This week I decided to exam the LA Controller’s Office‘s dataset of the compilation of funds that the city of Los Angeles disperses to projects related to Health, Environment, and Sanitation. Despite LA’s infamy for its cloud of pollutants that engulf the city, I wanted to see how much the city council allocates to environmental projects.
The dataset includes 37 different “funds” in which the total monies budgeted for environmental protection adds to roughly $390,000,000. While that number may seem large, the city of Los Angeles has nearly 4 million civilians the overall revenue that the city collects through taxes is well over 390 million. The dataset further includes the type of fund, denoted by a three digit fund number, the fund name, the department requiring the fund, and the fund’s purpose.
The LA Controller’s Office’s dataset exemplified the issues discussed in the Wallack and Srinivasan article (Local-Global: Reconciling Mismatched Ontologies in Development Information Systems). The article examined how there exists a disconnect between the purpose for using the monies and the program’s lack of total, intended execution. For instance, nearly $19 million went fund the amenities for Sunshine Canyon; the intended purpose of the funds is to “fund the amenities for the Sunshine Canyon landfill facilities”, and gives little information on how the amenities are used, why the amenities consume a large portion of the budget, and if the funds are actually implementing environmentally safe landfill management. Additionally, there is a $5 million fund allocated to Mobile Source Air Pollution Reduction, with a purpose of “for air pollution reduction projects” but little is told about what those projects are, how effective they will be, or how they will be implemented.
I believe this would make the most sense to the individuals writing the budget reports and the politicians disbursing the city’s money. They are the one’s creating these budgets and the lack of detail allows them to easily justify receiving large portions of funds.
This dataset demonstrates that the money collected by government may not always be used as efficiently as possible, and raises some questions as to why the descriptions are so strangely vague. It also brings into question the efficacy of these projects. Are they (the projects) really solving the problems that they are intended, if not, to what extend are they remedying the environmental issues?
If I were not picking this dataset apart and perhaps an individual from Bakersfield, I would be astonished by the sheer amount of money that the city of Los Angeles sets aside for environmental projects. However, of course, Bakersfield is a lot smaller than Los Angeles and one would need to take into account the relative amount of money in addition the extremity of the environmental issues in order to assess whether or not the city is realistically making an effort to curb its pollution situations.
Good effort here, Ethan. It is important to spend time with the data set you select. There is a horizontal slide bar at the bottom of the data sheet that is easy to miss. This would should you that your selected dataset has a much larger metadata record, with many more data types. You make great points about what the dataset can show and what it gets left out. After Monday’s lecture, hopefully it is a little clearer what the ontology of this dataset is and how our reading for this week helps us to understand how to determine it, but be sure to ask questions if you are still unsure.
This data set was super interesting to see how different motions towards environmental issues are made, and what percentage of budgets are being dedicated to civilians health and sanitation. As I look at this data the first ting that comes to my mind is how this compares to other cities budgets and how much they are spending on sanitation. I would like to compare sanitation and environmental budgets by city, and countries.
I like how you start out your introduction paragraph with a brief reason of why you chose the topic that you did; this adds flavor and a more personal connection to the blog post. Each question for this week’s blogpost has been throughly answered with each paragraph, which I can tell you have put a lot of effort in. One minor change I would recommend is grouping multiple paragraphs together, so the entire post becomes more fluid. This is because some paragraphs are too short to stand alone, but only there to address one question from the post. Another change may be just to add headlines for each question answered.
I enjoyed your blog post and thought you did a good job introducing the dataset at which you were exploring. The questions that you raised in your middle paragraphs bring up good points into making the dataset more detailed. I would’ve liked if you’d gone more in depth on all of the other categories of the data and if you’d conjoin some paragraphs to make the post less choppy.
I really liked how you broke down this datasets individual funds with some examples highlighting how the format its made in is structured more towards say a politician or budget report writer who wouldn’t need as much in depth information as say a concerned private citizen trying to dig deep into the data. I also liked how you were able to somewhat caution the reader from making judgements too quickly based on the fact that cities like Bakersville vs. Los Angeles would have widely different kinds of budget dollars spent.