In the previous series, Philadelphia was looked at in terms of poverty, emphasizing the relationship between demographics and poverty. Now, let’s look at how the level of poverty can characterize the Poverty within Philadelphia. Furthermore, once the level of poverty has been characterized, an attempt to balance the quantity of those in poverty with the severity of poverty within a given zip code will be performed. The hope is to build a model that can capture the city’s areas that may require additional resources and assistance.
Poverty levels are based on a percentage below the poverty line on the federal level, which is currently set at $12,760 for one. The poverty percentages represent the amount above the poverty line such that 50% is approximately six thousand dollars, and 500% is sixty-four thousand dollars a year.
Below is a map of Philadelphia that demonstrates which poverty-level is most prevalent in a given zip code.

A bright spot in the graph (purple) is present in the Old City and Center City section of Philadelphia, representing the most affluent section of the city.
There is no zip code wherein most of the population lives at or below the poverty line (100% or 50%).
Another view is looking at the ratio of persons living with a zip code that resides at least 50% below the poverty line. Below is the graph that demonstrates poverty distribution throughout the city of those living at least 50% below the poverty line.

It seems that the zip codes wherein there is the highest poverty of at least 50% below the federal poverty levels stretch around Center City in a northern and western band. These levels of poverty diminish as one moves north in both western and eastern directions towards the counties.
Interestingly, when comparing it to the map of raw poverty counts, the two maps are largely different: in Part 1, figure 5, the raw counts for those in poverty showed more wide-spread per-capita poverty levels. When utilizing a 50% poverty cut off, the poverty levels are clustered more tightly. This suggests that the level of poverty from Part I, Figure 5 may be experiencing greater poverty than just 50% below the poverty line.
Furthermore, we can compare the zip-codes to each other city-wide. The following map demonstrates how the 50% below the poverty line count relates to the other zip codes throughout the city.

In comparing the zip-codes throughout the city, a familiar trend emerges: the North Philadelphia region is most stricken with poverty. 19140, 19133, 19134 in the North Philadelphia, and Kensington region of the city have almost one order of magnitude greater per-capita poverty rates up to 50% below the poverty line.
Poverty Metric
It may be of use to social researchers to reconcile the quantity of poverty severity with the severity of poverty within a specific geographical region. In this section, a model for quantifying the balance between the number of persons and the level of poverty is introduced.
Although the proof isn’t provided here, two metrics were utilized. One that plays a greater role in capturing the number of people in poverty and plays a greater role in capturing the level of poverty. Both metrics take both into account, yet one is more suited to another, depending on its priorities.

The metric that captures the population count more significantly is Eq. 1. Where Np is the number of people and p is the poverty level.
Conversely, to minimize the impact of the population, the log of the population count is taken, which allows for an increased sensitivity towards those living in poverty, listed below.

As a result, the metric provides a rudimentary way of balancing two opposing considerations if one needs to decide where to invest resources. Does one invest resources where poverty is highest in terms of quantity or highest in terms of distance from the poverty line.
The map below Figure 4 visualizes the first metric that is more sensitive to the population counts living in poverty (Uses equation 1).

Interestingly, with the increased weight towards the population count, West Philadelphia and South Philadelphia’s poverty levels are diminished in comparison. Thus, if one were to focus on a population-count-centric model while still wanting to identify areas of increased poverty, the North Philadelphia region would be the target.
If one minimizes the impact of population count and allow for a more significant impact of the level of poverty, one would see the following map:

When minimizing the effects of population, a more robust picture of poverty throughout the city is seen in Figure 5. The persistent trend of North Philadelphia being the most poverty-stricken section of the city persists in both the population count-models and the poverty-level models. Yet, without the increased emphasis on population count, West Philadelphia’s and South Philadelphia’s poverty status becomes ore apparent.
Another persistent trend is University City (19103), Center City, and Old City having the lowest poverty levels.
Conclusion
In this, and final, look at the poverty throughout Philadelphia, several views were utilized. First, a look at which poverty level is most prevalent per zip code was looked at in Figure 1. It was found that the majority of Philadelphia resides at approximately 125% above the poverty line, and except for Center City and Old City, as one extended towards the surrounding counties, so did the distance from the poverty line.
To look at those living at the poverty level or below, up to 50% below the poverty line, Figure 2 looked at the prevalence per capita within each zip code. Then, to compare the zip codes to one another throughout the city, Figure 3 shows us how the zip-codes compare when looking at those who live at or up to 50% below the poverty line. In both instances, North Philadelphia is highlighted as an area of increased poverty.
Lastly, to capture the competing ideologies of social work: utilitarianism versus disparity-based relief, a poverty metric was designed to combine both the impact of the number of persons in poverty or the level of poverty that may be present. Although both views are taken into account in the poverty metric, one could highlight or specialize in one or the other by choosing the impact of the raw count of people in poverty within the metric. In Figure 4, the impact of the number of persons was maximized, traditional areas of Philadelphia associated with poverty were diminished against the prevalence of poverty in North Philadelphia. The effect of the number of people in poverty in North Philadelphia is further highlighted when the metric is muted against the number of people in poverty, as seen in Figure 5. Here, the number of people is minimized against the level of poverty present. Here, although North Philadelphia is again highlighted, other areas of poverty throughout Philadelphia are demonstrated as well.
Consistently several trends throughout the analysis of Philadelphia have shown themselves. First, North Philadelphia has a serious problem with poverty. The poverty presents itself in raw counts, per-capita counts, demographic-controlled counts, level of poverty counts, and poverty-metric counts.
Secondly, following close behind North Philadelphia is West Philadelphia. Although West Philadelphia has a lower raw count, the demographic and metric-derived poverty levels are pronounced.
Thirdly, South Philadelphia is a mix; when one accounts for demographics, South Philadelphia, for some, is a highlighted region of poverty. But when one controls for per-capita counts and for poverty-level counts, South Philadelphia is middle-of-the-row for Poverty throughout Philadelphia.
Lastly, Center City, Old City, and occasionally University City (depending on the view) are consistently low on poverty. In no metric did Old City have a significant level of poverty.
In sum, I hope to have provided several looks at the poverty throughout Philadelphia. It is the author’s hope that by highlighting the various way with which one can look at poverty, an understanding of the difficulties and challenges surrounding social work is highlighted. Additionally, although not the focus, the author’s hope is that the poverty-metric provides at least a rudimentary manner of attempting to reconcile at least two facets of identifying areas of greatest need.