...The Constant Gardener INTRODUCTION Why Fernando Meirelles? Fernando Meirelles’ film is one of a recent batch of Hollywood films dealing with serious issues. In this case the film is a conspiracy thriller, which looks at the involvement of a large pharmaceutical company in testing drugs in Africa. That said, the film is much more, combining a love story, a quest for revenge and expressing real anger about the West’s apparently unchecked exploitation of ordinary African people. The Constant Gardener is an adaptation of a novel by the British writer John le Carré, best known for his tales of spies and Cold War intrigue. Fernando Meirelles seemed an odd choice for director, because of his Brazilian background and the seemingly huge difference between this film and his first feature, the explosive story of a Rio favela, City of God (2003). www.filmeducation.org 1 Mike Newell was the first choice for director, but had already committed himself to the new Harry Potter film, but Meirelles was very interested in the project. He told The Independent, ‘The chance to take on the pharmaceutical industry was one of the three elements that made me want to direct The Constant Gardener, as was the chance to shoot in Kenya. Also, it’s a very original love story about a man who marries a much younger woman who is very different from him, and it’s only after she dies that he truly falls in love with her.’ Meirelles’ Brazilian background gave him a source of empathy with the poverty in...
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...The film ‘The Constant Gardener’ directed by Fernando Meirelles, I agree, is used as a means to critique our society. The character of Justin Quayle, a British High Commission Diplomat, is used by the director to reflect society. We see this in the beginning of the film where his ignorance leads to a false perception of reality, which highlights the 2 major themes in the film of Truth and Perception and Guilt and Atonement. Justin uses gardening as a means to feed this ignorance, just as society itself uses work, family and other matters to hide from the harsh reality. But as his wife Tessa dies under unusual circumstances it leads Justin into the real world, where the truth can no longer be covered up and he must follow the road to atonement. In an early scene of the film, Justin, like society is consciously removed from reality. Before this scene we are shown wide and establishing shots of Lake Tuitakana in Africa where we see mars-like images of the red sands and bright blue water streaked across the landscape. This scene then fades into the British High Commission Embassy, where there is a complete contrast in colours. We instead get a Wide Shot of the building with dull colours of grey and dark greens and blues. This shot also shows Justin “skiving” as he waters his plants. Although he is in charge of Aid distribution in Kenya, he is choosing to remain in his own perfect world “a world with no weeds”, where he stays in the office and has never once gone outside of the British...
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...The fragmented style of "The Constant Gardener" is the best way to tell this story. It is not a story told where the beginning starts with a mystery and ending at truth, but a circling around an elusive conspiracy. In a remote area of Northern Kenya, the passionate Tessa Quayle, played by Rachel Weisz, has been found brutally murdered. Tessa's travelling companion, a local doctor, appears to have fled the scene and the evidence points to a crime of passion. Members of the British High Commission assume that Tessa's widowed husband, Justin Quayle (Ralph Fiennes), will leave the matter to their discretion. Determined to clear his wife's name and "finish what she started", Justin embarks on a crash course to learn about the pharmaceutical industry, whose crimes Tessa was on the verge of uncovering. The film involves drug companies who test their products on the poor of the Third World and are willing to accept the deaths that may occur because, after all, those people don't count. Why not you might ask, no one is there to count them. Film editing could be called 'film construction' and has been regarded by many as the 'invisible' art behind some of the greatest motion picture sequences of all time. Film editing is a skilled art - the selection and integration of a sequence of shots taken from thousands of feet of film to establish a structure, tempo, mood, or style. Editing a films emotional intention of a scene is not realized: you don't laugh at what was intended to be funny...
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...self-preservation. This often results in the suffering of those carrying out their quest for justice. This idea, and the concept that the miscarriage of justice can have long lasting and far reaching effects which can never be fully redressed are thoroughly explored in both the film The Constant Gardener and Ian McEwan’s Atonement, through a range of literary devices and film techniques we can fully understand the impacts of miscarriage of justice. When those that are intent on preventing the course of justice to further themselves, whether financially or otherwise, they may become unrestrained by moral boundaries, which may allow them the mental capability to disregard the wellbeing of other humans. This disregard for welfare of such a vast number of individuals is explored through both texts allowing us to see the way in which the attainment of justice goes hand in hand with human suffering and sacrifice, as those that are determined to subvert justice can be unscrupulous in their attempts so as to further themselves, or to remove themselves from suspicion for their misdeeds. This can lead to extreme maltreatment of individuals that are trying to uphold justice. In the film The Constant Gardener we can see how those attempting to subvert justice can resort to mass manipulation, and violence against those standing in their way. The manipulation, forcing...
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...The Constant Gardener In John le Carré’s novel “The Constant Gardener” capitalism is brought to the table. A huge pharmaceutical company cares more about money and profit for themselves, than they do about human lives in Africa when they are testing a new drug for tuberculosis with deadly side effects. The activist Tessa, who is married to a British diplomat, is digging into it but it unfortunately leads to her own death. Her husband Justin who has always been avoiding conflicts and tried not to get involved in anything controversial, is now taking over what Tessa started. This all happens in the third world, and this novel takes place in Kenya. Since the drug business is so huge and the people there are so desperate, they test their drugs on them. And for the indigenous people to be able to get any medications they have to be willing to volunteer to try out the new drug, which mostly ended in their own death instead of getting rid of their disease. The long fight to get to the bottom of this unfortunate case against the pharma-giant and their “corporate greed” also ended with Justin’s own death, so we can only imagine how much power the drug companies have. Think slavery is a thing of the past? Think again In the article “Think slavery is a thing of the past? Think again” the writer Emily Dugan presents different stories about agricultural work, sex trafficking, child smuggling, drug trade and domestic slavery. There are so many people all over who want to start a...
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...value 1.8957 we on average make mistake about 0.4624 When we calculate our coefficient 3 at value 35.9569 we on average make mistake about 2.881 E) Check precision of estimate of S and L Si Standard Error Si= | |* 100 = | | I Coefficient 1.350 Ss= * 100 = 10.543 % 12.8052 2.881 SL= * 100 = 8.012 % 35.9569 F) Interpret and comment R^2 _ K (no of independent ) 2 2 R = R - * (1- R2) N –(K+1) (no of observation) _ 3 2 R = 0.964 - * (1- 0.964) = 0.959 => 95.9 % 25-3-1 R2 = 0.964 0.964 > 0.7 is good model It means 96% of dependent variable is explained by independent variable and is good model R2 > 0.7 is good model R2 < 0.5 is bad model 0.5 < R2 < 0.7 is in average G) Test significance of L,D and of constant term H0: 1=0 if parameters 1 is equal to zero variable j is not significant in the...
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...to filter the data to get more accurate results. Graph 1 contains the data between the years 1974 and 1992. Graph 2 Contains the data between the years 1992 and 2012. Graph 1 Filtered This scatter plot shows the amount of beer sold per capita between the years 1975 and 1992. The Independent variable “Year” is graphed on the x-axis and represents the predictor. The scatter plot has a negative, non-linear relationship. It has a strong relationship, with constant scatter. There seems to be a trend of beer sales declining per capita at a rate of 1.23 litres per year. Graph 2 Filtered: This scatter plot shows the amount of beer sold per capita between the years 1992 and 2012. The Independent Variable “Year” represents the predictor and is graphed on the x-axis. The Dependent Variable “Beer Sales Per Capita” is graphed on the y-axis and represents the response. The scatter plot has a non-linear trend, with a negative association that shows as one variable gets smaller, so does the other. It has a weak relationship with constant scatter. This graph shows that there is a trend of Beer Sales Per Capita declining at a rate of 0.31 litres per year. Part 2: The independent variable is “Year” because it does not rely on any other data and the dependent variable is the population aged 20-24 as a percent because it relies on the year. The relationship shown in this scatter plot is a strong, linear correlation...
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...QMS 442- Research Article The Starbucks effect on the Toronto Housing Market Chandini Algoo 500571436 March 31, 2015 Abstract: This study is looking at the relationship between the sales price in Downtown Toronto and the locations of Starbucks. The models being used in this study is first, second and third order models. The main findings of this study conclude that there is strong correlation between the two variables. However, sales price do depend on the independent variables of size, number of rooms and parking space. Introduction: The Starbucks effect is known as a phenomenon that has changed the face of coffee in the recent decade (Vishwanath & Harding, 2000). The idea is to rebrand the coffee by selling it at a premium level to not only promote a beverage, but also a lifestyle(Vishwanath & Harding, 2000). Starbucks has rebranded their company to model a high-class lifestyle. With the Toronto housing market on a rise, this analysis is to compute the relationship between Toronto condos in relation to the distance of a Starbucks location. The types of models being used are the hypothesized regression models that take the dependent variable and comparing them to our four independent variables. Data Collection: The data collected was used from the REMAX.CA website, this is because it was resourceful in finding precise sizes, locations and market prices of the condominiums in 2015. The limitations of collecting this information was the amount...
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...Conjoint Analysis 1. Explain the interpretation of the following tables -> (a) Utilities table (highest and lowest utility for each attribute) The preference of Package B* is highest (1.867 Utility value) among all other options for the Package and it is lowest in the case of A* (-2.233 utility value). The preference for K2 brand is highest (0.367 Utility value) and the Glory brand has the lowest value (-0.350 Utility value). The preference for the Price level of $1.19 is the highest (-1.108 Utility value) among all other price options and the price level 1.59 has the lowest value (-3.325 utility value). The preference of Seal to yes is more (4.0 utility value) and the Preference for money as yes is more (2.5 utility value). (b) Importance Values It gives us the relative importance of the factors in percentage. Like for Package the importance value is 35.6%, and is the most important factor. Similarly, Price has the importance of 29.5%, Brand has the importance of 15%, Seal has the importance of 11.7% and money is the least important factor with importance of 8.8% only. (Values are the average importance factor) (c) Coefficients The Linear Regression B Coefficient estimate for Price comes out to be -1.108, Seal comes out to be 2.000 and money comes out to be 1.250, when there coefficients are multiplied with value associated with different options of factors this gives us the utility for the same. When factor value for seal as yes (2) is multiplied...
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...Institute of Management, Christ University Kengeri Campus, Bangalore. Review On Cluster Analysis Submitted for the partial fulfillment of process related to Continuous Internal Assessment 1 In Marketing Analytics [MBA - III Trimester (MBA 322)] Submitted By P.Akhilesh 1420419 Cluster analysis? The Cluster Analysis is an explorative analysis that tries to identify structures within the data. Cluster analysis is also called segmentation analysis .It is used to identify groups of cases if the alignment is not previously known. Because it is explorative it does make any distinction between dependent and independent variables. The different cluster analysis methods that SPSS offers can handle binary, nominal, ordinal, and scale (interval or ratio) data. Different types of cluster analysis include: * Hierarchical Analysis * Two step Cluster * K-means cluster From the given data set: * We have both continuous and categorical variables * Continuous variables include: Attitude towards Nike, Awareness towards Nike, Preference for Nike Loyalty for Nike and purchase intention for Nike * Categorical variables: Sex, Hierarchical Cluster Analysis: Ward method: * Here it is clearly mentioned that from cluster one 15 respondents are available , from cluster two 15 respondents are available and from cluster three 10 respondents are available * We have 5 missing respondents who had not respondent or the...
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... Other factors such as position, method of loading, the material of which the beam is made will also influence the deflection. If we wish to find the relationship between y and one of the possible variables it is necessary to keep all the other possible variables constant throughout the experiment. 1. Length calculation In this experiment the same beam is used throughout and the centrally applied point load is kept constant. Thus keeping all possible variables other than the deflection y and the span L constant we may investigate the relationship between y and L. Let y[pic]Ln where n is to be found Then y = k•Ln where k is a constant Taking logarithms: log y = n log L + log k which is in the straight line form (y = mx + C). Thus plotting logy against log L will give a straight-line graph of slope “n” and “k” may be determined. 2. Width calculation In this experiment beams of the same material but of different width are used. The span and loading are kept the same for each beam. Hence keeping all possible variables other than width and deflection constant the relationship between y and b is determined. Let y[pic]bn where n is to be found. Then y = k•bn where k is a constant. Taking logarithms, log y = n log b + log k which is in the straight line from : (y = mx + C). Thus plotting logy against log b...
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...choose the variable “% of Firms expressing that a typical Firm reports less than 100 % of sales” that may act as a proxy for this inclination as the dependent variable. Several other variables are chosen to explain this dependent variable. These explanatory variables are: the firm’s age, ownership (domestic/private), exporter (whether it exports its product or not), % of firms using the web to communicate with clients/suppliers, % of firms using email to communicate with clients/suppliers, average number of unskilled production workers, average number of temporary workers, % of firms using technology licensed from foreign companies, % of firms expected to give gifts to secure a government contract, and the size of the firm. In addition, a constant is considered in the regression. After regressing the dependent variable on the above independent variables the following results have been attained: (will insert equation and table of coefficients) When the firms’ age is considered, a negative relationship can be deducted between it and the dependent variable illustrated by the negative coefficient -0.070. As the firm ages, it is expected to report its sales more accurately. The ages of the firms selected ranged from 2 years to 146 while the average age of these firms was 27.61. This may seem unsurprising as firms with a long history are not expected to underreport their output while new upcoming firms may be more willing to do that. Exporting firms (firms who are expected to...
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...LAB 3.1 Variable Name | Problem (Y or N) | If Yes, what’s wrong? | Declare Real creditsTaken | No | | Declare Int creditsLeft | Yes | The variable should be declared as Real so it can indicate decimal values | Declare Real studentName | Yes | The variable should be a String to store text | Constant Real creditsNeeded = 90 | No | | Step 2: The calculation should be “creditsLeft = creditsNeeded – creditsTaken” Step 3: “The student’s name is Nolan Owens” Step 4: “The Network Systems Administration degree is awarded after 90 credits and Nolan Owens has 70 left to take before graduation.” Step 5: 1. //Provide documentation on line 2 of what this program does 2. //This program calculates how many credits a student still needs to graduate the NSA program 3. //Declare variables on lines 4, 5, 6, and 7 4. Declare Real creditsTaken = 0 5. Declare Real creditsLeft = 0 6. Declare String studentName = “NO VALUE” 7. Declare Constant Real creditsNeeded = 90 8. //Ask for user input of studentName and creditsTaken on line 9 - 12. 9. Display “What is the student’s name?” 10. User input = studentName 11. Display “How many credits does the student have?” 12. User input = creditsTaken 13. //Calculate remaining credits on line 14 14. creditsLeft = creditsNeeded – creditsTaken 15. //Display student name and credits left on line 16 and 17 16. Display “The student’s name is “, studentName 17. Display “They require “, creditsLeft...
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...上海大学 20 4 ～ 2015 学年 秋季学期研究生课程考试 课程名称： Econometrics 论文题目（Title）: 研究生姓名(Name): Hoang Thi Lan Huong 学号(ID): 14760006 研究生班级： 留学生班 成 绩: 任课教师: 叶明确 评阅日期: 1. Introduction (Background and Purpose) The data use for this paper was constructed in the following way. The data are drawn from the OPE Campus Safety and Security Statistics website database to which crime statistics (as of the 2010 data collection) are submitted annually, via a web-based data collection, by all postsecondary institutions that receive Title IV funding (i.e., those that participate in federal student aid programs). This data collection is required by the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act and the Higher Education Opportunity Act. The outcome of this process was that the enrolments is not influenced significantly by the price or living conditions of the campus. When reading some articles I was personally very surprised about this since normally the living conditions should be influent more than the other factors in the enrolments. Based on this, I was very interested which other factors influence to students’ decisions. That is why I chose this dataset to analyze for the final term paper in the course of econometrics. 2. Multiple regressions 2.1 Data source The numerous data used in this paper (reference see below), consists of observations on six variables. The variables are: • enroll ...
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...Week 3 Activity—Calculate Overtime Pay ------------------------------------------------- TCO 3—Given a simple problem, design and desk-check a solution algorithm requiring a modular design that is expressed in terms of pseudocode or program notes, input-process-output (IPO) analysis, and flow chart. ------------------------------------------------- TCO 4—Given a simple problem that requires one or more decisions, create a working solution that uses decisions with logical and relational expressions. ------------------------------------------------- TCO 8—Given a more complex problem, develop a complete solution that includes a comprehensive statement of the problem, complete program design, and program documentation. ------------------------------------------------- Assignment You will need to design an application that it will prompt a user for his or her hourly pay rate, his or her hours worked, and whether he or she is single, married, divorced, or widowed. It will then calculate his or her gross and net pay. If the user works more than 40 hours, overtime is calculated at 1 ½ times the regular rate and displayed separately. If he or she is married, use a flat tax rate of 15%. If he or she is single, use 22%; if he or she is divorced, use 23%; and if he or she is widowed, use 13% (I realize that these are not very realistic). Below is a sample of what the program should do when run. (No overtime example) Enter hourly pay rate: 10.00 Enter hours worked: 35 ...
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