Data journalism: The Deadliest Jobs in America

In the Bloomberg reading The deadliest jobs in America, we learn that compensation is a huge factor in what are presumably high-risk, dangerous jobs here in America. When you look at the the various jobs and salary, it often seems like those who are at most risk, receive more compensation than those who are not regardless if they are actually hurt or not. The risk factor alongside actual fatalities that have happened in the past presumably determines the compensation. Construction workers, agricultural workers, and truck drivers do see fatalities per ever 100K but make more or the same pay rate as lodgers who are within the same status. Police officers and Fire fighters receive more of a pay rate even though their fatality to pay ratio is less than a lodgers because of their weight of risk. We can assume this is because of their official community involvement and the unknown, fatal situations they face daily. In this way, the graphical presentation is not commuting the information very well. In order to communicate this information better, the presentation could have a seperate section for risk based on pay rate.

In another section of statistics we see the comparison between garbage collectors, construction laborers, managers, and firefighters. Garbage collectors have a low income in comparison to fire fighters and security guards. I think the reasoning behind this is because, the expectation is not there. I believe that this factor encourages more exploration as to why their salary is low when they too have a high risk job. Their salary is based on conditions that do not see as much as a fatal risk as a fire fighter or security guard potentially sees. From the data on Managers on construction sites, they are much less likely to die than actual construction laborers which makes sense because, they have an office workspace they spend much more time at. However, that supervisors die more frequently that their subordinates which to me does not make sense in conjunction to learning about managers on construction sites who die less frequently than the actual workers on the site. To me this would need more variables and factors to figure out. I would probably need to know the location, ethnicity, and age to understand better.

The last section compares the highest number of death rates based on violence or homicide per every 100K. It would make sense that taxi drivers are most likely to die from homicide than from a transportation accident because of many different factors and variables surrounding safety. It also makes sense to see that coaches, athletes, and umpires are most likely than truck operators to die in a transportation accident. We can presume its because, a truck driver has more experience driving and being on the road than coaches, athletes, and umpires. Truck drivers also have work hours that they follow so it would be more helpful to see and know more variables with this data such as time, age, and location for more understanding.

I would have to say that the U.S. Department of Labor demonstrates how many people die at deadly jobs based on many factors in a precise way. However, they could have used more variables and factors within their data so that they could be more accurate. That way people could have more of an understanding of these specific deadly job comparisons. The colors are used to correspond to each category of comparisons in each section. However, form does not seem to depict accurate comparisons because, the comparisons are not all in their own separate, relatable category within each section: it then makes for a confusing intake of information.


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