Comparative Analysis-Privatizing Social Security
Essay by 24 • January 1, 2011 • 1,162 Words (5 Pages) • 1,870 Views
Comparative Analysis
Social Security is an important issue to our society. During campaign years, it is always a central topic for politicians and the public. Neither side can agree on whether Social Security should be privatized. I have selected two articles that represent the different viewpoints. First, there is "Creating A Better Social Security System for America," by Daniel Mitchell. The second article is "Privatizing Social Security Is Bad, Particularly for Women," by Catherine Hill. Each author explains why Social Security should or should not be privatized.
The title is the first thing a reader sees when deciding what to read. The title of Catherine Hill's article, "Privatizing Social Security Is Bad, Particularly for Women," is a great example of an eye-catching headline. It states her point-of-view clearly. It not only draws readers in by using a negative adjective "bad," but also making women curious as to how it's particularly bad for them. However, the second article, "Creating A Better Social Security System for America," is relatively plain. The author successfully gets the article's main point across in the headline, but compared to Hill's article, it's not as engaging. A better title could be, "How To Fix a Broken System." There are eye-catching words such as "broken" in it that make me want to keep reading.
A claim is the idea the writer is trying to portray in their article. In this case, each writer's claim is why or why not privatization of Social Security would be beneficial. In Mitchell's article for privatization, his claim is, "There is no way to fix the current Social Security system, but there is a way to guarantee workers a safe and secure retirement." He makes his claim more valid by stating what should be fixed and what hasn't worked in the past. His claim was made in the article's opening paragraph, therefore it made me want to keep reading and find out what ideas he had to fix the "broken system." In the second article, the author's claim is this: "In fact, privatizing Social Security will mean less income in retirement for almost all American workers and it will be particularly damaging for women." After the article's sensational headline, I felt this was just re-stating the title. However, I am drawn to the article to learn more about how women would be "particularly damaged" by privatization. The author also left the claim at the end of her opening paragraph. It took reading several lines to get to it.
When an issue, such as Social Security, is controversial and pertains to every citizen, it needs statistics to back up the author's claim. As a reader, I feel they help validate their point-of-view and prove the author has done research on the subject. Mitchell's article, which is for privatization, has few statistics or other data. He does write that capital returns have averaged 7% over the past 70 years, which supports his claim that privatization would help workers, especially younger ones. He also cites a National Chamber Foundation study that lays out income numbers that readers can understand. But what is the National Chamber Foundation? He never says. Real-life examples are more beneficial to readers. He could use more supportive data for his paragraph about how the current system is bad for low-income Americans. As a reader, I would also have liked some information on how private savings he supported would be taxed and what effects privatization would have on older workers and those already close to retirement.
In Hill's article, she has many statistics that support each argument she makes against privatization. She gives examples of current amounts retirees receive and percentages of workers that receive them. However, she needs to cite where she got her information. She doesn't elaborate on where she read her data or who she talked to. She cites no studies, but each point is very detailed. Neither article cites expert opinions or studies. The Hill article has more numerical data than Mitchell's,
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