Give the Kid a Number by R. J. Graham - Article Example

Give the Kid a Number Briefly summarize the main points of the “Give the Kid a Number” essay.  Perversion of data, that’s the best way to describe it. People blindly believe that data is the king. After all, it is just a collection of facts and figures; it is supposed to be objective and without bias, nothing of the aforementioned could be any further from the truth. Robert Graham (1982) shows in his essay that there are four (flawed) assumptions that people make when they view any data set. These assumptions lead them to believe that if it’s a data set then it must be true, unbiased without any intentional or unintentional influence. a) Data production is not effected by organizational politics. b) People will do what they say for the reasons they say it. c) People behave according to the rules. d) Data reflects a constant reality (Graham 40). However, it is not impossible to break free from these flawed assumptions. With the right mindset while analyzing the data can make the difference between choosing two opposite arguments. For instance, knowing the intent of the people that produced the data will keep the reader objective about the so called facts (Graham 43). This approach might easily save the readers from falling victim to data mining or cherry picking. Having a little sense of accounting, finance, business and corporate laws can equip the readers with the right tools before making a decision of investing in the firm. 2) Briefly summarize the main points of the newspaper or magazine article in a few sentences, with particular emphasis on its use of data, and the conclusions, decisions, etc., based on the data. The article in The Harvard Crimson, Death of Data by Raul Quintana declares that common populace lives in “post-truth” age of politics. This news article is in reference to the upcoming US presidential elections. It has become very easy to distort the facts statistically, as putting the stamp of individual belief on the data doesn’t rid it off the scent of spinning the data (Quintana). Representative Paul Ryan claims that Barrack Obama has doubled the size of the government, when in fact there is no data-matrix to confirm this. Institutes like Office of Management and Budget and Congressional Budget Office, and even Academia are facing criticism of being biased in their data projections or liberal bias. Instead of forming policies based on numerical facts, politicians formulate policies based on pre-existing ideology. What happens is that policies are made before objectively analyzing the data, and then to support the decision, the data is beaten to conform to the policy. 3) How were the data (mis-) used in the article?  Misinformation and inflammatory rhetoric are the predominant weapons used in twisting the data, and this is being done of regular basis. Data is no longer an objective input in a debate (Quintana). Showing one side of the picture is the most common tool for formulating policies that are based on an ideology. Politicization of data is one of the biggest challenges that the world (victims of policies/general public) is facing. 4) If you were to advise the people involved on better ways of using data in the situation, what would you recommend?  I would recommend the people to read between the lines. The best way to not get carried away with the ‘political black magic’ is to read more and watch less television. When people watch television, it gets so much easier for the media to influence viewers with data distortion. A whole think tank sits behind those cameras to strategize the data. For instance, even if unbiased data is posted regarding unemployment or massive corporate corruption, merely not highlighting it enough and creating another ‘flashing news’ would be more than enough to misdirect the viewers and throw them off the track. As they say, perception is reality, and media is a master of distorting perception. Works Cited Graham, R. J. "Give the Kid a Number": An Essay on the Folly and Consequences of Trusting Your Data." Interfaces 12.3 (1982): 40-44. Print. Quintana, Raul P. "The Death of Data." The Harvard Crimson. n.p., 5 Sept. 2012. Web. 08 Sept. 2012. . Copy of the News Article The Death of Data By RAUL P. QUINTANA Published: Wednesday, September 05, 2012 In the midst of convention season, it has become clear that both parties live in a world that none of us can truly recognize. Columnist James Fallows, a former Crimson editor, claims we live in the “post-truth” age of politics. While upsetting, it is entirely unsurprising that super PACs blatantly disregarded the facts, since their favored candidates can deny any involvement. Yet the parties and even the presidential and vice-presidential candidates themselves have started to publically lie without regard to our political discourse or society as a whole. Granted, politicians’ distortion of reality is not a new trend. But the de-regulation of campaign finance, escalation of hyper-partisanship, and insatiable public appetite for inflammatory rhetoric have all contributed to an unprecedented disregard for the truth. Besides honesty and integrity, the irrelevance of truth has particularly severe implications for public policy debates. Most statistics professors and frustrated Statistics 104 students will tell you that the interpretation of statistical data is an inherently subjective science. Transformations and reinterpretations can create different results from the same data set. Statistics thus becomes easy to twist in accordance with individual beliefs. Rather than deriving public policy from numerical facts, we have started to derive public policy from pre-existing ideological arguments. The proliferation of think tanks, policy organizations, and other quantitative-heavy institutions has given rise to a torrent of new research beholden to a specific ideology. Data simply adhere to an existing political narrative rather than providing objective evaluations. As a result, hyper-partisanship has flourished at the cost of substantive policy debate. We now have partisan conceptions of reality that differ on their most fundamental assertions about the world. For example, Representative Paul Ryan has recently declared that Barack Obama has doubled the size of government. In reality, no reliable data metric shows a doubling of government under President Obama, or even an increase of more than 10 percent. Debate, the basis of American governance, can only occur through fundamental agreements about political realities. To substantively debate healthcare, for example, legislators must agree that there is a need for healthcare. However, all of our recent political debates, from the debt ceiling to healthcare reform, have shown two parties so removed from each other that they do not even appear to be debating the same issues. In theory, policy differences result from differing beliefs on how the government should address a particular issue. It results from a difference of interpretation rather than a difference of construction. Statistics frame these debates by providing the foundation through which legislators can discuss potential solutions. Yet, data are no longer neutral. Even impartial offices like the Office of Management and Budget and the Congressional Budget Office have come under fire for these underlying tendencies. Academia, one of the few institutions with a mission that explicitly pursues objective truth, constantly faces criticisms of liberal bias. These destructive accusations have undermined the credibility of statistics as a tool for public policy. Actual policy implications become lost amidst inflammatory rhetoric and misinformation. The entire purpose of these organizations disappears, and data no longer aid debate. We have entered the age of post-modernity in American politics. Established truths no longer appear relevant. In the face of new evidence, we plug our ears and start shouting accusations in order to drown out the cognitive dissonance. In this way, we have entered a world of multiple political realities, fortified by the politicization of statistics. To refocus the political debate and create a functioning government, we must re-align these realities and, in doing so, understand the credibility of contrary data.   Raul P. Quintana ’14, a Crimson editorial writer, is a history concentrator in Quincy House. Web URL: http://www.thecrimson.com/article/2012/9/5/harvard-data-politics/ Read More