buy custom The Condition of African Nations Fifty Years after Independence essay

buy custom The Condition of African Nations Fifty Years after Independence essay More than 60 years since the independence of several African states, they are still seen as relying on its former colonies. It is worth noting that several African countries have been depending on their former colonies. Statistics illustrates that this has been caused by the increasing levels of poverty in most African States. Furthermore, many see the rise of African dictators as an indication that they are making themselves wealthy at the expense of their unsuspecting citizens. This has made the living conditions in the given countries more unbearable as the gap between the rich and the poor continue worsening. The following paper will look into an in-depth analysis on the reasons that causes several African countries to rely on their former colonies. Despite most countries trying to rely on their domestic production, the increasing level of poverty, corruption within the government and bad leadership has made its citizens to look unto the West as a sign of hope towards restoring t he already worsening conditions. This paper will look on three major issues of disease, bad governance and disease as the reason why Africa is still depending on former colonies. Three major causes of over dependence on former colonies a)Diseases There is great concern over the increasing rate of disease in Africa. The geographic condition of Africa makes it more vulnerable to disease as compared to other continents which experience colder climates. Malaria is one great illness that is proving to kill several people and in a bid to control its spread, several African countries are turning to former colonies with a bid to seeking the essential assistance so as to its spread (Obeng et al, 2002). Furthermore, the increasing rate of poverty in these countries leaves little option for the pharmaceutical companies to invest in the country. As a result, most of this countries approach former colonies that are well established to come back and invest on pharmaceuticals that have the ability to offer more medical attention to diseases like malaria. The several diseases is what causes a health care burden to different governments who in turn suffer from lack of ways to approach the given situation. They usually see a way forward as turning to the Western countries who are already established and who have the economic prowess to steer the several challenges. Over the last twenty years, HIV/AIDS have taken Africa by storm, claiming the life of several people (Mwakikagile, 2006). Many have argued that the rate of poverty i Africa has increased the rate of HIV/AIDS and countries like South Africa, Botswana and Swaziland which were showing signs of development now have to cope with initiatives to stop this pandemic from spreading. So how do they do this? They engage in enlisting the help of countries that have advanced technolo gy with the ready technical tools to control the disease. HIV/AIDS is feared as being one dangerous disease that is likely to kill majority of the working population in a developing country. Furthermore the working population will greatly impact on the countrys economy as well as taking away a great portion of human labour. In order for a country to counter the effects of disease spread in Africa, and owning to the lack of the necessary technology, they well enlist the assistance of former colonies that are well placed with the already established entities (Smith, 1993). It is through this orientation that governments also seek the importation of anti-retroviral drugs from former colonies and being that they cannot do so continually, they have to ask for help in purchasing the drugs. This can only be achieved by seeking foreign aids from former colonies. b)Colonialism Soon after several African countries became independent, there relative wealth was in the public limelight to be seen. However, the economic prosperity of African Nations started slowing down as soon as the colonizers started departing. As a result, the government in place saw that in order for economic prosperity to be realized, and then they had to continue with the link between them and former colonial powers. However, the link had been destabilized with African countries attaining independence (Garcia et al, 2003). It was widely viewed that the exit of colonial powers from Africa was beginning of the nation down fall being that they were more experienced in several fields like agriculture and planning. In the various administrative levels of government, Africa leaders were faced with lack of the necessary professionals to run the various sectors. European administrators had been vibrant in realizing that African countries had made a stride towards economic progress. However, independence meant their services were no longer needed, a fact that left the government more vulnerable. Government leaders then had to enlist the help of former colonial powers in giving the training as well as the necessary education needed to operate the government that they had inherited from the colonial masters (Cooper, 2002). The Congo Free State is a perfect exampple of ideas of the Europeans which were never implemented and which left the country poorer. The people in this region believe that were they to implement the policies of Leopold II, then they were likely to have made considerable progress. Colonialism can therefore be noted as having led to great progress on the African continent. However, the exit of the colonial masters was an indication that this progress was going to be affected. The government was going to lack the professional expertise and the establish economy was to be back to ruins. In order to ensure that this decline does not occur, it was vital that the governments in several African countries remain in contact with the colonies so as to boost their chances of survival. It was a case of retaining the European way of thinking so as to have an effective economy. c)Bad Governance The political condition of African countries has resulted to the increasing state of poverty. The state of democracy in several African countries has never been successful. There have been successful African leaders who have tried to maintain the prosperous leadership of former colonies while others have taken power unto their hands and ruled with animosity resulting in increasing levels of poverty of African states. Leaders of oppositions have tried to enlist the help of former colonies to bring in foreign assistance in terms of persuading the bad leadership out of power. Exporting the already processed goods can never be successful unless they link with former colonies that will encourage their citizens to buy. This shows that Africans still need the colonies in order to market their products abroad (African Timeline, 2010). On the other hand, the presence of dictatorial leaders have indicated that African will never progress because leaders are after enriching themselves by the ac cumulation of more wealth hence neglecting the common people. Conclusion The paper has illustrates the fact that African nations, despite 60 years after attaining independence, have remained in the dark age of underdevelopment. For instance, several nations still depend on their former colonial powers. This is because they have to enlist the help of colonial masters to help them in the development of medicine that can limit disease like malaria and HIV/AIDS. On the other hand African countries are left with the option of relying on former colonies as a result of bad leadership and colonialism. All the three factors have been outlined through an in-depth analysis. Buy custom The Condition of African Nations Fifty Years after Independence essay

What Is Statistical Significance How Is It Calculated

What Is Statistical Significance How Is It Calculated SAT / ACT Prep Online Guides and Tips If you've ever read a wild headline like, "Study Shows Chewing Rocks Prevents Cancer," you've probably wondered how that could be possible. If you look closer at this type of article you may find that the sample size for the study was a mere handful of people. If one person in a group of five chewed rocks and didn't get cancer, does that mean chewing rocks prevented cancer? Definitely not. The study for such a conclusion doesn't have statistical significance- though the study was performed, its conclusions don't really mean anything because the sample size was small. So what is statistical significance, and how do you calculate it? In this article, we'll cover what it is, when it's used, and go step-by-step through the process of determining if an experiment is statistically significant on your own. What Is Statistical Significance? As I mentioned above, the fake study about chewing rocks isn't statistically significant. What that means is that the conclusion reached in it isn't valid, because there's not enough evidence that what happened was not random chance. A statistically significant result would be one where, after rigorous testing, you reach a certain degree of confidence in the results. We call that degree of confidence our confidence level, which demonstrates how sure we are that our data was not skewed by random chance. More specifically, the confidence level is the likelihood that an interval will contain values for the parameter we're testing. There are three major ways of determining statistical significance: If you run an experiment and your p-value is less than your alpha (significance) level, your test is statistically significant If your confidence interval doesn't contain your null hypothesis value, your test is statistically significant If your p-value is less than your alpha, your confidence interval will not contain your null hypothesis value, and will therefore be statistically significant This info probably doesn't make a whole lot of sense if you're not already acquainted with the terms involved in calculating statistical significance, so let's take a look at what it means in practice. Say, for example, that we want to determine the average typing speed of 12-year-olds in America. We'll confirm our results using the second method, our confidence interval, as it's the simplest to explain quickly. First, we'll need to set our p-value, which tells us the probability of our results being at least as extreme as they were in our sample data if our null hypothesis (a statement that there is no difference between tested information), such as that all 12-year-old students type at the same speed) is true. A typical p-value is 5 percent, or 0.05, which is appropriate for many situations but can be adjusted for more sensitive experiments, such as in building airplanes. For our experiment, 5 percent is fine. If our p-value is 5 percent, our confidence level is 95 percent- it's always the inverse of your p-value. Our confidence level expresses how sure we are that, if we were to repeat our experiment with another sample, we would get the same averages- it is not a representation of the likelihood that the entire population will fall within this range. Testing the typing speed of every 12-year-old in America is unfeasible, so we'll take a sample- 100 12-year-olds from a variety of places and backgrounds within the US. Once we average all that data, we determine the average typing speed of our sample is 45 words per minute, with a standard deviation of five words per minute. From there, we can extrapolate that the average typing speed of 12-year-olds in America is somewhere between $45 - 5z$ words per minute and $45 + 5z$ words per minute. That's our confidence interval- a range of numbers we can be confident contain our true value, in this case the real average of the typing speed of 12-year-old Americans. Our z-score, ‘z,' is determined by our confidence value. In our case, given our confidence value, that would look like $45 - 5(1.96)$ and $45 + 5(1.96)$, making our confidence interval 35.2 to 54.8. A wider confidence interval, say with a standard deviation of 15 words per minute, would give us more confidence that the true average of the entire population would fall in that range ($45Â ± \bo{15}(1.96)$), but would be less accurate. More importantly for our purposes, if your confidence interval doesn't include the null hypothesis, your result is statistically significant. Since our results demonstrate that not all 12-year-olds type the same speed, our results are significant. One reason you might set your confidence rating lower is if you are concerned about sampling errors. A sampling error, which is a common cause for skewed data, is what happens when your study is based on flawed data. For example, if you polled a group of people at McDonald's about their favorite foods, you'd probably get a good amount of people saying hamburgers. If you polled the people at a vegan restaurant, you'd be unlikely to get the same results, so if your conclusion from the first study is that most peoples' favorite food is hamburgers, you're relying on a sampling error. It's important to remember that statistical significance is not necessarily a guarantee that something is objectively true. Statistical significance can be strong or weak, and researchers can factor in bias or variances to figure out how valid the conclusion is. Any rigorous study will have numerous phases of testing- one person chewing rocks and not getting cancer is not a rigorous study. Essentially, statistical significance tells you that your hypothesis has basis and is worth studying further. For example, say you have a suspicion that a quarter might be weighted unevenly. If you flip it 100 times and get 75 heads and 25 tails, that might suggest that the coin is rigged. That result, which deviates from expectations by over 5 percent, is statistically significant. Because each coin flip has a 50/50 chance of being heads or tails, these results would tell you to look deeper into it, not that your coin is definitely rigged to flip heads over tails. The results are statistically significant in that there is a clear tendency to flip heads over tails, but that itself is not an indication that the coin is flawed. What Is Statistical Significance Used For? Statistical significance is important in a variety of fields- any time you need to test whether something is effective, statistical significance plays a role. This can be very simple, like determining whether the dice produced for a tabletop role-playing game are well-balanced, or it can be very complex, like determining whether a new medicine that sometimes causes an unpleasant side effect is still worth releasing. Statistical significance is also frequently used in business to determine whether one thing is more effective than another. This is called A/B testing- two variants, one A and one B, are tested to see which is more successful. In school, you're most likely to learn about statistical significance in a science or statistics context, but it can be applied in a great number of fields. Any time you need to determine whether something is demonstrably true or just up to chance, you can use statistical significance! How to Calculate Statistical Significance Calculating statistical significance is complex- most people use calculators rather than try to solve equations by hand. Z-test calculators and t-test calculators are two ways you can drastically slim down the amount of work you have to do. However, learning how to calculate statistical significance by hand is a great way to ensure you really understand how each piece works. Let's go through the process step by step! Step 1: Set a Null Hypothesis To set up calculating statistical significance, first designate your null hypothesis, or H0. Your null hypothesis should state that there is no difference between your data sets. For example, let's say we're testing the effectiveness of a fertilizer by taking half of a group of 20 plants and treating half of them with fertilizer. Our null hypothesis will be something like, "This fertilizer will have no effect on the plant's growth." Step 2: Set an Alternative Hypothesis Next, you need an alternative hypothesis, Ha. Your alternative hypothesis is generally the opposite of your null hypothesis, so in this case it would be something like, "This fertilizer will cause the plants who get treated with it to grow faster." Step 3: Determine Your Alpha Third, you'll want to set the significance level, also known as alpha, or ÃŽ ±. The alpha is the probability of rejecting a null hypothesis when that hypothesis is true. In the case of our fertilizer example, the alpha is the probability of concluding that the fertilizer does make plants treated with it grow more when the fertilizer does not actually have an effect. An alpha of 0.05, or 5 percent, is standard, but if you're running a particularly sensitive experiment, such as testing a medicine or building an airplane, 0.01 may be more appropriate. For our fertilizer experiment, a 0.05 alpha is fine. Your confidence level is $1 - ÃŽ ±(100%)$, so if your alpha is 0.05, that makes your confidence level 95%. Again, your alpha can be changed depending on the sensitivity of the experiment, but most will use 0.05. Step 4: One- or Two-Tailed Test Fourth, you'll need to decide whether a one- or two-tailed test is more appropriate. One-tailed tests examine the relationship between two things in one direction, such as if the fertilizer makes the plant grow. A two-tailed test measures in two directions, such as if the fertilizer makes the plant grow or shrink. Since in our example we don't want to know if the plant shrinks, we'd choose a one-tailed test. But if we were testing something more complex, like whether a particular ad placement made customers more likely to click on it or less likely to click on it, a two-tailed test would be more appropriate. A two-tailed test is also appropriate if you're not sure which direction the results will go, just that you think there will be an effect. For example, if you wanted to test whether or not adding salt to boiling water while making pasta made a difference to taste, but weren't sure if it would have a positive or negative effect, you'd probably want to go with a two-tailed test. Step 5: Sample Size Next, determine your sample size. To do so, you'll conduct a power analysis, which gives you the probability of seeing your hypothesis demonstrated given a particular sample size. Statistical power tells us the probability of us accepting an alternative, true hypothesis over the null hypothesis. A higher statistical power gives lowers our probability of getting a false negative response for our experiment. In the case of our fertilizer experiment, a higher statistical power means that we will be less likely to accept that there is no effect from fertilizer when there is, in fact, an effect. A power analysis consists of four major pieces: The effect size, which tells us the magnitude of a result within the population The sample size, which tells us how many observations we have within the sample The significance level, which is our alpha The statistical power, which is the probability that we accept an alternative hypothesis if it is true Many experiments are run with a typical power, or ÃŽ ², of 80 percent. Because these calculations are complex, it's not recommended to try to calculate them by hand- instead, most people will use a calculator like this one to figure out their sample size. Conducting a power analysis lets you know how big of a sample size you'll need to determine statistical significance. If you only test on a handful of samples, you may end up with a result that's inaccurate- it may give you a false positive or a false negative. Doing an accurate power analysis helps ensure that your results are legitimate. Step 6: Find Standard Deviation Sixth, you'll be calculating the standard deviation, $s$ (also sometimes written as $ÏÆ'$). This is where the formula gets particularly complex, as this tells you how spread out your data is. The formula for standard deviation of a sample is: $$s = √{{∑(x_i – Â µ)^2}/(N – 1)}$$ In this equation, $s$ is the standard deviation $∑$ tells you to sum all the data you collected $x_i$ is each individual data $Â µ$ is the mean of your data for each group $N$ is your total sample So, to work this out, let's go with our preliminary fertilizer test on ten plants, which might give us data something like this: Plant Growth (inches) 1 2 2 1 3 4 4 5 5 3 6 1 7 5 8 4 9 4 10 4 We need to average that data, so we add it all together and divide by the total sample number. $(2 + 1 + 4 + 5 + 3 + 1 + 5 + 4 + 4 + 4) / 10 = 3.3$ Next, we subtract each sample from the average $(x_i – Â µ)$, which will look like this: Plant Growth (inches) $x_i – Â µ$ 1 2 1.3 2 1 2.3 3 4 -0.7 4 5 -1.7 5 3 0.3 6 1 2.3 7 5 -1.7 8 4 -0.7 9 4 -0.7 10 4 -0.7 Now we square all of those numbers and add them together. $1.32 + 2.32 + -0.72 + -1.72 + 0.32 + 2.32 + -1.72 + -0.72 + -0.72 + -0.72 = 20.1$ Next, we'll divide that number by the total sample number, N, minus 1. $20.1/9 = 2.23$ And finally, to find the standard deviation, we'll take the square root of that number. $√2.23=1.4933184523$ But that's not the end. We also need to calculate the variance between sample groups, if we have more than one sample group. In our case, let's say that we did a second experiment where we didn't add fertilizer so we could see what the growth looked like on its own, and these were our results: Plant Growth (inches) 1 1 2 1 3 2 4 1 5 3 6 1 7 1 8 2 9 1 10 1 So let's run through the standard deviation calculation again. #1: Average Data $1 + 1 + 2+ 1 + 3 + 1 + 1 + 2 + 1 + 1 = 14$ $14/10 = 1.4$ #2: Subtract each sample from the average $(x_i – Â µ)$. $0.4 + 0.4 + (-0.4) + 0.4 + (-1.6) + 0.4 + 0.4 + (-0.4) + 0.4 + 0.4 = 0.4$ #3: Divide the last number by the total sample number, N, minus 1. $0.4/9=0.0444$ #4: Take the square root of the previous number. $√0.0444 = 0.2107130751$ Step 7: Run Standard Error Formula Okay, now we have our two standard deviations (one for the group with fertilizer, one for the group without). Next, we need to run through the standard error formula, which is: $$s_d = √((s_1/N_1) + (s_2/N_2))$$ In this equation: $s_d$ is the standard error $s_1$ is the standard deviation of group one $N_1$ is the sample size of group one $s_2$ is the standard deviation of group two $N_2$ is the sample size of group two So let's work through this. First, let's figure out $s_1/N_1$. With our numbers, that becomes $1.4933184523/10$, or 0.14933184523. Next, let's do $s_2/N_2$. With our numbers, that becomes $0.2107130751/10$, or 0.02107130751. Next, we need to add those two numbers together. $0.14933184523 + 0.02107130751 = 0.17040315274$ And finally, we'll take the square root: $√0.17040315274 = 0.41279916756$ So our standard error $s_d$, is 0.41279916756. Step 8: Find t-Score But we're still not done! Now you're probably seeing why most people use a calculator for this. Next up: t-score. Your t-score is what allows you to compare your data to other data, which tells you the probability of the two groups being significantly different. The formula for t-score is $$t = (Â µ_1 – Â µ_2)/s_d$$ where: $t$ is the t-score $Â µ_1$ is the average of group one $Â µ_2$ is the average of group two $s_d$ is the standard error So for our numbers, this equation would look like: $t = (3.3 - 1.4)/0.41279916756$ $t = 4.60272246001$ Step 9: Find Degrees of Freedom We're almost there! Next, we'll find our degrees of freedom ($df$), which tells you how many values in a calculation can vary acceptably. To calculate this, we add the number of samples in each group and subtract two. In our case, that looks like this: $$(10 + 10) - 2 = 18$$ Step 10: Use a T-Table to Find Statistical Significance And now we'll use a t-table to figure out whether our conclusions are significant. To use the t-table, we first look on the left-hand side for our $df$, which in this case is 18. Next, scan along that row of variances until you find ours, which we'll round to 4.603. Whoa! We're off the chart! Scan upward until you see the p-values at the top of the chart and you'll find that our p-value is something smaller than 0.0005, which is well below our significance level. So is our study on whether our fertilizer makes plants grow taller valid? The final stage of determining statistical significance is comparing your p-value to your alpha. In this case, our alpha is 0.05, and our p-value is well below 0.05. Since one of the methods of determining statistical significance is to demonstrate that your p-value is less than your alpha level, we've succeeded! The data seems to suggest that our fertilizer does make plants grow, and with a p-value of 0.0005 at a significance level of 0.05, it's definitely significant! Now, if we're doing a rigorous study, we should test again on a larger scale to verify that the results can be replicated and that there weren't any other variables at work to make the plants taller. Tools to Use For Statistical Significance Calculators make calculating statistical significance a lot easier. Most people will do their calculations this way instead of by hand, as doing them without tools is more likely to introduce errors in an already sensitive process. To get you started, here are some calculators you can use to make your work simpler: How to Calculate T-Score on a TI-83 Find Sample Size and Confidence Interval T-Test Calculator T-Test Formula for Excel Find P-Value with Excel What's Next? Need to brush up on AP Stats? These free AP Statistics practice tests are exactly what you need! If you're struggling with statistics on the SAT Math section, check out this guide to strategies for mean, median, and mode! This formula sheet for AP Statistics covers all the formulas you'll need to know for a great score on your AP test!

Protagoras' Denial Essay Example | Topics and Well Written Essays - 250 words

Protagoras' Denial - Essay Example Lee noted that Aristotle criticized that this is where the principle of non-contradiction has been used as a critical accentuation to what Protagoras imposed (57). This could be due to the observation of Aristotle that the good and bad virtues, justice and injustices of Protagoras were found to be so much relative that it would already make the learners wonder which sides could be considered as true or false. Protagoras, indeed, has a unique way of teaching his own philosophy. However, his study could have been criticized because of time before where access of information is not the same with the modern technology. This would mean that philosophers before would depend on their insights and elaborative knowledge based on experience and observational skills. With this, Protagoras could be considered as intellectually smart because his assumptions that were previously criticized are now orthodoxically used as means of how people should be virtually wise in terms of knowing how to listen and accept

Walmart. Final project Lab Report Example | Topics and Well Written Essays - 1250 words

Walmart. Final project - Lab Report Example SWOT analysis refers to the evaluation of an organization strengths, weaknesses, opportunities, and threats. A SWOT analysis offers an insight into an organization management strategy and the potential for success. Wal-Mart is an international company that provides home-based products at affordable prices. The company utilizes its strength in each of the market distributed worldwide, to meet the demands of their international and regional consumers. This paper seeks to provide a strategic insight of the company and a detailed SWOT analysis. Wal-Mart is a large wholesale distributor in the world that can afford modern construction technologies. For instance, during the year 2011, the company was ranked position one by Fortune 500 (Morse & Glassman, 30-40). Its operations are distributed worldwide and there is no worthy rival. Owing to its large influence on the market, Wal-Mart has the potential to replicate its best architectural techniques in all its stalls across the world (Roberts & Berg, 40). Wal-Mart uses variety of construction materials such as red bricks, steel-iron alloys, and coagulated tiles. In addition, it can suit its construction model with its retail products that cover cuts across different categories including apparels, domestic wares, and grocery. Wal-Mart’s dominant position allows it to benefit from high sales volume. In general, Wal-Mart’s strength includes international operations, scale of operations, wide range of products and cost leadership strategy (Hicks, 20-25). Wal-Mart is large supplier of domestic products and operates vast centers that require large construction space. This acts as a disadvantage as the company limit cannot expand beyond urban areas due to space. Research has shown that Wal-Mart has experienced loss in its store sales for the last eight years due to limited space (Kneer, 24). As such, Wal-Mart is required to develop new stores to accommodate fully its strengths concentrated in urban areas. This is

Influence of the Modernist Ideal City

Influence of the Modernist Ideal City The influence of the modernist ideal city, on urban design and master planning Introduction This essay will focus on the influence of Modernist Ideal City movement. At first showing that understanding of social, political and economic background is necessary, along with contemporary technological influences. Secondly, the purpose, principles and results of the movement will be illustrated. Then using the case study-Brasilia demonstrates the influence of the modernist ideal city. Finally, a critical view of historic and future of the movement will be provided. Background At the age of Early 20th, in most of western countries, the industrial revolution was dropping towards the end. With the development of technology and the increase of the social wealth, the population of 1800 1880 1910 Pars 647,000 2,200,000 3,000,000 London 800,000 3,800,000 7,200,000 Berlin 182,000 1,840,000 3,400,000 New York 60,000 2,800,000 4,500,000 Europe dramatically raised (figure 1). The contemporary cities could not stand the pressure of the population boom. A series of problem appeared, chaos, overcrowding, low efficiency, serious pollution, high density, narrow streets and lack of sunlight all threaten peoples life quality especially for lower class people. (Greed 1996, 70) Social conflict liked a time bomb hanging on the sky of the city. As Le Corbusier saidif we cannot suit to the situation of the new trend, the cities cannot meet the requirements of modern lifestyle (Corbusier 1987, 84). At this time, after the World War 1 (WW1), the Europe returned to peace. A great rebuilding process began buildings, and whole cities needed to be rebuilt. At this time, technology was vital to speed up this usually slow process. Express train and car speeded up the travel; telephone and radio reduce the commuting time and skyscrapers increased the city density. On the other hand, the modernist principles already were put forward. Both the real situation backed up and influenced by the theory basic gave people the opportunity to rethink the city of tomorrow. Finally,urban utopias emerged as the time requires, and Le Corbusier’s modernist ideal city is one of the most crucial parts (Hall 2011, 11-18, 28). The form of the modernist ideal city aimed to improve health of citizens, reduce commuting times, create more open space and get more sunlight, this way le Corbusier wanted to solve the social conflict (Greed 1996, 101-102). In 1914, Le Corbusier stated the Dom-ino House (figure 2). It is made of reinforce concrete and it reject the traditional load bearing wall. The frame structure frees the internal space which can be divided freely. low-cost, convenient, uniformity and standardisation all those figures show why He believed the Dom-ino system can meet the people’s requirements after WW1 (Frampton 2001, 21-22). In 1922, Le Corbusier published a blueprint of a contemporary city with 3,000,000 residents. And it was the first time for Le Corbusier to describe a whole ideal city. He searched a pure mechanism order. In his eyes, humanity would lost from chaos but revive from the pure order. In order to express the order, pure forms was used by le Corbusier. All the elements of city such as houses, roads, industries, offices even human were classified by function (Corbusier 1987, 15). The whole city was planned by clear hierarchy of class; people were divided into three parts, citizens, suburban dwellers and the mixed sort people. Roughly 400,000 to 600,000 citizens who were treated as urban elites lived in the 24 60-storey skyscrapers in the city centre. In Corbusier’s opinion these skyscrapers were vertical streets, which contain shops, hotels, etc. Furthermore, they only covered about 15% area of the entire city, which dramatically increase the density. At the same time, considered the environment pollution and human needs, the rest 85% of ground should be free for green lands. The working class (about 2,000,000) was planned to live in the garden city, which was influence by the garden city movement (Corbusier 1987, 163-176). On the other hand, fast traffic played an important role in the city. He (Corbusier 1987, 191) pointed out â€Å"that the city which can achieve speed will achieves success-and this is an obvious truth.† The whole city was connected by transportation system. And planner used symmetrical grid of streets to replace traditional â€Å"corridor street†. Two great arterial highways ran north and south, and east and west intersecting at the exact centre of the city (Corbusier 1987, 163-176). In general, the whole city worked as a huge machine. In 1932, Le Corbusier showed a more daring blueprint-The Radiant City that was more authoritarian and more libertarian than the Plan Voisin. The principle of design is existenzminimum (Corbusier 1976, 6-7). Every building would be strictly designed on the human scale. Furthermore, the radiant city has no class divisions. All of the people live in high-rise apartment blocks â€Å"Unità ©s†. Each block intended for 2,700 people and included individual service and public facilities such as shops, restaurant, swimming pools and gymnasiums (Corbusier 1967, 162). In order to avoid waste of space, the size of the apartment was decided by the family’s needs not class. Buildings raised on pilotis free the ground land and would be benefit to fast traffic and green land. Symmetrical grid of highway connected the whole anti-street city (Frampton 2001, 51). Same as the Dom-ino house, the radiant city from a single room to an entire city applies low cost and mass production techniqu es. In addition, these blocks only covered about 12% land. The rest area 100% ground area plus 12% top area of buildings were made up the green city. South facing glass wall, roof terraces and big open space made the city more radiant (Corbusier 1976, 44, 163). At the following years, Four Unità © d’Habitations were built in UK including Park Hill, Sheffield, Alton West, Roehampton, Barbican, London, and South Acton Estate, London. In general, the modernist ideal city could be described an order city; a functional city; a machine city; a high-rise city; a green city; a radiant city and a fast-traffic city. Case study There is no other cities can completely show Corbusier’s ideas liked Brasilia, although he wasn’t involved in the design (Hall 2002, 230).From 1956 to 1960, in order to narrow the gap between rich and poor and strengthen the development of interior area, a new capital-Brasilia that was designed by Lucio Costa and Oscar Niemeyerhas been built. (Epstein 1973, 9) Brasilia as a totally new capital, without historical context, embodies a symbol of the modern movement (Hall 2002, 232). It means that costa got the best chance to seek to a pure order liked Corbusier. This order can be shown that the whole plan was axisymmetric and was divided different area by its function and residential area, working area and leisure area was linked by fast traffic (Evenson 1973, 146-153). In details dragonfly, bird, airplane, body and fuselage always are used to describe and plan the Brasilia. Roughly 10 kilometres monumental axis link east and west. From east to west, respectively, were gov ernmental buildings, uniform office blocks and train station. The uniformrectangle residential districtthat included shops, apartments etc. were located at both sides of the wind shape north-south axis. And the connection of the two axes was called rodoviaria that was designed as a centre of commerce, culture and entertainment. In addition, artificial lakes were surrounded north, east and south, zoo and serial small factories were near to train station (Issitt 2014). In general we can say, under the influence of modernist ideal city, Brasilia is an order, functional, green jet very motorised city. However,same as the theory of modernist ideal city, critics of Brasilia never stop from the first day of it built. With the development of city, a great deal of problems emerges. In fact, people are not willing to live in Brasilia. In 2000, the population of Brasilia was above stunning 2,000,000 citizens which was 4 times more than origin plan. Yet about 75% lived in outside of planning area, which, implement low density of population. Because of Brasilia being so motorised, and extensively large, it is almost impossible to travel the city by foot. In addition due to the rigid functional zone, human behaviour was strongly ruled (Evenson 1973, 118). Conclusion In my opinion, the modernist ideal city movement was the product of era. And the design of Brasilia was a great experiment, which successfully proved that the theory of modernist ideal city cannot totally suit to a real world. The fact proved that the modernist ideal city is good-looking but not practical. Personally, Le Corbusier was contradictory, he rationally planned the whole city but perceptually wanted to destroy the original city; he rationally ruled behaviours of human but perceptually thought that everyone has the same requirements; he rationally treated house as a machine but perceptually treated human as a machine too. Furthermore, the most controversial point is that the modernist ideal city is an autocratic city that does not leave any space to other possibilities. It is a unique answer for le Corbusier (Marshall 2009, 38). However, no one can ignore the worldwide influence of the movement especially in post-war time, we can still find the shadow of Le Corbusier in many modern cities such as London, Canberra, shanghai, etc. With time goes by, various movements of urban deign emerged. People, nowadays, reach a consensus that we need to find a balance point between economy, environment and social well-being and build a sustainable city. References Clara H. Greed, Introducing town planning (Harlow: Longman, 1996), 70. David G. Epstein, Brasilia, Plan and Reality (Berkeley: University of California Press, 1973), 9. Kenneth Frampton, Le Corbusier (London: Thames Hudson, 2001), 21-22, 51. Le Corbusier, The city of to-morrow and its planning (New York: Dover, 1987), 15, 84, 163-176, 191. Le Corbusier, The radiant city: elements of a doctrine of urbanism to be used as the basis of our machine-age civilization (New York: Orion Press, 1967), 6-7, 44, 162-163. Micah L. Issitt, â€Å"Brasà ­lia, Brazil,† Salem Press Encyclopedia, January, 2014. Norma Evenson, Two Brazilian capitals: architecture and urbanism in Rio de Janeiro and Brasà ­lia (New Haven: Yale University Press, 1973), 118, 146-153. Peter Hall, Cities of tomorrow: an intellectual history of urban planning and design in the twentieth century (Oxford: Blackwell Publishers, 2002), 230, 232. Peter Hall, Urban and regional planning (London: Routledge, 2011), 11-18, 28. Stephen Marshall, Cities, Design Evolution (Routledge, 2009), 38.

My Community Service Award Essay

Every individual desires to be recognized. It is a nice feeling that people around you are happy to what you are doing and even give a recognition that will definitely make the awardee motivated to do better in every endeavor that he is going to do in the future. This kind of once in a lifetime recognition has come to my life unexpectedly. It is truly a great experience that cannot be bought by money. This event is so close to my heart that until I become old, I will not stop telling my grandkids about the honor which the community coalition has given me. Each year, community coalition called Building a Better Bensalem Together has a luncheon and I was given Bensalem’s community service award of the year in 2007. My heart pounds very fast as I receive the award and I do not know at that time where to put the happiness that I feel. It is indeed a surprise because I really lend my hand without any expectations to be recognized because all I want to do is to help. The award I received was from the Mayor of my township Bensalem, PA. As a recognized awardee, it makes me really feel fulfilled and happy. I am glad that people see my worth as a volunteer in our community coalition. Although I have experienced tough times during the service that makes me down sometimes yet it paves away when I see everything is in place. Moreover, as a young individual, I tend to see myself helping my community. In my point of view, lending a hand is a good act of love to others. It is a great feeling that you make other people happy. I never withhold myself in serving my community because for me it is a privilege that not all people are given the chance to do so. In addition, I have been volunteering for our community coalition called Building a Better Bensalem Together for 7 years. Throughout those years of serving, I learned to communicate and deal with various kinds of people from different walks of life. Although at the start it was a bit difficult because I have to adjust with different personalities and characters yet these make me more dedicated to learn the crop. I started to love this kind of service of our community coalition and never tired of doing good to others. Thus, this opportunity developed my patience and concern for the betterment of my community. Another thing I learned from volunteering is that, it develops my leadership as an individual. When I worked with the community coalition, I have the chance to make decisions for the betterment of the community and conducted some activities and projects that were also successful and have contributed to the progress and development of my community. In addition, as I search myself, I discovered that my growth in leadership have improved my common sense especially when making decisions for the community. Well, many people might laugh of what I say but that is the fact. Even though how good a person is in leading people but without common sense in performing the activities, it is still nothing. Common sense is very important in leading people because it is a practical intelligence and tact in behavior. Common sense is a product of individual experience gained through contact with practical problems of life and through lessons derived from success and failure. Furthermore, every time I deal with people, I always remind myself to be kind and polite and take things easy. If ever we encounter some dilemmas in the community coalition, I always welcome suggestions from my co-workers and then present my options of what to do however I never impose my ideas to them because I want to see one by one working hand-in-hand for the benefit of everyone. In conclusion, I would I say that giving your time and effort in helping others is a noble and right thing to do. I am happy that I have undergone this kind of experience because it makes me a better person and a chance to experience of receiving an award from honorable Mayor of PA. Everyone dreams of it I guess and I am fortunate and blessed enough to be chosen as one.

Kathy Gill - ThoughtCo