HMWK 12 (Paper Guidelines)
This assignment builds off of HMWK 10 and HMWK 11. The goal of this assignment is to prepare you to do a write-up for the analysis of the data from the city you chose to explore in HMWK 11.
While there is considerable flexibility in how you carry out the write-up, I’d like you to focus your efforts on a specific question and a target audience interested in that question. Your write-up must include at least two graphs, each of which is well labeled and documented.
Details:
Audience: local city council members
Background: the city council for the city you chose to analyze has approached you to get advice about which policies they should enact. Policies ranging from education and policing to nutrition and housing are all under consideration. They are very open to creative solutions and happy to entertain any suggestions you have. The city council is particularly persuaded by policies that can be supported with data analysis.
Topic of the Council: the city council is concerned about the well-being of children born to lower-income parents. They want to understand what factors can help children born to low income parents escape poverty and live well. They are concerned about children of all races, all ethnicities and genders, but recognize that there might be disparities across these demographic categories.
Necessary Items in your Write-Up:
1. Explanatory prose consisting of at least 1,000 words
2. At least 2 well-labelled figures showing relationships from the atlas data. These figures must also be documented with a note that explains what the variables in the figure mean, and where you obtained them.
3. A proposal of at least one policy that the council could enact, which your data analysis suggests might help improve the well-being of children born to low income parents. Your policy proposal should, in some way, be supported by the data analysis you provide
Suggestions:
One way to start this project is to look at the kfr_`race’_p25 variables and see which control variables and which other variables (incarceration, *_p75 variables, etc.) bear a strong relationship to these variables. Then think about what explanation could account for that relationship. Then, based on that explanation, think about a policy that might increase upward mobility.
Personal narratives can be relevant, but please keep in mind that your audience is most persuaded by what can be shown with data.
Excellent write-ups with explore several breakdowns such as those in step 5 of HMWK 10, including but not limited to, how different factors might affect mobility differently by race and gender.
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