have access to computers and the Internet than African Americans. Males have more access than females, and wealthier Americans have more access regardless of race and gender. The digi tal divide is a term that has been used to refer to the gap between those who have access to technology and those who do not; between those who have the expertise and training to utilize technology and those who do not.According to Chistopher Latimer in a report to the New York State Forum for Information Resources, social gaps in society cause the digital divide, but the digital divide, in turn, may intensify existing social gaps and create new ones. Because members of minority groups and people from lower socioeconomic groups have less access to technology, they are likely to be even further disadvantaged from attaining some of the higher positions in tomorrow's economy, widening the economic divisions that already exist. The trend is already occurring.According to a report of the National Science Foundation (Papadakis, 2000), 46. 6% of White families in the United States own a home computer, whereas only 23. 2% of African American families own one. Although computer purchase and use rose for both Whites and Blacks over the last several years, the gap between racial groups has widened. During the 4–year period of 1994–1998, Papadakis reported that computer ownership increased 18% nationally, but the gap between Blacks and Whites widened by an additional 7%. The gap seems to persist at the college level.For instance, the Office of Institutional Research at a community college in northern Virginia polled the commuter–oriented student population and, even among this group, computer ownership was higher among White students than it was among Black students. Socioeconomic status also plays a large role. Of Americans with incomes of under $15,000, 12. 7% have computers in their homes. The percentages climb steadily with income such that families who earn more than $75,000 annually have a 77. 7% likelihood of owning a computer.The racial variable is often confounded with income, because Blacks and Hispanics make up a larger proportion of the lo wer income groups than do Whites. Nonetheless, some racial differences continue to exist, even when income is statistically removed from the phenomenon. For example, the lowest likelihood of computer ownership is for Black households whose income is below $15,000 (7. 7%). For all families earning less than $35,000, the percentage of White households owning computers is three times greater than the percentage of Black families and four times greater than the percentage of Hispanic families.It is not only crucial that everyone has the access and knowledge to use computers and the Internet for the jobs for which they will compete upon finishing school, but it is also critical for school performance itself. Survey data from a large number of eighth–grade students in the United States. They specifically noted the relationship between children’s having access to a computer at home and their scores on standardized tests. They found that reading and math scores were related to home ownership of computers.Not surprisingly, they also found that White students were more advantaged than Black students; wealthier students were more advantaged than poorer students. More surprisingly, the data showed that, controlling for the number of households who had computers, wealthy students obtained more of an advantage from their computer ownership than did poorer students, and White students obtained more of an advantage than Black students. Policymakers have good reason to worry about the digital divide. Wealth and socioeconomic status have frequently made education and employment opportunities more accessible to some than to others.Unequal distribution of wealth, even in the public sector, has created schools that are unequal in facilities, staff, and, in the end, academic performance of its students. The unbalanced relationship between race and socioeconomic status bears prime responsibility for the lower academic performance of traditionally underrepresented minor ities. The cycle perpetuates itself as underrepresented minorities are in a disadvantaged position to compete for the higher paying technology jobs of today's and tomorrow's workplace. The same precipitating factors are more difficult to glean in the case of gender.Nonetheless, compared with men, women are underrepresented in their use and ownership of computers. Women take fewer technology classes in high school and college, are far less likely to graduate college with degrees in IT fields, are less likely to enroll in postgraduate technology fields, and are underrepresented in the higher end of technology jobs. A recent study by the American Association of University Women (AAUW, 2000), for example, highlights how the vast majority of girls and women are being left out of the technology revolution.The AAUW report shows that women and men are using computers as a â€Å"tool†Ã¢â‚¬â€œfor accessing the Internet, using e–mail, and using word processing programs–at equal rates. However, there is a striking disparity in the number of women and men who are participating in the technological revolution at a more sophisticated level, the level that will allow them to be equal and active participants in the computer revolution that is taking classrooms and workplaces across the world by storm. Much of the debate about the digital divide has centered on the question of who has access to computers and the Internet.A series of studies by the National Telecommunications and Information Administration (NTIA, 1995, 1999, 2000, 2002) revealed that those in low-income, low-education, minority-racial, and rural location groups have unequal access to the new technologies. The most recent NTIA (2002) report indicated that the gaps in access are narrowing. However, this chapter argues that a number of fundamental aspects of the digital divide persist, above and beyond access issues. It examines continuing gaps that underlie the digital divide from a case study of Austin, Texas.A highly wired city, Austin reveals the social and cultural barriers that remain in place when most conventional remedies, such as public access centers, Internet-connected schools and libraries, and computer training programs, become fairly widely available. So far this discussion of the digital divide has taken a structural point of view. Many analyses point to income as the key issue in access, which leads many to assume that when computers and Internet access become cheap enough for all income levels can afford them, and then lower income consumers will, as a matter of course, adopt and use them.However, both the national NTIA research and the recent Texas study showed that, particularly within lower income populations, ethnicity is still related to less frequent use of the Internet. Economic structures related to class are crucial in limiting access to media, but culture, as indicated by ethnic differences, remains important. Bourdieu (1980, 1984, 1993a) intro duced the concepts of habitus, field, and capital to elaborate the continuity, regularity, and regulated transformation of social action that solely structural explanations fail to account for, such as technology use by individuals and groups.He described habitus as a set of dispositions that create â€Å"durable† and â€Å"transposable† practices and perceptions over a long process of social inculcation. The similarity of dispositions and practices experienced by members of the same social class constitutes class habitus for Bourdieu (Johnson, 1993). Such shared orientations help explain why groups acquire and hold dispositions against the use of certain technologies like networked computers, even when those technologies become accessible and receive favorable publicity in the media.During the past decade, the Department of Commerce has conducted research on the extent of Internet access throughout the United States. Their initial studies warned of a growing digital d ivide, particularly when the data factored in demographic variables such as race and income. Inspired by studies such as these, local, state, and national organizations emerged to close the gap, to ensure that most (if not all) Americans enjoy access to the Internet in the same manner as they do basic services such as water and electricity.What progress has been made since those earlier warnings? To answer that question the Commerce Department's National Telecommunications and Information Administration (NTIA), conducted a survey of about 57,000 households in September 2001, releasing their findings in 2002. Their results inspired many observers to conclude that efforts to close the digital divide have largely succeeded but that important work remains. Internet access has become an essential component to public life for most Americans.Indeed, the Commerce Department found that in September 2001, 174 million Americans (two thirds of the population) were online. Moreover, during the t ime of their study, they found that roughly 2 million more Americans go online every month. Many of these new Internet users are children, the fastest growing group in the study. Already, three fourths of all teenagers use the Internet for study, socializing, and entertainment. Just think, a mere decade ago, Internet usage was a rarity, a research tool for scientists or a plaything for the wealthy.Now the Net has wired itself into the fabric of our lives through stand-alone computers, personal data assistants, mobile phones, mall kiosks, and a growing number of other means that allow virtually anyone to go online from virtually anywhere. The Internet and ICTs are at present accessible to only a very limited proportion of the world s population. The diffusion of the communication networks is not uniform between countries or even within societies.Indeed, it is estimated that not even half of the people on the planet have ever made a telephone call. This uneven access to the new media is believed to be giving rise to a digital divide between the information-rich and the information-poor. For some privileged groups life-chance opportunities may be significantly enhanced by access to the Internet through greater bandwidth and high-speed connectivity. For the majority of less well off, access may be non-existent or at best limited to slow telecommunications links.As the rate of development of ICTs becomes faster and the competitive advantage to the information-rich increases, it is possible that the digital divide will act to reinforce and even extend existing social and material inequalities between people. Community informatics (CI) is the application of information and communications technologies (ICTs) to enable community processes and the achievement of community objectives including overcoming digital divides both within and among communities. But CI also goes beyond discussions of the digital divide.It goes on to examine how and under what conditions ICT acce ss can be made usable and useful to the range of excluded populations and communities and particularly to support local economic development, social justice, and political empowerment using the Internet. Thus a framework is emerging for systematically approaching information systems from a community perspective that parallels MIS in the development of strategies and techniques for managing community use and application of information systems closely linking with the variety of community networking research and applications.This is based on the assumption that geographically based communities (also known as physical or geo-local communities) have characteristics, requirements, and opportunities that require different strategies for ICT intervention and development from the widely accepted implied models of individual or in-home computer/Internet access and use. Because of cost factors, much of the world is unlikely to have in-home Internet access in the near future.Thus CI represents an area of interest both to ICT practitioners and academic researchers and to all those with an interest in community-based information technologies addressing the connections between the academic theory and research, and the policy and pragmatic issues arising from community networks, community technology centers, telecenters, community communications centers, and telecottages currently in place globally. The types of communities we are concerned with are those suffering economic and social disadvantage relative to other groups and neighborhoods within the city, town, or region.These are the communities in which the level of earning potential and capacity for income generation is poor. Unemployment figures are high and educational attainment is low. Poverty and discrimination are visible. People's confidence in and aspirations for the future are low. Most of the people living in these communities find themselves on the wrong side of the digital divide for reasons not so much of ac cess (although this can certainly be a factor) but of social and economic exclusion.Within these communities too there are often large numbers of hard-to-reach groups. These are the people who are beyond the net of social inclusion initiatives and whom in terms of turning around and transforming neighborhoods and regions it is perhaps most crucial to reach. ICTs can be used as a tool for reconnecting individuals and groups. With appropriate interventions and support, the influence of ICTs on the local economy can be more positive than negative. Poor and disadvantaged communities do not have to be left behind in the digital economy.They can be information society â€Å"shapers† rather than â€Å"trailers† (Shearman 1999a). ICTs open the door to the future. Having a share in the future is not just a question of â€Å"catching up. † It means having access to the new opportunities at the same time as everybody else. It is about having the chance to be at the forefro nt, to shape the direction of local economic, social, and community development. This means going beyond the basics of Internet access and training provision. Providing access and resources is just the first step.Leaving it at that condemns these communities to a perpetual second-class existence—always lagging behind. With a bit of imagination and thought, community-based ICT projects can offer a way out of this. One way of working toward this is to promote the use of state-of-the-art technologies in community contexts. Community-based ICT projects are not normally perceived as being at the technical cutting edge of their field or pioneers in applications development. But local ICT projects can be both state-of-the-art and community based.Community enterprises like Artimedia in Huddersfield and Batley and Mediac in Sheffield develop projects that encourage people to experiment with state-of-the-art technologies. Many of the cultural projects they are engaged in require people to acquire sophisticated ICT skills such as image compression, converting sound into streamed media and output from digital format to video. It goes without saying that a medium that is increasingly adopted into society is approaching average parts of the population.However, in my view, digital divides are about relative differences between categories of people. In the 1980s and 1990s, most of these divides concerning possession of computers and Internet connections increased, as was convincingly demonstrated by the American and Dutch official statistics supplied earlier. One is free to predict that these divides will close rapidly, an argument to be dealt with later, but their existence in the present and recent past cannot be denied. The argument about cheaper hardware is correct, but only partly so. It neglects many facts like:(a) The new media add to the older mass media that do not disappear: One still needs a TV, radio, VCR, telephone, and perhaps a newspaper; low income hous eholds continually have to weigh every new purchase (with the newspaper beginning to lose); (b) Computers are outdated much faster than any of the medium and continually new peripheral equipment and software has to be purchased; and (c) â€Å"Free† Internet access or computer hardware is not really free, of course. There are nominal monthly fees, long-term service agreements, privacy selling, and low-quality service, for instance.However, the most important problem of this interpretation, and the next one, is their hardware orientation. Perhaps the most common social and political opinion is that the problem of the digital divide is solved as soon as every citizen or inhabitant has the ability to obtain a personal computer and an Internet connection. In contrast, my analysis suggests that the biggest problems of information and communication inequality just start with the general diffusion of computers and network connections.

Birth Control in Schools Essay

Schools are the one institution in our society regularly attended by most young people-nearly 95% of all youth aged 5 to 17 years are enrolled in elementary or secondary schools (National Center for Education Statistics, 1993). Large percentage of youth attend schools for years before they encounter sexual risk-taking behaviors and a majority is enrolled at the time they initiate intercourse. Just as youth in communities with high rates of poverty and social unawareness are more likely to become pregnant so youth in schools with high rates of poverty and social inadequacy are also more likely to become pregnant. In particular, when female teens attend schools with high percentages of dropout rates and with higher rates of school vandalism they are more likely to become pregnant. The lack of opportunity and greater disorganization in some minority communities in this country, teens in schools with higher percentages of minority students are also more likely to have higher pregnancy rates than teens in schools with lower percentages of minority(Manlove, 1998).. Students in these studies, it is often difficult to distinguish the impact of school character from the impact of the community characteristics in which they reside. Social scientists and educators have suggested a wide variety of explanations for how schools reduce sexual risk-taking behavior. Some of their explanations have observed research supporting them, while others are credible, but lack supporting research. For example, educators concerned with adolescent sexual behavior have suggested that: 1. Schools structure students’ time and limit the amount of time that students can be alone and engage in sex. 2. Schools increase interaction with and attachment to adults who discourage risk-taking behavior of any kind (e.g., substance use, sexual risk-taking, or accident-producing behavior). More generally, they create an environment which discourages risk-taking. 3. Schools affect selection of friends and larger peer groups that are important to them. Because peer norms about sex and contraception significantly influence teens’ behavior, this impact on schools may be substantial. However, just how schools affect selection of friends and peers is not clearly understood. 4. Schools can increase belief in the future and help youth plan for higher education and careers. Such planning may increase the motivation to avoid early childbearing. As noted above, multiple studies demonstrate that educational and career aspiration are related to use of contraception, pregnancy, and childbearing. 5. Schools can increase students’ self-esteem, sense of competence, and communication and refusal skills. These skills may help students avoid unprotected sex. Despite the growing strength of the abstinence movement across the country, large majorities of adults favor SEX and AIDS education that includes discussions of condoms and contraceptives. For example, a 1998 poll of American adults found that 87% thought birth control should be covered (Rose & Gallup, 41-53), a 1998 poll found that 90% of adults thought condoms should be covered (Haffner & Wagoner, 22-23)and another 1999 poll found that 82% of adults believed all aspects of sex education including birth control and safer sex should be taught . (Hoff, Greene, McIntosh, Rawlings, & D’Amico, 2000). Given both the need for effective educational programs and public support for such programs, schools have responded. According to a 1999 national survey of school teachers in grades 7 to 12, about 93% of their schools offered sexuality or HIV education (Darroch, Landry, & Singh, 204-211, 265). Of those schools teaching any topics in sexuality education, between 85% and 100% included instruction on consequences of teenage parenthood, STD, HIV/AIDS, abstinence, and ways to resist peer pressure to have sex. Between 75% and 85% of the schools provided instruction about puberty, dating, sexual abuse, and birth control methods. Teachers reported that the most important messages they wanted to convey were about abstinence and responsibility. During the same year, survey results from a second survey of teachers and students in grades 7 to 12 were completed (Hoff et al., 2000). Their results were similar to the study above. They revealed that at least 75% of the students and similar percentages of the teachers indicated the following topics were covered in their instruction: basics of reproduction, STD and HIV/AIDS, abstinence, dealing with pressures to have sex, and birth control. Despite the fact that most adolescents receive at least a minimum amount of sexuality or HIV education, it is widely believed by professionals in the field that most programs are short, are not comprehensive, fail to cover some important topics, and are less effective than they could be (Britton, deMauro, & Gambrell, 1-8; Darroch, Landry, & Singh, 2000; Gambrell & Haffner, 1993; Hoff, et al., 2000). For example, both surveys of teachers discussed above found that only half to two thirds of the teachers covered how to use condoms or how to get and use birth control. there is very little information about the extent to which sex- and HIV-education curriculum have been found to be effective and are implemented with fidelity in additional schools. However, considerable unreliable information indicates few schools implemented the lessons. There is a widely held belief that schools have established a foundation for programs, but that effective programs need to be implementing more broadly and with greater dedication throughout the country. I want to take you back to when I was a teenager and how I personally can relate to the same choices and decisions our teenagers is face with today, in my personal experience; My boyfriend and I had our sex talk we decide I should go to my mother and talk to her about some form of birth control, her response was no. there was no explanation, no reasoning, and no questions ask about why I want to go on it. It was simply no! The end result I have 21yrs old. I’m not saying that we made the best choice because I still had an option to use a condom and contraceptives. Today’s teenagers resources are plentiful, they can go to cook county hospital, they have Planned Parenthood and there local clinic in there neighborhood and now they have program that are being implemented in their high schools. Children, who do not have supported parents, can not talk to their parents. I want to bring in another aspect as to what can happen when you do not enforce communication about birth control, sex and consequences with your teenager, as you know I’m a grandmother I wouldn’t trade my granddaughter in for anything in the world. Not enforcing the use of contraceptive, I feel one of the reasons that I became a grandmother in my thirty. because I did not get as involved with my son as I should have after he inform me that he was sexually active. The high Schools offer them open lines of communication and provide a safe atmosphere in which allows them to express their thought as to why they are there in the first place. It’s possible it can lead to single parenthood and a high drop out rate. Pregnancy among teenagers is continuing to rise despite a 40 million Government campaign to reduce the problem, while sexually transmitted diseases are reaching epidemic levels. The Royal College of Nursing revealed that increasing numbers of teenagers are indulging in sex and even taking part in orgies called ‘daisy chaining’. The Department for Education and Skills has admitted that 66 out of 150 local education authorities have at least one ‘ school based health service’ in their area providing advice, access to or direct provision of contraception. You have statistics on birth control and personal experience wouldn’t you rather your teenager be knowledgeable than not? Biliography Britton, P. O., DeMauro, D., & Gambrell, A. E. HIV/AIDS education: SIECUS study on HIV/AIDS education for schools finds states make progress, but work remains. SIECUS Report, 21(1), 1-8 (1992) Chandy, J. M., Harris, L., Blum, R. W., & Resnick, M. D. Female adolescents of alcohol misusers: Sexual behaviors. Journal of Youth and Adolescence, 23, 695-709 (1994) Darroch, J. E., Landry, D. J., & Singh, S. Changing emphases in sexuality education in U.S. pubic secondary schools, 1988-1999. Family Planning Perspectives, 32, 204-211, 265 (2000) Gambrell, A. E., & Haffner, D. Unfinished business: A SIECUS assessment of state sexuality education programs. New York: SIECUS (1993) Haffner, D., & Wagoner, J. Vast majority of Americans support sexuality education. SIECUS Report, 27(6), 22-23 (1999) Hoff, T., Greene, L., McIntosh, M., Rawlings, N., & D’Amico, J. Sex education in America: A series of national surveys of students, parents, teachers, and Jones 8 principals. Menlo Park, CA: The Kaiser Family Foundation. (2000) Manlove, J. The influence of high school dropout and school disengagement on the risk of school-age pregnancy. Journal of Research on Adolescence, 8, 187-220 (1998) National Center for Education Statistics. Digest of Education Statistics, 1993. Washington, DC: US Department of Education, Office of Educational Research and Improvement. (1993) Rose, L. C., & Gallup, A. M. The 30th annual Phi Delta Kappa/Gallup Poll of the public’s attitudes toward the public schools. Phi Delta Kappan, Sept., 41-53 (1998, September) Singh S. Adolescent pregnancy in the United States: An interstate analysis. Family Planning Perspectives, 18, 210-220 (1986)

Globalization and Technology Essay

Friedman explains how 10 ingredients, he calls â€Å"flatteners† which has inadvertently brought about a new global business environment. The 1st flattener is the â€Å"Fall of the Berlin Wall†, where Friedman explains how on 11/09/89 the Berlin Wall came down and exposed the continents into one globalize trading world. Friedman explains about six months after the â€Å"Berlin Wall Falling† the â€Å"Windows Operating System† computer chip exploded and launched the beginning era of internet PC revolution. He calls this era â€Å"The Fall of The Walls and the Rise of The Windows†. Explaining how the â€Å"Wall† stood in the way of globalization. Six months after the Wall Fell the Windows Operating System 3.0 shifted and created a single graphical interface. The 2nd flattener was the date 08/09/95 having an immense impact which I believe is a milestone in the history of our technology growth and its repercussions was when Netscape, a internet b rowser (which is a drop box that is illustrated on computer screens giving a outburst of availability to the internet’s world wide web of information and created an open highway with no speed limits), went public. As Netscape became available to all people at their finger tips it played a key roll empowering individuals with massive amounts of information and helped commercialize and set open standards, equally facilitating all of the world’s people with virtually the same chance of opportunities for growth. This phenomenon is greatly indicative to the remaining of Thomas Friedman’s flatteners and their implications, good and bad, on human kind essentially defining what he meant with the statement: â€Å"The World Is Flat†. The Netscape browser brought the internet to life and gave us the .com boom creating a bubble of wild crazy investments which facilitated the fiber optic boom. Friedman explains how an overinvestment of 1 trillion dollars in five years into fiber optic cable inadvertently connected the world through the internet. Which lead us to the â€Å"Workflow Software†, the 3rd flattener where all the software programs and standards that connect PCs with ba nds of cable to allow work to flow, such as Microsoft Word. These events fountain a technology revolution, which virtually connected everyone’s application to everyone else’s application. Creating a new global platform where Friedman describes this era as a collaboration of platforms, flattening the world. This platform marks the end of a new beginning as Freidman describes â€Å"The Genesis Moment†. Freidman explains how this Genesis moment fueled a network connecting  Ã¢â‚¬Å"people to people†, â€Å"companies with companies†, â€Å"people with companies† and â€Å"more people with more different places† and so. Thus, starts the emergence of Freidman’s theory â€Å"The World Is Flat†. This new platform is based on a collaboration of the following six flatteners. Starting with the 4th flattener in which Friedman labels as â€Å"Outsourcing† was built around the â€Å"Y2K† fade. Outsourcing was the product of collaboration which allows departments of large companies to work out of State, and more so, to work out of our country. This collaboration aided companies to disaggregate a good proportion of their business processes and source it out to anywhere around the world at a lesser cost than it would have otherwise cost here in the US. Outsourcing gave way for companies to take advantage of high skilled laborers with low-cost wages, utilizing them as vehicles for companies to gain profits and develop an exponential boost of effective efficiency by tremendously improving their overall production and operations increasing profit margins. Although, many American companies probably did not stop to analyze the repercussions of their gains. The 5th flattener is â€Å"Off Shoring†, which is built around China joining the World Trade Organization. Off-shoring is taking an entire factory and physically moving it from the U.S. to a foreign country and integrating into global production operations. The 6th flattener is â€Å"Open-Sourcing† where the writing of â€Å"Linux† was created. Linux is a computer operating system program and is the biggest competitor’s to Microsoft’s operating system program. This new operating system â€Å"Linux† was created by a collaboration of computer sc ientists on the internet who demanded no money for their efforts allowing this free program to be downloaded by anyone who seeks it out. Linux is the biggest competitor to Microsoft whereby under cutting Microsoft, Friedman emphasis, how it would be hard to bet â€Å"zero†. â€Å"Supply Chain† is the 7th flattener which is built around Wal-Mart, as Freidman stated, represents the construction of a hyper-efficient, down to the last atom of efficiency global supply chain of operations. Wal-Mart successfully capitalized on MIT (management information technology). An example is where as you take an item off a Wal-Mart shelf in one city, that item will immediately be in production in China. Surprisingly, Wal-Mart doesn’t manufacture anything, but has successfully held itself as the biggest American retail company by innovation of a global supply chain to the last atom of efficiency. â€Å"In-Sourcing† is the 8th  flattener. UPS, an express package delivery service company capitalized on in-sourcing by taking over internal logistics of companies such as Toshiba. This way of business is not an e asy situation but can successfully be done by normal standardization company set-up where UPS will repair a broken item of Toshiba products. UPS virtually creates and operates a replication of Toshiba’s repair center. Toshiba agrees to pay UPS to operate this repair services for their customers in which UPS delivers the repaired product back to the original customer where Toshiba never touch their own products. The 9th flattener is where Friedman describes as â€Å"Informing† examples are Google, Yahoo, and Microsoft search engines. These informing tools allow you to collaborate yourself with unlimited amounts of data, information and resources. Informing is a way where we as individuals can collaborate ourselves with information. The 10th flattener is what Friedman calls â€Å"Steroids†. This is wireless technology, voice over the IP, and advances in computer microchips and storage capacity. He explains how Steroids basically turbo charge all nine of these new forms of collaboration and make it so you can now use anyone of these advances from anywhere through any device. These ten flatteners complement each other and converged into a single global web enabled platform. Without plan these events of convergence overlapped and complemented each other, working together with multiple forms, melting any world’s gaps and virtually bringing all people together closer than ever before. Friedman summarizes the flatteners by explaining how â€Å"three convergence of technology† makeup the 10 flatteners are as followed: †¢ 1st Convergence: Globalization 1.0: where the world changed from â€Å"Large? to Medium† and the agent of this global change were through countries. Globalization 2.0: where the world changed from â€Å"Medium? to Small† and the agent of this global change were through companies, markets and laborers. Globalization 3.0: where the world changed from â€Å"Small? to Tiny† and the agent of this global change were not countries or companies but individuals and small groups. Where individuals world wide, now have access and the ability to facilitate, embrace, and empower themselves individuality with any advancements they may desire. This global change has flattened the economic playing field geographically through time, distance and language providing the opportunities of capitalism and its byproduct is competition world wide for all people of the world. Essentially, this defines Thomas  Friedman’s meaning of â€Å"The World Is Flat†. †¢ 2nd Convergence: The need for adaptation of our new flat world habits where resources, rather it be natural or synthetic, are more evenly distributed among all living people of the world therefore resulting in a negative amount of resources allocated for each American’s average income level. Friedman tells a detailed personal story when he experienced the flatten world describing how he once lacked new information and therefore failed to take advantage of attaining his airplane flight boardin g pass the night before starting at 12:01am. Other passengers took advantage and utilized their resource tool of new technology where customer service provided by Southwest Airline’s internet we2 site. Even thought other passengers on the same airline flight as Thomas Friedman was able to receive their airline-boarding pass the night before the flight. Allowing the other passengers more free time before having to arrive at the airport and not having to stand in a waiting line. According the Friedman’s writing, we as Americans would have to learn to view the world from a different perspective, understanding and accepting competition will increase and we may get less for our dollar in the near future. Friedman called this process where people will have to horizontalize themselves. He explains when the world goes flat the value increasing is not created vertically, in single sections or companies, but is increasingly created horizontally by who is collaborated with what companies, inside and outside your company and/or companies you buy from as consumers. People having to horizontalize them selves and to think very different about how we collaborate within firms and with other firms in order to reach new value creation. An example is when computers became available to the average consumer and businesses, people had to adapt to a very different workplace and work habits in order to collaborate with the new technology. †¢ 3rd Convergence: Freidman states the last convergence is since all of this globalize collaboration been accruing there was a massive quite perfect storm was being created â€Å"3-billion† people who were out of the game walked onto the playing field of trade and consumerism from China, India and the former Soviet Union. Freidman recognizes that approximately only 5% of those three billion people can plug in and play after calculating the numbers it turns outs to 150 million people, which equal the size of the American workforce today. Freidman’s main argument of his book is the triple convergence of the ten  flatteners that are flattening the world, the convergence of a whole new way of doing business is much more horizontal rather vertical including three billio n new players. In general, Thomas Friedman finalized his argument by emphasizing â€Å"the world is flat and I’m here to tell you that everything we called IT revolution these last 20 years, was just the warm-up act that has been the sharpening and the distribution of the tools of collaboration. Now you are going to see several billion people increasing quickly learn how to use and apply those tools across a whole new range and forms of collaboration†. I agree with much of Friedman’s theories and the flatteners he chose to describe the extreme important impacts that affect our IT revolution world to at which the state it is in today. Freidman chose these events as milestone, where I would add emphasis on the importance of the sequential pattern of the flatteners’ events in which they transpired. Much through pure chance the sequence of events our technology growth and it processes just fell into action, rather for better or for worst, it was bound to happen. And if you ask most Americans if they think we should have not had the opportunity in attaining these advance technology leaps, I would prognosticate that most people would not forgo these gains for anything less regardless of the repercussions. I believe the most important flattener is 08/09/95 when Netscape went public because it opened an express highway of doors of opportunities with no speed limits, in my opinion, having one of the greatest technological improved impacts on human kind by immediately and direct changing our standard ways of living and increasingly potential capabilities. When Netscape became public it gave us a huge stepping-stone of advancement connecting the people of the entire world to each other. This change gave way for all of the other leaps of events to unfold without such a change Friedman’s other collaboration could not have taken place in the matter in which it did. This technology metamorphosis has allowed people to work from their homes, communicate to family members that are out of the country, and educate themselves with tons of information. I agree with Friedman in that â€Å"learning to love learning† are important elements missing from our culture’s view of education today. People must know that learning is never ending. There is always some skill or fact that is unknown that can be learned, but only if that person has a desire to learn. Even though children have the greatest opportunity to gain knowledge,  many children do not take advantage of it. They should realize that learning is constant and that educat ion is very powerful. Although I do not agree with Friedman in that â€Å"learning to love learning† is â€Å"most† important elements our society is missing from our culture’s view of education. I believe first and foremost public schools from 1st grade all the way to BA degree with in a university should be facilitated and paid for all American children with governmental taxes. National health care and wage insurance can help people survive while they are unemployed. Basically, we Americans should go back to the basics in that our society should enforce (good old fashion morals) basic conduct that reflects morals and respect utilizing integrity anything we do. The opposite is true in which we allow the media and forms of other public exposure to report stories with exaggerated facts and/or information that adversely affects our children’s view of themselves and everything around them. Should we go back to basic traditional teaching where in the beginning of child’s education building a strong foundation in our children’s life incorporating strong work ethics including a strong sense of pride in the all work and accomplishments attain. I believe if these foundations are bestowed within our children’s lives, the results will give them empowerment, enabling and encouraging our children in the right direction so that, when needed they can educate, empower, enable, and encourage themselves in becoming the most efficient individual collaboration. Understanding this way of life and incorporating these values within our daily lives utilization of fewer resources. Americans must acknowledge that we may have to learn to live with fewer luxuries and learn to be more conservative with natural resources but not necessary having to accept a weaker economy for the sake of it. There is a limited amount of natural resources available at any given time on earth and after these natural resources are evenly divided out per individual, the amount per individual is very small in size. Therefore, I do believe Americans should start adapting to new ways of living and consume fewer resources per individual. Many people may agree with my belief that Thomas Friedman failed to emphasis, what I call â€Å"individual re-shapers† where Americans should re-evaluate (re-shaping) their morals, integrity, honor and trust and try to incorporate these ideas within the intra-structure of American families, public schools, public facilities,  communities, cities, states, agencies, government, services, products and companies of the United States. If Americans would utilizes the same amount of time and investments, monetary and non-monetary, within our society moral values as whole and start new policies that will complement our global changes. These changes can initiate with my extremely important idea of â€Å"individual re-shapers† by developing and morally growing in a positive direction for the better good of all people around the world as a whole. Some â€Å"individual re-shapers† are technological advancements within public schools, which is essential for success and may have exponentially increasing our standard of living and helped improved most Americans everyday life by starting with our children. Another â€Å"individual re-shapers† is restricting the media to mislead or avoid the real truth of WORLD NEWS and not allow political groups or public positions and agencies to utilize law suites and avoid addressing real society moral problems of the American people. This can facilitate our country to be effective in a continuous society that morally develops at a rate parallel to the repercussions of technologies developments. The most important knowledge I have acquired from Thomas Friedman’s book â€Å"The World Is Flat† is the confirmation of my own personal beliefs as well as my personal career plans and professional development that incorporates and utilizes my code of honor and integrity in whatever I do in my life, rather it be a branch manager overseeing many employees, and/or a wife and mother (in which I believe is one of the hardest but important jobs a person can hold) raising children that reflecting the same, if not better, code of conduct in the ir life.

An Analysis of Punch-Drunk Love Film by Paul Thomas Anderson Essay

An Analysis of Punch-Drunk Love Film by Paul Thomas Anderson - Essay Example The film tackles a number of issues on the personal life of the main character but presents it in a way that is obscuring and lagging that takes away from the focus of what the story is trying to convey in essence. It hints on family issues and the environment of growing up as the only boy in a family with 7 other sisters but it does not really tackle it full on. The topic remains hanging in the air and there never was any resolution to the end. Growing up with such a number of sisters does not in itself make any person less of a man nor would it necessarily mean that one is bound to have psychological issues. To present the audience with the background that this alone serves as full explanation without having to give further details to support it would be nothing less than a shoddy argument. It leaves one feeling shorthanded instead of having the actual realization that such is so because this happened or that was the fact presupposing on other events. The film starts off with the i ntroduction to Barry’s life laden with family woes in the form of seven overbearing sisters who each has a strong personality that overpowers that of Barry’s own insecurities. ... Then there was another sister who tries to be more involved in his life and even going so far as to fix him up with her co-worker. The idea immediately put Barry on the spot but in the scene where they are in a tug-and-pull whether it was going to be a good idea or not there was no concrete sense on whether Barry was really adamant to meeting somebody or he was just trying to play it coy to avoid embarrassment. Perhaps it was more of both just to avoid having to be ridiculed by her sisters. The most effective in conveying the relationship between the siblings was when all of Barry’s sisters kept on pushing him about the time the called him ‘gay boy’ and he got so mad that he threw a hammer to the windows. Here the definite illustration of the character’s anger management issues shown through as he smashed the windows of the house nonchalantly then reacting by crying to Walter asking him to refer him to s shrink. To be more accurate, the story tries to incul cate that his family structure is perhaps the most distinctive part of Barry’s life that contributes to his repressed emotional issues. But further than the birthday scene there was really nothing else that points out to the theme other than his constant reminder for no one to tell his sisters he will be going to Hawaii. Two minutes into the film one is already bored with the longshot of the camera into the streets and the ominous woman leaving her car without so much as indicating what needs to be fixed. There was of course the small piano that Barry literally had to sneak and grab from the streets although the whole exercise seemed to be pointless as there was nobody else in there. This object which turned out to be a harmonium as pointed out by Lena tried but failed to

Poverty in Africa the oil-rich Country Essay Example | Topics and Well Written Essays - 1000 words

Poverty in Africa the oil-rich Country - Essay Example Major oil producer countries in Africa are Nigeria, Angola, Sudan, equatorial, Guinea and republic of Congo. Major oil producer countries in Africa are Nigeria, Angola, Sudan, Equatorial Guinea and republic of Congo, Gabon, Cameroon, Chad. But the oil is not always a boon. It increases corruption and is responsible for grievance, relative poverty and instability. Studies have shown that countries with oil wealth in Africa grow more slowly, less equitably, more corruptly and more violently. Angola has huge oil reserves but the civil war in Africa made it hard to reach till 2002. Angola is second large producer of oil in the sub- Sahara region. But in Angola, the corrupt government officials and the well connected business man grow immensely rich using oil resources. The ruling dynasty uses oil wealth to consolidate its own position. The common man grows poorer. It is estimated that the government collected more than $10 billion in oil revenues in 2005 and this amount expected to go hi gher as the production peaks. But the riches are not evenly spread. More than 70% Angolans are still under poverty line. Nigeria is the largest oil producer in Africa and has huge oil serves but it has also set records for corruption. Nigerian government’s anticorruption wing, the economic and financial crimes commission calculates that between 1960 and 1999, the countries rulers stole $400 billion in oil reserves. In the last 47 years, Nigeria lost one million people due to civil war as they mostly fought to control oil-rich areas. It has also seen 30 years of military rules with six coups in 47 years. More than 67 percent of populations live under poverty line. Gabon was once a huge producer of oil and its oil reserves are drying up. The country still ranks 124th on human development index. Sudan has some reserves of $63 million barrels of oils but is one of the poorest countries in the world. Majority of African nations are undeveloped

Use of Digital Media within Organisations Case Study

Use of Digital Media within Organisations - Case Study Example In the recent years, facing stiff competition in industries and the high need to cut costs while still maintaining efficiency in businesses has seen the rapid growth and development of digital solutions for businesses. A key area in which digital media has greatly been used by the various businesses is communication. Communication is a critical success factor in the business world and hence the development and improvement of digital media such as web videos, availability of e-books and social media have been key turnaround factors for business organisations. In the above mentioned case study involving virgin media, it is demonstrated beyond reasonable doubt that the use of digital media has a positive rather than negative impact on the performance of an organisation depending on the overall objective for the incorporation of digital media was. Here, the objectives of the study were to raise awareness of Virgin Media HD football packages through online mobile marketing and this was sp ecifically targeting the users of iPhones. The brand basically wanted to use a new, innovative and creative mobile marketing form in a bid to get the attention of football fans browsing the Guardian mobile internet website. Virgin media was working I partnership with an advertising agency, 4th street advertising. The main objective that was to be achieved was to get the information on virgin media HD football channels to a specific target audience which was football fans who owned iPhones. This was done through the execution of a well laid out strategy that involved exposing the target audience to the advertising message and a clear action that encouraged the recipients to learn more about the products and services offered by virgin media. Additionally, the advertisement campaign provided value addition with a calendar sync option that enabled the users with a fixture list of all games to be televised of the English Premier League. The intended purpose was to improve customer loyalt y and give then pride in being virgin customers. The banner bearing the campaign on the website was easy to use and access and it provided users with two calls-to-action. â€Å"Find out more about Virgin Media Football Packages† and â€Å"Sync televised games with calendar†. The call to action that allowed the audience to find out more about various other packages offered allowed the organisation to put across all or other products that the potential clients may not have been well aware of. The results obtained from the implementation of digital media in communicating to the target audience produced splendid results for Virgin Media. The creative execution drove high interactivity with the brand from the target audience. During the quarter to December after the launch of the digitized media in August, Virgin added over 100,000 Sky premium subscribers to reach a total of 725,000. As depicted clearly, clear and simple messages via digital media are a really positive way to communicate to potential customers. I chose to break down the in depth analysis of the effect of digital communication in this above briefly introduced scenario within in topics that depict every step of the process. Goal of Organisation The goal of Virgin media, according to the scenario, was to raise awareness of Virgin Media HD football packages that were in store for avid football fans via mobile advertising and targeting specifically iPhone users. The brand aimed to employ innovative

Book Publishing Industry Assignment Example | Topics and Well Written Essays - 750 words

Book Publishing Industry - Assignment Example Their role is especially threatened with the availability of self-publishing options for the authors, an aspect that puts them out of the picture, with an added value of cheaper services for the authors (Bradley & Bartlett, 2012). Nevertheless, those publishers who will be willing to embrace the online trend and establish online services for the publishing of works, they are likely to survive. Such a trend is already evident with various publishers embracing online platforms through which they provide online versions of their publications to meet the online demand. The agents’ position and role are also threatened with the changes towards increased online services as the author have a choice of being in direct contact with the online platforms (Bradley & Bartlett, 2012). For them, they are likely to be intermediate, this time advocating the traditional publishing as it is only through this type of publishing that they role holds significance. An increase in the online demand f or reading material has a definitive impact on the print media. This means that with the increase in information technology, the printers are bound to be disintermediated from the book publishing industry as their role will be consumed by online publishing and accessibility of the books. On the other hand, the distributors are likely to be cyber-mediated through the development of online distribution platforms in the form of e-Libraries that would enhance the accessibility of eBooks (Bradley & Bartlett, 2012).

What do Northcentral's Mission Statement, Vision, and Values Statement Personal

What do Northcentral's Mission , Vision, and Values mean to me personally as a Learner - Personal Statement Example This can lead to several challenges in ensuring that students not only understand their lessons but are also integrated into the university's culture. I think Northcentral University is doing a very good job of ensuring this and as such is one of the best online universities out there. Northcentral university's mission statement and vision clearly spell out how their approach to online learning is unique and distinctive. The university's and its faculty's passion and commitment to educating individual students are clearly spelt out in the university's value statement. This distinctive approach to learning and the commitment of the faculty is passed onto the students and inspires them to conduct themselves with integrity and give their best performance through innovation and teamwork. In my opinion, Northcentral University's mission statement, vision and values statement help define how I as a learner shall conduct myself and learn from the dedicated faculty members. Northcentral Univ ersity's mission is to provide "quality educational opportunities" to people around the world. The commitment to providing education to not just a community but to interested individuals all over the world makes the university unique. Traditional universities, by the virtue of their location, can only provide education to the individuals living in the community. Because these traditional universities have a commitment to their communities, when they do enroll outsiders, they often charge them higher tuition rates. The campus-based model also means that students need to be at the campus at particular times, which can make it difficult for many students to pursue an education while also being gainfully employed. Northcentral University's online model takes care of these typical problems of a traditional university. It removes boundaries from education and makes it easily available at the same affordable rate to people around the world, thus removing the location based discrimination s een in local universities. The online model also allows busy professionals to get education without giving up their day jobs. Thus, the university's mission ensures that education can become truly universal by making it available to anyone who seeks it. A big problem often faced by online students is that the quality of education is often much lower than what is available through the traditional classroom model. One reason for this is that professors often think of their online classes as an additional job and are not dedicated to it in the same way as they are to their traditional classes. Since teachers can see their students in person in a traditional classroom, they feel more of a connection to them. In an online environment, this connection between the teachers and students is often missing. The "distinctive faculty mentored approach" of Northcentral University ensures that the university's students do not feel neglected by their teachers. Being a fully online university, teach ers do not see their online students as an additional job. The faculty's passion and investment into the student's education ensures that Northcentral University does not suffer from the problems faced by other online programs. Northcentral University values the needs of individual students promotes a passion for education in its faculty and administration. The focus on the needs of each individual student is important because in large class sizes, individual students often get lost. On the one hand, the brighter students stand out and often become teacher's favorite while on the other hand students at the bottom of the class are ignored. As a result, the good students excel and get much more attention from the teachers while the average students are left to fend for

Aircraft emergency response Essay Example | Topics and Well Written Essays - 2500 words

Aircraft emergency response - Essay Example The planning processes should be interlinked to ensure that the company is able to take appropriate initial actions, and then continue managing the emergency crisis for an unspecified duration. Ultimately, the aim of comprehensive emergency response and crisis management planning is to minimize pain and suffering of all associated in the event of an accident in the airport premises or its immediate vicinity and to save human lives All airports authorities should have aircraft rescue and fire-fighting services and equipment, for procedures for handling aircraft fire emergencies, and for specialized vehicles used to perform these functions at airports, with particular emphasis on saving lives and reducing injuries coincident with aircraft fires following impact or aircraft ground fires. Everything that can be done to protect the health and life of the individual must have priority over maintaining aircraft equipment and facilities, however valuable these may be. Human life comes first; efforts to salvage aircraft, buildings or technical equipment are secondary. "If you are looking for perfect safety, you will do well to sit on a fence and watch the birds; but if you really wish to learn, you must mount a machine and become acquainted with its tricks by actual trial." Emergency response is a product of preparedness. ... Especially the first responders: fire, police, emergency medical service, and building safety professionals. Major accidents are being studied by many emergency response agencies to achieve workable response procedures using a specific set of guidelines applicable to each type of occurrence. As in nearly all countries, the guidelines and recommendations set out in Annex 14 of the International Civil Aviation Organization (ICAO) applies to fire fighting and rescue services. Planning for the crisis is the key to minimizing the harmful effects of aircraft accident. Every airport is categorized for rescue and fire safety purposes in accordance with International Civil Aviation Organization (ICAO) guidelines, depending on the maximum total length and fuselage width of the aircraft normally used at the airport. Some of the regulatory requirements for international airport authorities and covered by the existing regulations include (Shantakumar 29): 1. The minimum number of vehicles and quantities of extinguishing agents, emergency equipment and the qualifications and training of personnel that must be made available by the airport operator; Aircraft emergency response 4 2. A three-minute response time for first-response vehicle(s) responding to an emergency at applicable airports; 3. A minimum of 90 per cent coverage of commercial aircraft conducting regular flights, and in addition, coverage of 100 per cent of all 20-passenger aircraft. 4. The presence of qualified personnel, trained who are able to deliver aircraft rescue and firefighting service at the airport during operating hours; 5. The annual testing of emergency services conducted, monitored and enforced to evaluate response times and confirm that the emergency services being

Response to Article Questions Example | Topics and Well Written Essays - 500 words

Response to Questions - Article Example Cocoa is also lower the rate of weight gain when added to food with elevated fat levels. The ability to lower weight gain worked perfectly in research involving overweight mice (Esposito 2012). The weak points of this argument are its inability of the research to identify the exact period and location within which the research was done. It does not specify the gender of those involved in the research whereas we clearly know gender and age are important factors that may affect credibility of results. The article also fails to give the quantity of flavonoids in the cocoa used in the different tests. The article is biased in the one-dimensional approach it has given about black cocoa. It focuses only on the benefits black cocoa or black chocolate has but does not warn the readers of possible side effects, which might result for those who may choose to overindulge with the hope of speedy results. The article is so general on the dosage required and does not even specify the ages, which the given dosage is applicable. The strong point of the reported information is the simplicity with which it has addressed the issues involved. The language used is simple enough to be understoo d by many. The argument also provides evidence from already published journals, which one can use to ascertain the issues discussed. The article clearly interprets results obtained from mice animals that have been used for long to carry out tests and provide results closer to those in human subjects. The reported information is not detailed enough and it fails to address a number of very critical issues, which leaves the leader in doubt on the accuracy of the information. The reported information fails fully explain, if there has been any success in identifying the exact flavanoid in the cocoa beans that offers remedy for each of the condition. If they have been identified the paper should explain if any successful attempts to extract such flavonoids have been made. Other information

Analysis Report Assignment Example | Topics and Well Written Essays - 500 words

Analysis Report - Assignment Example Both the staffs and students of any institution seem to neglect the importance of internet in their lives and studies and official works are carried out by the means of paper work. However after the invention of internet, many schools/colleges have switched to an automated environment, still it’s necessary on the parts of the students to know why internet seems to be so vital. Thus the students will be assigned with the task of data gathering by the application of internet and this could be done by involving them in a group project where the objective would be to gather data about the usage of internet in various regions within their locality. Each group would be assigned with one region of their choice where they would have to present data on the following- The objective of the task is to make the students realize the capabilities of internet and implement the same in their further academic projects. The instructional issues would also get resolved once they get familiarized with the internet and its utilities. The task would be conducted in an environment comprising both the classroom activities and the field job. The field job would include visiting the households or the corporate houses for deriving more reliable data and then properly tabulate the data so that it becomes easier for the evaluator to understand the study. They can also collect the data via some sites that offer trends and statistics related to internet usage (Internet World Stats, 2013). The class activity would include analyzing the data collected through various statistical tools and representing those in a simple manner. Internet is regarded by most of people belonging to the younger generation, as a channel for entertainment. However, Internet also serve various purpose like it can offer an individual a chance to explore what is going on in the entire world just staying at the comfort of their home.

Violence in the Media and how it Affects Society Essay Example for Free

Violence in the Media and how it Affects Society Essay The effect of media is profound and far-reaching. All over the world, the media influences our values and intrudes upon our deep-seated ideologies and beliefs. Indeed the media has been a powerful force in influencing people’s perceptions, and more importantly, their behavior as well. Business, politicians, and showbiz personalities pay huge sums of money to media firms in order create an image or change an existing one. Politics in particular, has been making use of the media to generate public support for their campaigns and support for certain policies and legislations. Indeed, the power of the media to affect our behavior has long been proven. Among the most pressing issues about media nowadays is how the proliferation of media violence can affect society. People have long believed that constant and chronic exposure to violence through various forms of mass media can erode the values of an individual, especially if the person does not have a strong system of moral support. (Croteau Hoynes 23) However while it is easy to say that violence in media has an adverse effect in society, there are scholars who argue that it is not media per se that causes the negative effects, rather it is a complex interplay of many elements in society, and media is but one element in the issue. (Freedman 54) Media violence and its effect on society cannot be separated from these other factors and therefore, media alone cannot be held responsible for violence in society. As such, this paper intends to understand media violence and its effects on society by understanding the issues that underlie the argument. Violent behavior has long been a source of confusion among sociologists, psychologists and society in general. While there have been many extensive researches that have attempted to study, understand, and explain criminal acts, none thus far has been found to satisfactorily explain all the complex processes and the interplay of factors that pushes an individual to commit violence. Among these theories, the most widely-accepted is the constitutive criminology. According to this theory, violent behavior is the result of the complex interplay between man and the social structures that he interacts with on a regular basis. (Sanders Ferrell 146) As such, perpetrators of violence cannot be analyzed separately from the social processes that they interact with. Following this theory, it is easy to understand why media has often been implicated in the increase of aggressive or violent behavior. Media has been growing more powerful and omniscient by the minute. In particular the Internet, has amplified the power of the media to effect change and influence society’s behavior. The effects of these technological advances have been discussed by Croteau and Hoynes, â€Å"The increase in media options in recent years has even led to an increase in ‘multi-tasking’- using more than one form of media at a time. † (5) With the ubiquitous media surrounding us in all aspects of our lives, it is easy to realize that the media is a big and indispensable part of contemporary life. Indeed the media has become the most dominant and powerful force in our modern world, displacing religious and educational institutions as the primary molder of our individual and collective ideologies. (Croteau and Hoynes 6) And if media can be used to influence buying, voting, and other forms of behavior, it follows that is also affects violence and aggressiveness among people. How media influences people may be explained by Bandura’s social learning theory. According to Bandura (1977), the need to be accepted and conform to society is the main driving force for an individual’s actions. If media then creates the image of what is acceptable and popular, then it is only logical that society acts in accordance to this media-created image. The following figures are taken from the official website of the National Institute on Media and the Family (2006): ? Based on average viewing time, an individual would have seen some 200,000 acts of violence including 40,000 murders on television by the time he or she is eighteen years old (Huston, et al qtd. from the National Institute on Media and the Family). ? Children between the ages of 8 and 18 spend more time exposed to various forms of media (TV, computer, game consoles, music, etc) than any other activity in their lifetime. (Kaiser Family Foundation qtd. from the National Institute on Media and the Family). ? Of over a thousand studies that have been done on the effects of violence in television and movies, majority of them conclude that individuals, especially children who spend significant time watching violence on TV and movies are more likely to display aggressive or violent behavior, attitudes and values. (Senate Committee; Congressional Public Health Summit qtd. from the National Institute on Media and the Family) According to these figures, the younger the age of the individual, the more susceptible they become to the adverse effects of exposure to media violence. (Trend 93) The aggressiveness are often latent and presents later in life which is adds to the difficulty of measuring the actual effects of media violence. (Freedman 137) Women who spend long hours watching TV violence are more likely to respond violently towards their spouses. There is an increase in physicality among women with higher media violence exposure. (Partenheimer) In the same vein, men who watched more media violence exhibit increased physical violence and aggressive behavior towards others as well. Both men and women who watch violence on the Internet, movies, and TV are three times more likely to commit traffic violations and other misdemeanors and felonies. Regardless of any theory, there is no denying the fact that any violent actions or aggressive behavior is a product of a highly complex process, the mechanics of which may forever elude social scientists. However, while violence may indeed be just the end product of a series of interactions between the perpetrator and the world around him, the question still remains why some people who grow up watching the same levels of media violence grow up to be normal people while others become social deviants. As the individual makes the choice to commit an aggression, how much of this is because of media influence and other social and physical factors, and how much of this is purely the individual’s choice? For social scientists the challenge is to create theories that will help prevent violence rather than analyze the aggressive after the fact, after the harm has been done. As previously mentioned, learning does not take place in a vacuum; it does so within a social context. Young children are very impressionable, and they need constant supervision and explicit direction from their parents. Children should be made to realize what behaviors are acceptable and those that are not. Parents should exhaust all efforts to monitor what their children see and hear and provide proper and consistent guidance Indeed the media is very powerful and highly influential. But it is a neutral instrument and can be used for both good and bad. By virtue of its platform of delivery, films and television are highly accessible and are able to reach an enormous audience within a short span of time. The elements of compelling narrative, appealing characters, vivid imagery, and technological achievements, make a powerful combination that is able to stir deep emotions and leave lasting impressions in the psyche of the individuals who are watching. Shows and music that carry positive themes of justice, equality, and honor are very effective in shaping public opinion, and by extension, positive behavior as well. A well-made film or TV show can galvanize a society into action and initiate positive change. Media should temper violence by featuring shows that promote values as well. Works Cited Bandura, Albert. Social Learning Theory. Prentice-Hall. 1977 Croteau, David. Media Society: Industries, Images and Audiences. Thousand Oaks, CA: Sage. 2003. Freedman, Jonathan. Media Violence and Its Effect on Aggression: Assessing the Scientific Evidence. University of Toronto Press. 2002. Partenheimer, David. Public Affairs Office. Childhood Exposure To Media Violence Predicts Young Adult Aggressive Behavior, According To A New 15-Year Study. 2003. Retrieved on March 7, 2008 from http://www. apa. org/releases/media_violence. html

Trends in Social Welfare and Crime Control

Trends in Social Welfare and Crime Control Georgiana Raluca Andrei Explain and illustrate the claim that contemporary trends in social welfare and crime control policy are indicative of a punitive turn. In contemporary Western societies the division between crime control and welfare is blurred, with the two coming together to produce a complex and sometimes ambiguous policy mix, within which crime control policy substitutes for welfare but may also incorporate welfarist notions of care and protection. The threat and fear of crime has impacted on public and policy attitudes towards welfare and crime control through a process of innovation in law and policy that blurs the boundaries between traditional crime control and welfare fields. Punitivity is a term which means that systems of punishment have become harsher and that though measures have a large degree of popular support (Cochrane and Talbot, 2008, p. 11). Allan Cochrane and Deborah Talbot (2008) suggest that the security/insecurity nexus illuminates a set of connections between the worlds of social welfare (broadly, the search for security) and crime control (broadly, responses to threats of insecurity). The policy worlds of social welfare and crime control need to be understood in relation to one another. In the contemporary world, demands for security and fears of insecurity are present and visible in personal lives, in political agendas and in policymaking domains. The search for security is likely to be unfinished as efforts to ensure security paradoxically heighten personal and societal senses of insecurity, in turn leading to further searches for more security. The emergence of security as a personal, governmental and policy concern is reflected in the work of social theorists and policy analysts, who have debated how the search for security may be understood as shaping social relations and social policy. There are competing app roaches to achieving security. Some emphasize the need to extend criminal justice and legal systems to address the behaviors of those that threaten ‘our’ security; others highlight the need to address broader social divisions, inequalities and problems that undermine the security of societies. Security is a concept with multiple dimensions at individual, group, national and global levels. It’s sometimes argued that the responsibility for achieving security rests with us as individuals rather than with governments. Collective responses to the search for social and economic security are visible in the work of institutions, such as trade unions, credit unions, charities, businesses and governments. These organisations and institutions work to ensure economic security through work, welfare benefits, or pensions, and health security through medical support and care in times of illness and infirmity. They also work to ensure the air we breathe is free from pollution, the water we drink is clean, and the food we eat is uncontaminated. The loss of any one of these will undermine the security of individuals and potentially of societies. Government seek to defend the nation from perceived threats, such as terrorism, political dissent and foreign aggression, and to secure the resources necessary to support their economies and population’s water, food and energy. They enter into international agreements with other governments to address threats of global crime. For example money laundering and trafficking of humans, environmental degradation such as problems of global warming, pollution and waning biodiversity; and also to cooperate with other countries on matters of policing and justice. Security has meanings at every level of human existence from the most private needs and relationships to the broadest currents of international relations and global problems. Focusing on different sources of insecurity leads to different ideas about how we can achieve security. Focusing on security may heighten the anxieties and feelings of insecurity whether now or about the future. They may lead us to try to achieve our own security and that of our families in ways that make others less secure. For example, securing the houses with cameras, alarms, and fences, a nd having police officers visible on the streets, may make us feel safer. But it may also make others more fearful of crime. Actions taken by governments in the name of protection from internal and external security threats sometimes come at the cost of personal freedoms and civil liberties of entire populations. Measures used in pursuit of security often fail to deliver it, and may often, paradoxically,increasea sense ofinsecurity. Security is increasingly being sought (by those who can afford it) through private solutions. Examples of such solutions include living in secure residential enclaves or driving sports utility vehicles (SUVs). This recourse to private solutions represents a form of risk management and social retreat. The media is one of the main drivers of insecurity. The news organisations create a false picture of the problem of crime, exaggerating certain categories of offending, such as random and violent attacks by strangers, and ignoring or underplaying other types, such as the crimes of governments and powerful organisations, or domestic crimes within the family. This can result in a distortion of public perceptions about crime, with greatest level of fear attached to crimes which are least likely to affect them. It has been noted that fear of crime often exceeds the actual risk of personal harm (Jewkes, 2008, p. 33). As individuals, people seek to manage risk by creating safe spaces in a variety of ways. At one extreme these strategies include narrowly delimited places of retreat for personal safety, which might incorporate a range of security devices including barred windows, spy glass, intercom systems. Families are a site of both individual and social security; that is, they are seen as being a key social formation that ensures personal security, as well as a ‘building block’ of society and social order. Families have tended to remain at the top of political and policy agendas, with strong families being equated with strong societies. However, families can also be understood as sites of insecurity – for individuals, who experience family life as harmful or neglectful, and for societies more broadly. While recent debate has centred on whether family change represents some kind of social decline or descent into social disorder, ‘family breakdown’, ‘problem families’ or ‘failing’ families are not new anxieties. For many decades, families who were thought to be ‘failing’ in some way have been a target of social welfare interventions and, increasingly, of crime prevention strategies. Families mirror the contradictio ns in relation to security – they offer a range of securities and act as sites of safety and social welfare, but they also present a range of insecurities, threats and dangers. This means that families are the focus of not only social welfare policy but also crime control policy. Some families are perceived as ‘better’ and more competent than others, and some families are perceived as problematic, disorderly and threatening, and therefore in need of different kinds of policy intervention, including crime control and social welfare policies. These perceptions can be normative and influenced by assumptions based on class, ethnicity and sexuality. Families are closely connected to child welfare issues. Contemporary anxieties about the nature of childhood, together with conflicting ideas about children – as vulnerable and in need of protection and care, and as threats to society and in need of control – are reflected in child and family policy intervent ions. These tensions and ambiguities about children inform social policies aimed at providing both welfare support and reducing crime. Antisocial behaviour and hate crime legislation can both be understood as sites in which the criminal justice system has been extended into new areas. In this way, there is an increasing shift to a more punitive approach within criminal justice systems, particularly in the UK and the USA. Anti-social Behaviour Orders (ASBOs), were part of an increasingly large and complex set of New Labour measures for managing and governing populations. Wacquant stated that â€Å"various neo-conservative think tanks in the USA were able to valorise the diminution of the social or welfare state† and that punitive measures were spreading from USA through Europe. According to the article, the USA/UK policy is being defined by â€Å"mass imprisonment, curfews, interventions based on risk assessment rather than need, zero tolerance, naming and shaming† , becoming more punitive and affecting everyday social relations. States all around the world seem to take a puntive turn to young offending. The depth of the punitive turn in USA in the 1990s is undeniable and Wacquant’s thesis is being supported by quantitative data that shows an increase of children detained in â€Å"juvenile secure estate† in UK and Wales. The American intolerance for those under 18 is getting more popular in the rest of the world. A punitive turn in juvenile justice in a number of countries in Western Europe has been more repressive but not necessarily more efective. It has achieved a political legitimacy to the detriment of traditional principles of juvenile protection and support. The article provides important data that shows the high number of immigrants and minority groups under arrest or in detention and the more punitive elements of juvenile justice. It is difficult to estimate the total amount of the juvenile secure population in various countries at various times due to differences in defining a child, a juvenile. Different countries have different ages of criminal responsability, there is also a difference in definition of offences which make it difficult to compare the countries. Security cannot be fully understood without reference toinsecurity, the idea of security implies the threat of insecurity, so that insecurity and security are intertwined. The ways in which welfare and crime control policies intersect and are entangled help to shape experiences of social inequality. Families can be sites of both security and insecurity. Identifying differences in experiences of security and insecurity is important for understanding, in turn, the different responses of policy and legislation to the (in)securities of family lives. In order to keep under control juvenile and adult crime rates, the system becomes punitive and adopts extreme solutions that will only lead to more drastic consequences. Words: 1652 words References Cochrane, A. and Talbot, D. (2008) ‘The search for security’, in Cochrane, A. and Talbot, D. (eds)Security: Welfare, Crime and Society, Open University; Jewkes, Y. (2008) Insecurity, fear and social retreat, in Cochrane, A. and Talbot, D. (eds)Security: Welfare, Crime and Society, Open University; Muncie, John (2008). The ‘punitive’ turn in juvenile justice: cultures of control and rights compliance in western Europe and the USA. Youth Justice, 8(2) pp. 107–121. Reflection I found it challenging to incorporate in my essay the details from the journal article due to the large amount of information provided. The journal article was written in a different way than the course materials from OU and it needed extra attention. The language used was complex and specialised and required further investigation. I developed the ability to integrate a journal article into my essay. I have used the skills that I have practiced before such as gathering ideas from different sources and create an essay, reading and interpreting different types of evidences such as journal articles or quantitative data. I have used my tutor’s previous feedback and tried to be more confident with using references.

Medical Data Analytics Using R

Medical Data Analytics Using R 1.) R for Recency => months since last donation, 2.) F for Frequency => total number of donation, 3.) M for Monetary => total amount of blood donated in c.c., 4.) T for Time => months since first donation and 5.) Binary variable => 1 -> donated blood, 0-> didnt donate blood. The main idea behind this dataset is the concept of relationship management CRM. Based on three metrics: Recency, Frequency and Monetary (RFM) which are 3 out of the 5 attributes of the dataset, we would be able to predict whether a customer is likely to donate blood again based to a marketing campaign. For example, customers who have donated or visited more currently (Recency), more frequently (Frequency) or made higher monetary values (Monetary) are more likely to respond to a marketing effort. Customers with less RFM score are less likely to react. It is also known in customer behavior, that the time of the first positive interaction (donation, purchase) is not significant. However, the Recency of the last donation is very important. In the traditional RFM implementation each customer is ranked based on his RFM value parameters against all the other customers and that develops a score for every customer. Customers with bigger scores are more likely to react in a positive way for example (visit again or donate). The model constructs the formula which could predict the following problem. Keep in repository only customers that are more likely to continue donating in the future and remove those who are less likely to donate, given a certain period of time. The previous statement also determines the problem which will be trained and tested in this project. Firstly, I created a .csv file and generated 748 unique random numbers in Excel in the domain [1,748] in the first column, which corresponds to the customers or users ID. Then I transferred the whole data from the .txt file (transfusion.data) to the .csv file in excel by using the delimited (,) option. Then I randomly split it in a train file and a test file. The train file contains the 530 instances and the test file has the 218 instances. Afterwards, I read both the training dataset and the test dataset. From the previous results, we can see that we have no missing or invalid values. Data ranges and units seem reasonable. Figure 1 above depicts boxplots of all the attributes and for both train and test datasets. By examining the figure, we notice that both datasets have similar distributions and there are some outliers (Monetary > 2,500) that are visible. The volume of blood variable has a high correlation with frequency. Because the volume of blood that is donated each time is fixed, the Monetary value is proportional to the Frequency (number of donations) each person gave. For example, if the amount of blood drawn in each person was 250 ml/bag (Taiwan Blood Services Foundation 2007) March then Monetary = 250*Frequency. This is also why in the predictive model we will not consider the Monetary attribute in the implementation. So, it is reasonable to expect that customers with higher frequency will have a lot higher Monetary value. This can be verified also visually by examining the Monetary outliers for the train set. We retrieve back 83 instances. In order, to understand better the statistical dispersion of the whole dataset (748 instances) we will look at the standard deviation (SD) between the Recency and the variable whether customer has donated blood (Binary variable) and the SD between the Frequency and the Binary variable.The distribution of scores around the mean is small, which means the data is concentrated. This can also be noticed from the plots. From this correlation matrix, we can verify what was stated above, that the frequency and the monetary values are proportional inputs, which can be noticed from their high correlation. Another observation is that the various Recency numbers are not factors of 3. This goes to opposition with what the description said about the data being collected every 3 months. Additionally, there is always a maximum number of times you can donate blood per certain period (e.g. 1 time per month), but the data shows that. 36 customers donated blood more than once and 6 customers had donated 3 or more times in the same month. The features that will be used to calculate the prediction of whether a customer is likely to donate again are 2, the Recency and the Frequency (RF). The Monetary feature will be dropped. The number of categories for R and F attributes will be 3. The highest RF score will be 33 equivalent to 6 when added together and the lowest will be 11 equivalent to 2 when added together. The threshold for the added score to determine whether a customer is more likely to donate blood again or not, will be set to 4 which is the median value. The users will be assigned to categories by sorting on RF attributes as well as their scores. The file with the donators will be sorted on Recency first (in ascending order) because we want to see which customers have donated blood more recently. Then it will be sorted on frequency (in descending order this time because we want to see which customers have donated more times) in each Recency category. Apart from sorting, we will need to apply some business rules that have occurred after multiple tests: For Recency (Business rule 1): If the Recency in months is less than 15 months, then these customers will be assigned to category 3. If the Recency in months is equal or greater than 15 months and less than 26 months, then these customers will be assigned to category 2. Otherwise, if the Recency in months is equal or greater than 26 months, then these customers will be assigned to category 1 And for Frequency (Business rule 2): If the Frequency is equal or greater than 25 times, then these customers will be assigned to category 3. If the Frequency is less than 25 times or greater than 15 months, then these customers will be assigned to category 2. If the Frequency is equal or less than 15 times, then these customers will be assigned to category 1 RESULTS The output of the program are two smaller files that have resulted from the train file and the other one from the test file, that have excluded several customers that should not be considered future targets and kept those that are likely to respond. Some statistics about the precision, recall and the balanced F-score of the train and test file have been calculated and printed. Furthermore, we compute the absolute difference between the results retrieved from the train and test file to get the offset error between these statistics. By doing this and verifying that the error numbers are negligible, we validate the consistency of the model implemented. Moreover, we depict two confusion matrices one for the test and one for the training by calculating the true positives, false negatives, false positives and true negatives. In our case, true positives correspond to the customers (who donated on March 2007) and were classified as future possible donators. False negatives correspond to the customers (who donated on March 2007) but were not classified as future possible targets for marketing campaigns. False positives correlate to customers (who did not donate on March 2007) and were incorrectly classified as possible future targets. Lastly, true negatives which are customers (who did not donate on March 2007) and were correctly classified as not plausible future donators and therefore removed from the data file. By classification we mean the application of the threshold (4) to separate those customers who are more likely and less likely to donate again in a certain future period. Lastly, we calculate 2 more single value metrics for both train and test files the Kappa Statistic (general statistic used for classification systems) and Matthews Correlation Coefficient or cost/reward measure. Both are normalized statistics for classification systems, its values never exceed 1, so the same statistic can be used even as the number of observations grows. The error for both measures are MCC error: 0.002577   and Kappa error:   0.002808, which is very small (negligible), similarly with all the previous measures. REFERENCES UCI Machine Learning Repository (2008) UCI machine learning repository: Blood transfusion service center data set. Available at: http://archive.ics.uci.edu/ml/datasets/Blood+Transfusion+Service+Center (Accessed: 30 January 2017). Fundation, T.B.S. (2015) Operation department. Available at: http://www.blood.org.tw/Internet/english/docDetail.aspx?uid=7741pid=7681docid=37144 (Accessed: 31 January 2017). The Appendix with the code starts below. However the whole code has been uploaded on my Git Hub profile and this is the link where it can be accessed. https://github.com/it21208/RassignmentDataAnalysis/blob/master/RassignmentDataAnalysis.R library(ggplot2) library(car)   # read training and testing datasets traindata à ¯Ã†â€™Ã… ¸Ãƒâ€šÃ‚   read.csv(C:/Users/Alexandros/Dropbox/MSc/2nd Semester/Data analysis/Assignment/transfusion.csv) testdata à ¯Ã†â€™Ã… ¸Ãƒâ€šÃ‚   read.csv(C:/Users/Alexandros/Dropbox/MSc/2nd Semester/Data analysis/Assignment/test.csv) # assigning the datasets to dataframes dftrain à ¯Ã†â€™Ã… ¸ data.frame(traindata) dftest à ¯Ã†â€™Ã… ¸ data.frame(testdata) sapply(dftrain, typeof) # give better names to columns names(dftrain)[1] à ¯Ã†â€™Ã… ¸ ID names(dftrain)[2] à ¯Ã†â€™Ã… ¸ recency names(dftrain)[3]à ¯Ã†â€™Ã… ¸frequency names(dftrain)[4]à ¯Ã†â€™Ã… ¸cc names(dftrain)[5]à ¯Ã†â€™Ã… ¸time names(dftrain)[6]à ¯Ã†â€™Ã… ¸donated # names(dftest)[1]à ¯Ã†â€™Ã… ¸ID names(dftest)[2]à ¯Ã†â€™Ã… ¸recency names(dftest)[3]à ¯Ã†â€™Ã… ¸frequency names(dftest)[4]à ¯Ã†â€™Ã… ¸cc names(dftest)[5]à ¯Ã†â€™Ã… ¸time names(dftest)[6]à ¯Ã†â€™Ã… ¸donated # drop time column from both files dftrain$time à ¯Ã†â€™Ã… ¸ NULL dftest$time à ¯Ã†â€™Ã… ¸ NULL #   sort (train) dataframe on Recency in ascending order sorted_dftrain à ¯Ã†â€™Ã… ¸ dftrain[ order( dftrain[,2] ), ] #   add column in (train) dataframe -   hold score (rank) of Recency for each customer sorted_dftrain[ , Rrank] à ¯Ã†â€™Ã… ¸ 0 #   convert train file from dataframe format to matrix matrix_train à ¯Ã†â€™Ã… ¸ as.matrix(sapply(sorted_dftrain, as.numeric)) #   sort (test) dataframe on Recency in ascending order sorted_dftest à ¯Ã†â€™Ã… ¸ dftest[ order( dftest[,2] ), ] #   add column in (test) dataframe -hold score (rank) of Recency for each customer sorted_dftest[ , Rrank] à ¯Ã†â€™Ã… ¸ 0 #   convert train file from dataframe format to matrix matrix_test à ¯Ã†â€™Ã… ¸ as.matrix(sapply(sorted_dftest, as.numeric)) # categorize matrix_train and add scores for Recency apply business rule for(i in 1:nrow(matrix_train)) { if (matrix_train [i,2]   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   matrix_train [i,6] à ¯Ã†â€™Ã… ¸ 3 } else if ((matrix_train [i,2] = 15)) {   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   matrix_train [i,6] à ¯Ã†â€™Ã… ¸ 2 } else {   matrix_train [i,6] à ¯Ã†â€™Ã… ¸ 1   }   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   } # categorize matrix_test and add scores for Recency apply business rule for(i in 1:nrow(matrix_test)) { if (matrix_test [i,2]   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   matrix_test [i,6] à ¯Ã†â€™Ã… ¸ 3 } else if ((matrix_test [i,2] = 15)) {   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   matrix_test [i,6] à ¯Ã†â€™Ã… ¸ 2 } else {   matrix_test [i,6] à ¯Ã†â€™Ã… ¸ 1 }   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   } # convert matrix_train back to dataframe sorted_dftrain à ¯Ã†â€™Ã… ¸ data.frame(matrix_train) # sort dataframe 1rst by Recency Rank (desc.) then by Frequency (desc.) sorted_dftrain_2à ¯Ã†â€™Ã… ¸ sorted_dftrain[order(-sorted_dftrain[,6], -sorted_dftrain[,3] ), ] # add column in train dataframe- hold Frequency score (rank) for each customer sorted_dftrain_2[ , Frank] à ¯Ã†â€™Ã… ¸ 0 # convert dataframe to matrix matrix_train à ¯Ã†â€™Ã… ¸ as.matrix(sapply(sorted_dftrain_2, as.numeric)) # convert matrix_test back to dataframe sorted_dftest à ¯Ã†â€™Ã… ¸ data.frame(matrix_test) # sort dataframe 1rst by Recency Rank (desc.) then by Frequency (desc.) sorted_dftest2 à ¯Ã†â€™Ã… ¸ sorted_dftest[ order( -sorted_dftest[,6], -sorted_dftest[,3] ), ] # add column in test dataframe- hold Frequency score (rank) for each customer sorted_dftest2[ , Frank] à ¯Ã†â€™Ã… ¸ 0 # convert dataframe to matrix matrix_test à ¯Ã†â€™Ã… ¸ as.matrix(sapply(sorted_dftest2, as.numeric)) #categorize matrix_train, add scores for Frequency for(i in 1:nrow(matrix_train)){    if (matrix_train[i,3] >= 25) {   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   matrix_train[i,7] à ¯Ã†â€™Ã… ¸ 3    } else if ((matrix_train[i,3] > 15) (matrix_train[i,3]   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   matrix_train[i,7] à ¯Ã†â€™Ã… ¸ 2    } else {   matrix_train[i,7] à ¯Ã†â€™Ã… ¸ 1   }   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   } #categorize matrix_test, add scores for Frequency for(i in 1:nrow(matrix_test)){    if (matrix_test[i,3] >= 25) {   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   matrix_test[i,7] à ¯Ã†â€™Ã… ¸ 3    } else if ((matrix_test[i,3] > 15) (matrix_test[i,3]   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   matrix_test[i,7] à ¯Ã†â€™Ã… ¸ 2    } else {  Ãƒâ€šÃ‚   matrix_test[i,7] à ¯Ã†â€™Ã… ¸ 1   } } #   convert matrix test back to dataframe sorted_dftrain à ¯Ã†â€™Ã… ¸ data.frame(matrix_train) # sort (train) dataframe 1rst on Recency rank (desc.) 2nd Frequency rank (desc.) sorted_dftrain_2 à ¯Ã†â€™Ã… ¸ sorted_dftrain[ order( -sorted_dftrain[,6], -sorted_dftrain[,7] ), ] # add another column for the Sum of Recency rank and Frequency rank sorted_dftrain_2[ , SumRankRAndF] à ¯Ã†â€™Ã… ¸ 0 # convert dataframe to matrix matrix_train à ¯Ã†â€™Ã… ¸ as.matrix(sapply(sorted_dftrain_2, as.numeric)) #   convert matrix test back to dataframe sorted_dftest à ¯Ã†â€™Ã… ¸ data.frame(matrix_test) # sort (train) dataframe 1rst on Recency rank (desc.) 2nd Frequency rank (desc.) sorted_dftest2 à ¯Ã†â€™Ã… ¸ sorted_dftest[ order( -sorted_dftest[,6],   -sorted_dftest[,7] ), ] # add another column for the Sum of Recency rank and Frequency rank sorted_dftest2[ , SumRankRAndF] à ¯Ã†â€™Ã… ¸ 0 # convert dataframe to matrix matrix_test à ¯Ã†â€™Ã… ¸ as.matrix(sapply(sorted_dftest2, as.numeric)) # sum Recency rank and Frequency rank for train file for(i in 1:nrow(matrix_train)) { matrix_train[i,8] à ¯Ã†â€™Ã… ¸ matrix_train[i,6] + matrix_train[i,7] } # sum Recency rank and Frequency rank for test file for(i in 1:nrow(matrix_test)) { matrix_test[i,8] à ¯Ã†â€™Ã… ¸ matrix_test[i,6] + matrix_test[i,7] } # convert matrix_train back to dataframe sorted_dftrain à ¯Ã†â€™Ã… ¸ data.frame(matrix_train) # sort train dataframe according to total rank in descending order sorted_dftrain_2 à ¯Ã†â€™Ã… ¸ sorted_dftrain[ order( -sorted_dftrain[,8] ), ] # convert sorted train dataframe matrix_train à ¯Ã†â€™Ã… ¸ as.matrix(sapply(sorted_dftrain_2, as.numeric)) # convert matrix_test back to dataframe sorted_dftest à ¯Ã†â€™Ã… ¸ data.frame(matrix_test) # sort test dataframe according to total rank in descending order sorted_dftest2 à ¯Ã†â€™Ã… ¸ sorted_dftest[ order( -sorted_dftest[,8] ), ] # convert sorted test dataframe to matrix matrix_test à ¯Ã†â€™Ã… ¸ as.matrix(sapply(sorted_dftest2, as.numeric)) # apply business rule check count customers whose score >= 4 and that Have Donated, train file # check count for all customers that have donated in the train dataset count_train_predicted_donations à ¯Ã†â€™Ã… ¸ 0 counter_train à ¯Ã†â€™Ã… ¸ 0 number_donation_instances_whole_train à ¯Ã†â€™Ã… ¸ 0 false_positives_train_counter à ¯Ã†â€™Ã… ¸ 0 for(i in 1:nrow(matrix_train)) {    if ((matrix_train[i,8] >= 4) (matrix_train[i,5] == 1)) {   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   count_train_predicted_donations = count_train_predicted_donations + 1   } if ((matrix_train[i,8] >= 4) (matrix_train[i,5] == 0)) {   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   false_positives_train_counter = false_positives_train_counter + 1}    if (matrix_train[i,8] >= 4) {   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   counter_train à ¯Ã†â€™Ã… ¸ counter_train + 1   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   }    if (matrix_train[i,5] == 1) {   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   number_donation_instances_whole_train à ¯Ã†â€™Ã… ¸ number_donation_instances_whole_train + 1    } } # apply business rule check count customers whose score >= 4 and that Have Donated, test file # check count for all customers that have donated in the test dataset count_test_predicted_donations à ¯Ã†â€™Ã… ¸ 0 counter_test à ¯Ã†â€™Ã… ¸ 0 number_donation_instances_whole_test à ¯Ã†â€™Ã… ¸ 0 false_positives_test_counter à ¯Ã†â€™Ã… ¸ 0 for(i in 1:nrow(matrix_test)) {    if ((matrix_test[i,8] >= 4) (matrix_test[i,5] == 1)) {   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   count_test_predicted_donations = count_test_predicted_donations + 1   } if ((matrix_test[i,8] >= 4) (matrix_test[i,5] == 0)) {   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   false_positives_test_counter = false_positives_test_counter + 1}    if (matrix_test[i,8] >= 4) {   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   counter_test à ¯Ã†â€™Ã… ¸ counter_test + 1   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   }    if (matrix_test[i,5] == 1) {   Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   number_donation_instances_whole_test à ¯Ã†â€™Ã… ¸ number_donation_instances_whole_test + 1   Ãƒâ€šÃ‚   } } # convert matrix_train to dataframe dftrain à ¯Ã†â€™Ã… ¸ data.frame(matrix_train) # remove the group of customers who are less likely to donate again in the future from train file dftrain_final à ¯Ã†â€™Ã… ¸ dftrain[c(1:counter_train),1:8] # convert matrix_train to dataframe dftest à ¯Ã†â€™Ã… ¸ data.frame(matrix_test) # remove the group of customers who are less likely to donate again in the future from test file dftest_final à ¯Ã†â€™Ã… ¸ dftest[c(1:counter_test),1:8] # save final train dataframe as a CSV in the specified directory reduced target future customers write.csv(dftrain_final, file = C:\Users\Alexandros\Dropbox\MSc\2nd Semester\Data analysis\Assignment\train_output.csv, row.names = FALSE) #save final test dataframe as a CSV in the specified directory reduced target future customers write.csv(dftest_final, file = C:\Users\Alexandros\Dropbox\MSc\2nd Semester\Data analysis\Assignment\test_output.csv, row.names = FALSE) #train precision=number of relevant instances retrieved / number of retrieved instances collect.530 precision_train à ¯Ã†â€™Ã… ¸Ãƒâ€šÃ‚   count_train_predicted_donations / counter_train # train recall = number of relevant instances retrieved / number of relevant instances in collect.530 recall_train à ¯Ã†â€™Ã… ¸ count_train_predicted_donations / number_donation_instances_whole_train # measure combines PrecisionRecall is harmonic mean of PrecisionRecall balanced F-score for # train file f_balanced_score_train à ¯Ã†â€™Ã… ¸ 2*(precision_train*recall_train)/(precision_train+recall_train) # test precision precision_test à ¯Ã†â€™Ã… ¸ count_test_predicted_donations / counter_test # test recall recall_test à ¯Ã†â€™Ã… ¸ count_test_predicted_donations / number_donation_instances_whole_test # the balanced F-score for test file f_balanced_score_test à ¯Ã†â€™Ã… ¸ 2*(precision_test*recall_test)/(precision_test+recall_test) # error in precision error_precision à ¯Ã†â€™Ã… ¸ abs(precision_train-precision_test) # error in recall error_recall à ¯Ã†â€™Ã… ¸ abs(recall_train-recall_test) # error in f-balanced scores error_f_balanced_scores à ¯Ã†â€™Ã… ¸ abs(f_balanced_score_train-f_balanced_score_test) # Print Statistics for verification and validation cat(Precision with training dataset: , precision_train) cat(Recall with training dataset: , recall_train) cat(Precision with testing dataset: , precision_test) cat(Recall with testing dataset: , recall_test) cat(The F-balanced scores with training dataset: , f_balanced_score_train) cat(The F-balanced scores with testing dataset:   , f_balanced_score_test) cat(Error in precision: , error_precision) cat(Error in recall: , error_recall) cat(Error in F-balanced scores: , error_f_balanced_scores) # confusion matrix (true positives, false positives, false negatives, true negatives) # calculate true positives for train which is the variable count_train_predicted_donations # calculate false positives for train which is the variable false_positives_train_counter # calculate false negatives for train false_negatives_for_train à ¯Ã†â€™Ã… ¸ number_donation_instances_whole_train count_train_predicted_donations # calculate true negatives for train true_negatives_for_train à ¯Ã†â€™Ã… ¸ (nrow(matrix_train) number_donation_instances_whole_train) false_positives_train_counter collect_trainà ¯Ã†â€™Ã… ¸c(false_positives_train_counter, true_negatives_for_train, count_train_predicted_donations, false_negatives_for_train) # calculate true positives for test which is the variable count_test_predicted_donations # calculate false positives for test which is the variable false_positives_test_counter # calculate false negatives for test false_negatives_for_test à ¯Ã†â€™Ã… ¸ number_donation_instances_whole_test count_test_predicted_donations # calculate true negatives for test true_negatives_for_testà ¯Ã†â€™Ã… ¸(nrow(matrix_test)-number_donation_instances_whole_test)- false_positives_test_counter collect_test à ¯Ã†â€™Ã… ¸ c(false_positives_test_counter, true_negatives_for_test, count_test_predicted_donations, false_negatives_for_test) TrueCondition à ¯Ã†â€™Ã… ¸ factor(c(0, 0, 1, 1)) PredictedCondition à ¯Ã†â€™Ã… ¸ factor(c(1, 0, 1, 0)) # print confusion matrix for train df_conf_mat_train à ¯Ã†â€™Ã… ¸ data.frame(TrueCondition,PredictedCondition,collect_train) ggplot(data = df_conf_mat_train, mapping = aes(x = PredictedCondition, y = TrueCondition)) +    geom_tile(aes(fill = collect_train), colour = white) +    geom_text(aes(label = sprintf(%1.0f, collect_train)), vjust = 1) +    scale_fill_gradient(low = blue, high = red) +    theme_bw() + theme(legend.position = none) #   print confusion matrix for test df_conf_mat_test à ¯Ã†â€™Ã… ¸ data.frame(TrueCondition,PredictedCondition,collect_test) ggplot(data =   df_conf_mat_test, mapping = aes(x = PredictedCondition, y = TrueCondition)) +    geom_tile(aes(fill = collect_test), colour = white) +    geom_text(aes(label = sprintf(%1.0f, collect_test)), vjust = 1) +    scale_fill_gradient(low = blue, high = red) +    theme_bw() + theme(legend.position = none) # MCC = (TP * TN FP * FN)/sqrt((TP+FP) (TP+FN) (FP+TN) (TN+FN)) for train values mcc_train à ¯Ã†â€™Ã… ¸ ((count_train_predicted_donations * true_negatives_for_train) (false_positives_train_counter * false_negatives_for_train))/sqrt((count_train_predicted_donations+false_positives_train_counter)*(count_train_predicted_donations+false_negatives_for_train)*(false_positives_train_counter+true_negatives_for_train)*(true_negatives_for_train+false_negatives_for_train)) # print MCC for train cat(Matthews Correlation Coefficient for train: ,mcc_train) # MCC = (TP * TN FP * FN)/sqrt((TP+FP) (TP+FN) (FP+TN) (TN+FN)) for test values mcc_test à ¯Ã†â€™Ã… ¸ ((count_test_predicted_donations * true_negatives_for_test) (false_positives_test_counter * false_negatives_for_test))/sqrt((count_test_predicted_donations+false_positives_test_counter)*(count_test_predicted_donations+false_negatives_for_test)*(false_positives_test_counter+true_negatives_for_test)*(true_negatives_for_test+false_negatives_for_test)) # print MCC for test cat(Matthews Correlation Coefficient for test: ,mcc_test) # print MCC err between train and err cat(Matthews Correlation Coefficient error: ,abs(mcc_train-mcc_test)) # Total = TP + TN + FP + FN for train total_train à ¯Ã†â€™Ã… ¸ count_train_predicted_donations + true_negatives_for_train + false_positives_train_counter + false_negatives_for_train # Total = TP + TN + FP + FN for test   total_test à ¯Ã†â€™Ã… ¸ count_test_predicted_donations + true_negatives_for_test + false_positives_test_counter + false_negatives_for_test # totalAccuracy = (TP + TN) / Total for train values totalAccuracyTrain à ¯Ã†â€™Ã… ¸ (count_train_predicted_donations + true_negatives_for_train)/ total_train # totalAccuracy = (TP + TN) / Total for test values totalAccuracyTest à ¯Ã†â€™Ã… ¸ (count_test_predicted_donations + true_negatives_for_test)/ total_test # randomAccuracy = ((TN+FP)*(TN+FN)+(FN+TP)*(FP+TP)) / (Total*Total)   for train values randomAccuracyTrainà ¯Ã†â€™Ã… ¸((true_negatives_for_train+false_positives_train_counter)*(true_negatives_for_train+false_negatives_for_train)+(false_negatives_for_train+count_train_predicted_donations)*(false_positives_train_counter+count_train_predicted_donations))/(total_train*total_train) # randomAccuracy = ((TN+FP)*(TN+FN)+(FN+TP)*(FP+TP)) / (Total*Total)   for test values randomAccuracyTestà ¯Ã†â€™Ã… ¸((true_negatives_for_test+false_positives_test_counter)*(true_negatives_for_test+false_negatives_for_test)+(false_negatives_for_test+count_test_predicted_donations)*(false_positives_test_counter+count_test_predicted_donations))/(total_test*total_test) # kappa = (totalAccuracy randomAccuracy) / (1 randomAccuracy) for train kappa_train à ¯Ã†â€™Ã… ¸ (totalAccuracyTrain-randomAccuracyTrain)/(1-randomAccuracyTrain) # kappa = (totalAccuracy randomAccuracy) / (1 randomAccuracy) for test kappa_test à ¯Ã†â€™Ã… ¸ (totalAccuracyTest-randomAccuracyTest)/(1-randomAccuracyTest) # print kappa error cat(Kappa error: ,abs(kappa_train-kappa_test))