Homicides in Chicago have decreased by more than 7 percent compared to this time last year. Through September of 2016, there were 568 homicides in the Windy City. Through September of this year, there were 525.

That is a 7.57 percent reduction in homicides. That is terrific news. However, young American men are still dying. In fact, hundreds of young American men have been dying every year in Chicago for decades. Decades!

Hopefully this decreasing trend will continue and that the remaining 2017 months will experience lower numbers of homicides than what was experienced last year, which can be viewed in the data table above. Stay tuned for further updates and statistical analysis on this very issue.

Matt has a Bachelor of Science in Systems Science, with focuses in applied mathematics and economic systems, from Iowa State University. He is also a professional member of the Society of Industrial and Applied Mathematics and the International Society for the Systems Sciences and a scholarly member of Omicron Delta Epsilon, which is an International Honors Society for Economics.

You can connect with him directly in the comments section, and follow him on Facebook.

You can also follow The Systems Scientist on Twitter or Facebook.

We can use U.S. Census Bureau data to compare the educational attainment of the United States to any of the 50 states; we can use U.S Census Bureau data to compare the educational attainment of the United States to any city contained within the United States (provided data exists); and we can use U.S. Census Bureau data to compare the educational attainment to compare states to each other, counties to each other, cities to each other, or any combination our hearts desire.

For this blog, we will compare the educational attainment of Minnesota, and the United States. In future blogs, we will compare other city, state, and country combinations. We will also compare city, state, and county; and we will even compare zip codes to one another. Which ones will explore? We will answer this question in due time. Let’s begin.

United States

The United States is the Super-system. This means all 50 states and their respective counties, cities, town, zip codes, etc. are contained within the borders of the United States. Readers of this blog are familiar with this idea (for a more in-depth exploration of systems and sub-systems click here). This also means the United States meets the (3) systems’ axioms:

A system consists of a set of elements.

Elements in a system interact.

A system has a function, or purpose.

We will take this axioms to be a given for this blog. Instead we will focus on the data. As we can see, the United States is second in every category except graduate and professional.

As the data illustrates, the United States has a lower median annual earnings (MAE) than that of Minnesota. This is good news for many residents of Minnesota who exceed the median annual earnings at each level of the ladder.

Minnesota

As readers of this blog will know, Minnesota is a sub-system of the United States. This means Minnesota meets the (3) systems’ axioms:

A system consists of a set of elements.

Elements in a system interact.

A system has a function, or purpose.

Again, and for our purposes here, this will be given knowledge to us realize we are dealing with different systems and should treat each data set as its own entity. However, we will observe that the three data sets in this blog have similar behaviors. That is, earnings increase at each level of the educational ladder. However, we observe there are subtle differences.

According to the data, Minnesota has the highest median annual earnings (MAE) at each level of the ladder. For example, the MAE for Minnesota is $51,239 whereas the MAE is $50,595 for the United States. It should be noted that at the professional and graduate level MAE for Minnesota is the same as the United States.

One final thought, it should be noted that the U.S. Census Bureau decomposes its data into regions and divisions as well. So, for example, Minnesota educational attainment data can be compared to Iowa educational attainment data and/or Wisconsin educational attainment data. And this is really just the start of what could be an exhaustive exploration of the educational attainment data. One could even compare men and women at each level of the United States system, if the data exists.

Matt has a Bachelor of Science in Systems Science, with focuses in applied mathematics and economic systems, from Iowa State University. He is also a professional member of the Society of Industrial and Applied Mathematics and the International Society for the Systems Sciences and a scholarly member of Omicron Delta Epsilon, which is an International Honors Society for Economics.

You can connect with him directly in the comments section, and follow him on Facebook.

You can also follow The Systems Scientist on Twitter or Facebook.

Unfortunately, the homicide rate is increasing in Chicago. That is, the number of homicides per month are increasing as 2017 progresses.

The year started off with 145 homicides in the 1st quarter – January, February, and March – compared to the 151 homicides through the 1st quarter in 2016. However, things started to pick up at the beginning of the 2nd quarter. April saw seven more homicides than April of 2016. There were 41 homicides in April of 2016 compared to 48 homicides this year.

May saw a slight decrease. That was certainly good news. But then June happened.

June saw more homicides this year than last year – 84 to 73 – about a 15 percent increase. And now July is following suit. July of 2017 has seen more homicides than July of 2016.

For those keeping count, 409 families have lost a loved one this year compared to the 403 families at this time last year. 400 families?

August starts tomorrow. And that’s terrible news for those who live in the economically depressed parts of the city (my readers recognize these parts of Chicago as subsystems).

Last year, there were 96 homicides in August of 2016. If this homicide rate remains constant, the windy city will see 500 plus homicides by the end of the 8th month of 2017.

It is certainly possible this thing could slow down (I’m rolling my eyes). Cities are stochastic systems; that is, they are probabilistic. But it’s probably not likely that the homicide rate will slow down enough to see fewer people die this year. If the last two months are any indication of what might be possible, then it’s very likely local policy makers could be faced with answering the obvious question from journalists and others in the press, “Why were there more than 800 homicides this year?” The response will be a clutter of words and sentences in ambiguous language – doublespeak.

To be frank, Chicago hasn’t experienced such a ridiculous and appalling statistic since the mid 1990’s. Chicago saw 828 homicides in 1995; and Chicago hasn’t seen fewer than 400 homicides in decades. Wait. What?

Anyway, will 2017 break the 95′ threshold of 828 homicides? One would certainly hope not. It would be great if the number went down to zero starting tomorrow. But that isn’t realistic for a plethora of reasons. The challenges of the depressed economic systems, where most of these homicides happen, are not being met with judicious economic solutions.

The necessary economic tools do exist. But it might be the case that local policy makers in Chicago don’t have accessibility to the necessary economic tools: labor economics, game theory, behavioral economics, systems economics, etc… Or perhaps it’s something else entirely (I doubt it – my money is on the economic tool-kit).

Until then, enjoy the featured image for this article. It is a beautiful picture of a Chicago train surrounded by the city’s stunning architecture. Good stuff.

Matt has a Bachelor of Science in Systems Science, with focuses in applied mathematics and economic systems, from Iowa State University. He is also a professional member of the Society of Industrial and Applied Mathematics and the International Society for the Systems Sciences and a scholarly member of Omicron Delta Epsilon, which is an International Honors Society for Economics.

You can connect with him directly in the comments section, and follow him on Facebook.

You can also follow The Systems Scientist on Twitter or Facebook.

So far, we’ve presented the (3) systems’ axioms and the notions of system’s behavior and system’s boundary. We have also explored these ideas via different examples. And we’ve touched on the idea of a set. However, we now want to differentiate between what a set is and what a system is. Once we show the difference between the two, then we will be able to demonstrate the difference between a subset and a subsystem. And most importantly, we will be able to better observe, analyze, and make sense of different kinds of systems, albeit economic systems, political systems, or political systems.

So how can we differentiate between a set and a system? First, we can address this question by referencing back to the (3) systems’ axioms:

A system consists of a set of elements.

Elements in a system interact.

A system has a function, or purpose.

The difference between a set and a system is that a set satisfies the first axiom; whereas, a system satisfies all three axioms. More specifically, a set B is a collection of well-defined objects (we will use Naive Set Theory for now), for instance B = {2,4,6,8,10}. Further more, the elements in this set interact with each other. For example, the element ‘2’ interacts with element ‘8,’ or element ‘4’ interacts with element ’10,’ or some combination of possible interaction. And finally, there is a function that is produced, or purpose, via the interactions.

As we can see, a set satisfies the first axiom; whereas, a system satisfies all three axioms. Now we have the tools to delve into the subsets and subsystems. We will see that subsets satisfy the first axiom while subsystems satisfy all three axioms.

As stated before, a set B is a collection of well-defined objects, for instance B = {2,4,6,8,10}. However, a subset of B can be partitioned and observed. For instance, a subset A is a subset of set B if all of the elements in the set A are contained in the set B. That is, A = {2,4,6} so since all of the elements in the set A are contained in the set B, the set A = {2,4,6} is a subset of set B = {2,4,6,8,10}.

Thus, this subset or any combination of subsets with any of the five elements – 2,4,6,8,10 – satisfies the first system’s axiom.

To illustrate the second axiom with respect to a subsystem, we want to show that if elements interact in a subsystem, then they interact in a parent system. There are a few ways we can do this. For this article, we can do this by observing the interactions in set A = {2,4,6}. Thus if ‘2’ interacts with ‘4’ and ‘6,’ and ‘4’ interacts with ‘6’ in set A, then these elements also interact in set B because set A = {2, 4, 6} is a subset of set B = {2, 4, 6, 8, 10} because set A is contained in set B.

The final step is to show that a subsystem has a function, or purpose. It could be the case that a subsystem has the same function as its parent system, or it could be the case that it has a function different from its parent system. But either way, it ought to have a function no matter if it is the same or different from its parent system. So how can this be illustrated?

As Donella Meadows conveyed in her book Thinking in Systems: A Primer identifying the function of a system can sometimes be difficult. Indeed, there are instances where the function or a system is fairly obvious.

One way this can be done is by mapping the elements in set B to the elements in set A. In other words, the elements in set B will go to the elements in set A.

The sketch in Example 1 illustrates this point. For instance, 1 goes to 3, and 2 also goes to 3; 4 goes to 7; and 5 goes to 8.

And so something is imputed through 1, 2, 4, and 5, and something is outputted through 3, 7, and 8. This means the elements in set B = {1, 2, 4, 5} would be the inputs of the system and the elements in set A = {3, 7, 8} would be the outputs.

To illustrate this point further, one could view a system that includes labor and wages as the elements. That is, a person exchanges their labor, hours worked, for a wage. If, for example, the wage was set at $30 per hour, then a person would obviously make more for every hour worked as Graph 1 shows.

That is, if 5 hours are imputed into the system, then $150 will be outputted from the system; if 6 hours are imputed into the system, then $180 will be outputted from the system; and if 7 hours are imputed into the system, then $210 will be outputted from the system. And of course this game could be played over and over again. Thus, as the number of hours imputed into the system increases, the number of dollars outputted from the system increases.

Another demonstration of a function can be illustrated through an interaction between an oxygen molecule, O2, and two hydrogen molecules, 2H2. If a gaseous oxygen molecule interacts with two gaseous hydrogen molecules at a high temperature, these molecules are known as the reactants in chemistry, then two gaseous H2O molecules, known as the products in chemistry, will be produced. In other words, if one gaseous oxygen molecule and a two gaseous hydrogen molecules are imputed into a system, then the system will output two gaseous H2O molecules as Example 2 demonstrates.

These systems’ functions and purposes are obviously not what we often think of as a function or purpose of a system. They are in one instance somewhat familiar and in another instance esoteric.

In this article, we have used mathematics along with a couple of examples from economics and chemistry to distinguish the difference between a set and a system. Moving forward, we will be able to continue building off of these axioms, notions, and examples as we begin to apply these ideas to more familiar systems such as economic systems, political systems, and social systems.

Let us now, as we have done before, attempt to disprove our notions and work in the tradition of natural philosophy until the next blog.

Matt has a Bachelor of Science in Systems Science, with focuses in applied mathematics and economic systems, from Iowa State University. He is also a professional member of the Society of Industrial and Applied Mathematics and the International Society for the Systems Sciences and a scholarly member of Omicron Delta Epsilon, which is an International Honors Society for Economics.

You can connect with him directly in the comments section, and follow him on Facebook.

You can also follow The Systems Scientist on Twitter or Facebook.

However, these numbers do change from time to time. According to the most current Chicago Tribune data, the total number of homicides through 2017 now stands at 333. This means that 2017 homicide data is now on pace with 2016 homicide data: 333 homicides in 2016 through June and 333 homicides in 2017 through June.

We’ve built a system’s foundation over the past few articles. We’ve established the (3) systems’ axioms, we’ve provided examples of systems’ boundaries, and we’ve illustrated systems’ behaviors; and now we can these axioms and notions to provide a greater understanding of what the homicide data is telling us.

We know Chicago is a system with boundaries and behaviors. If we differentiate 2016 from 2017, we can identify similarities and differences in Chicago’s homicide behavior; that is, how a system’s performance changes over time. In this case, we mean the lower the number of homicides, the better the performance of this system.

Why is this the case? This is because economic utility is inversely proportional to crime and therefore homicides. In other words, as crime increases, economic utility decreases, and as crime decreases, economic utility increases. However, it should be noted that there are exceptions to this rule, for example, Downtown Minneapolis.

By observing the data in Graph 1, we can see that there aren’t many significant differences between 2016 data and 2017 data. Of course, there are months in 2016 that contain a greater number of homicides than there are months in 2017 and visa versa.

For example, there were more homicides in January, March, and May of 2016 than in those same months in 2017. In contrast, there were more homicides in February, April, and June of this year than those same months in 2016.

The greatest difference between the two years has been the months of May and June. For instance, there were 12 more homicides in May of 2016, 68 in total or approximately 17.5 percent, than in May of 2017. In comparison, there were 11 more homicides in June of 2017, 84 in total or approximately 15 percent, than in June of 2016. But overall, the behavior of the Chicago system of 2017 has been similar to the behavior of the Chicago system of 2016.

Either way, this system’s behavior is going to continue to depress economic utility in some parts of Chicago where these homicides are concentrated. And as the readers of this blog now, homicide distribution is not equal throughout Chicago.

This is because the neighborhoods of Austin, Englewood, Garfield Park, and North Lawndale to name a few continue to experience high numbers of homicides and high numbers of crime in general year after year. In contrast, the neighborhoods of Edison Park, North Park, Forest Glen, and Hegewisch to name a few do not experience such adverse systems’ variables, and of course this is good.

But how can adverse systems’ variables be addressed either by economic and public policy or by market solutions in these depressed subsystems of Chicago? Or perhaps these systems’ challenges could be addressed with a combination of government and marketplace solutions in these depressed subsystems of Chicago?

Let us now, as we have done before, attempt to disprove our notions and work in the tradition of natural philosophy until the next blog.

Matt Johnson is a blogger/writer for The Systems Scientist and the Urban Dynamics blog. He has also contributed to the Iowa State Daily and Our Black News. Matt has a Bachelor of Science in Systems Science, with focuses in applied mathematics and economic systems, from Iowa State University.

You can connect with him directly in the comments section, and follow him on Facebook.

You can also follow The Systems Scientist on Twitter or Facebook.

So far we’ve established the (3) systems’ axioms; we’ve touched on the notion of systems’ boundaries by using examples of cities; and we’ve established what a system’s behavior is by analyzing the labor force, average weekly wages, and unemployment rate of Minneapolis. Today, we are going to begin to partition the Minneapolis system into its respective subsystems and we are going to do it by ward.

In the next blog, we will decompose Minneapolis by zip-code. And in a future article, we will decompose Minneapolis’ wards into their respective subsystems – neighborhoods – which will introduce us to the notion of systems’ levels.

Minneapolis is a city with 413,651 residents as of July 1, 2016 according to the U.S. Census Bureau. Furthermore, those 413,651 residents obviously live in different parts of the city. Those parts of the city are called wards and Minneapolis has 13 Wards. According to Minneapolis City Government data, each ward contains about 32,000 residents, which of course varies every few years.

This means that each ward in Minneapolis contains about 32,000 residents; those residents interact with each other; and each ward has a function, which in this case is to provide political opportunity in voting and representation, and allocation of resources.

Besides illustrating that these 13 wards are systems, we have also established that these wards are themselves subsystems of the general system of Minneapolis. This is because we have shown they satisfy the systems’ axioms, they are contained within Minneapolis, and they have established boundaries, i.e., political boundaries.

And this is a great place for us to dig a little deeper into the notion of boundary. Boundaries can be fuzzy or concrete; and boundaries can be regular or irregular. In the case of political boundaries, which are the wards we are observing, they are concrete and irregular. If we look at any of the 13 wards in Minneapolis, we can observe that the boundaries of the wards are well-defined, i.e., concrete. And we know this is because of the Minneapolis City Charter. But we can also observe that these boundaries are irregular. That is, they are not squares, rectangles, triangles, or circles.

In this short blog, we established that these 13 wards are subsystems of Minneapolis. We also established, with the help of the map, that the boundaries of these wards are concrete and irregular. As we keep moving forward, we will see that our new-found knowledge of systems will pay dividends when we begin to compare and contrast the different wards, neighborhoods, zip-codes, and other Minneapolis subsystems. And we will do this by adding a new tool to our systems’ took-kit – systems dynamics.

Let us now, as we have done before, attempt to disprove our systems’ notions and work in the tradition of natural philosophy until the next blog.

Matt Johnson is a blogger/writer for The Systems Scientist and the Urban Dynamics blog. He has also contributed to the Iowa State Daily and Our Black News. Matt has a Bachelor of Science in Systems Science, with focuses in applied mathematics and economic systems, from Iowa State University.

You can connect with him directly in the comments section, and follow him on Facebook.

You can also follow The Systems Scientist on Twitter or Facebook.

Over the past couple of blogs, we have illustrated the power of the (3) systems’ axioms (we will review the axioms very shortly) and we have introduced the idea systems’ boundaries. But in our quest to understand what a system is and how we can use system’s knowledge to find real-world applications, we must endeavor to keep testing the validity of our ideas while we add new notions to them.

In today’s blog, we will test the idea of an economic system against our (3) axioms with respect to Minneapolis. We will do this by introducing the notion of systems’ behavior via data and graphical representation. And in doing so, we will ask three questions to facilitate this discovery. First, does Minneapolis satisfy the (3) systems’ axioms? Second, does an economic system satisfy the (3) systems’ axioms? And third, what is systems’ behavior?

In our previous blog, we illustrated that Chicago satisfied the (3) systems’ axioms:

A system consists of a set of elements.

Elements in a system interact.

A system has a function, or purpose.

That is, Chicago consists of a set of elements in the form of approximately 2.7 million residents. Chicago’s residents also interact with each other in various ways on a daily, hourly, minute, and second basis. And one of Chicago’s functions is the ability to increase utility and stability while decreasing crime and instability.

Thus, homicides are concentrated in specific neighborhoods and so it follows that the economic, political, and social systems will behave much differently in the Austin neighborhood, which has experienced 43 homicides this year, than they do in the Edison Park neighborhood, which experienced no homicides this year, for example.

Using the template that we used for Chicago, we can illustrate that Minneapolis will also satisfy the (3) systems’ axioms. This is because we know from U.S. Census data that Minneapolis had 413,651 residents as of July 1, 2016, which is our set of elements.

We also know that residents interact with each other in various ways. And finally, we can think of a half-dozen possible functions that Minneapolis might have. For example, we can think of three economic variables that will tell us if utility is increasing or decreasing in Minneapolis: labor force, wages, and unemployment. We know that these three variables can be systems’ functions. Thus, our (3) systems’ axioms are satisfied once again.

Now we can show if an economy is an economic system in a few different ways, but in this case we will use a similar approach to that of our city examples.

Indeed, not all of the 413,651 residents participate in the marketplace. In reality it is those residents who are 16 years of age and older. And frankly, that’s all that is needed – a set of market participants. It could be 50 percent of the population. Those 50 percent, or 200,000 and some, are a set of elements.

In addition, these participants interact with each other various ways. Some of the participants are employees; some participants are even unemployed; and some participants are business owners. No matter the capacity of these participants, they are still interacting in the marketplace in one form or another. The point here is that they are interacting.

And finally, does the economic system have a function? If Adam Smith and his books The Theory of Moral Sentiments and The Wealth of Nations are to be a guide, than economic utility (stability and vitality) is to be the main function of an economic system.

Indeed, this notion of economic system is more abstract, but the (3) systems’ axioms are still satisfied.

Now if economic utility is our function and we want to illustrate that function for everyone to see, how do we do it? Simple. We’ll do it graphically via data.

As we stated before, the functions of the Minneapolis system are labor force, wages, and unemployment. We also stated the function of the economic system is utility. Adding in the title of this blog How is the city’s economic system performing? we can now address the systems’ functions and question in one sitting through the notion of systems’ behavior.

Systems’ behavior – how a system’s performance changes over time – will tell us how a system is performing. In other words, if the economic system of Minneapolis is performing well, then we ought to expect to see an increase in the labor force, an increase in wages, and a decrease in unemployment over time.

However, if the economic system of Minneapolis is not performing well, then we ought to expect to see a decrease in the labor force, a decrease in wages, and an increase unemployment over time. For sure there are other economic variables we could consider, but for now, and for brevity, we will concentrate on these three variables.

If we take a look at Graph 1, it will tell us how the labor force of Minneapolis has been behaving over the past decade. So what are we observing? What is the graphical data telling us about the labor force in the economic system of Minneapolis?

Well, we are seeing a steady, albeit stochastic (probabilistic), increase over time, correct? Aren’t we observing an increase of about 20,000 participants in the labor force since January of 2007? If our observations are correct, we are seeing an economic system that is performing well in regards to the labor force over time.

What do we see when we observe the wages of Minneapolis in Graph 2? Doesn’t it appear that the average weekly wages for Minneapolis have increased by about $300.00 since the 1st Quarter of 2007? If so, then we are observing an economic system that is performing well in regards to wages over time.

And finally, what do we see when we observe the unemployment rate of Minneapolis in Graph 3? We see the unemployment rate decreasing from more than 8 percent in early 2009 to a little more than 3 percent in late 2016. Again, and just like the first two variables, we are observing an economic system that is performing well in regards to unemployment over time.

So with respect to the systems’ functions of the Minneapolis system, the systems’ behaviors via our graphical representations of the labor force, wages, and unemployment are telling us that the economic system in Minneapolis has been increasing in utility for the residents of the city, in general, for some time now.

Thus, we have shown that Minneapolis is a system, the city has an economic system, and that the economic system is performing well based off our established parameters.

Let us now, as we have done before, attempt to disprove our notions (systems axioms, boundaries, and behaviors) and work in the tradition of natural philosophy until the next blog.

Matt Johnson is a blogger/writer for The Systems Scientist and the Urban Dynamics blog. He has also contributed to the Iowa State Daily and Our Black News. Matt has a Bachelor of Science in Systems Science, with focuses in applied mathematics and economic systems, from Iowa State University.

You can connect with him directly in the comments section, and follow him on Facebook.

You can also follow The Systems Scientist on Twitter or Facebook.