 Simple example, first we will identify variables for a system and then we will try to draw a causal diagram for this one. Hypothesis of dynamics in urban region, the job availability attracts migrants to the city. New arrivals to city expand the labour population, population absorbs available jobs, decreasing job availability. The long run as labour also creates demand for additional services and facilities. The further increase the number of jobs in the city comes about, more jobs increases job availability. It is a pretty simple and kind of an example written in a more straight forward language. So using this we can identify one causal link per statement so that is what it is about. So we have job availability attracts migrants to the cities so job availability should influence migrants or migration into the city in migration and as migrations occur that expands the labour population within the city for second statement. So first statement the variables are job availability increases migrants, more jobs are job availability is there more migrants are in the city, as more migrants are as migration happens migrants are going to expand the labour population within the city. As population as the entire population this thing labour as this labour population absorbs the existing jobs decreases job availability. So the population is going to take up jobs and jobs will decrease the job availability. The long run labour also creates demand for additional services as more labour comes new shops open new services has to be offered so that will after long term increase the number of job availability within the city. So we will identify this let us take it CLD for example 1. So we can identify some variables or let us say job availability migration labour population jobs these are four variables we identified using this let us create our kind of first let us create the links I guess. So let us take the job availability we say effects are migration the first statement said job availability attracts migrants to the city so job availability is more migration is going to be more that is what we can intuitively expect the job availability affects migration. So these left side are the initial variables we identified and migration expands the labour population within the city so migration increases the labour population this labour population is more what you can expect the job availability has to come down because you are observing the new jobs decreases job availability let us suppose there is more jobs come there is more job availability there is one more statement there which had the same way we had two links other one was the labour population after some time increases jobs within the system. So to indicate the after some time part we can simply put a D on the link to indicate that there is some delay in the process after some time the labour population increases the jobs within the system. So these are initial set of causal links that we have created based on the description but this again is still very cumbersome to read you can just combine all of them we do not need to repeat all the variables so many times and create what we call as a nice causal map of it we are continuing the same example let us start with job availability can call it in migration also we are not talking about people leaving people coming in can make it more explicit then we have labour population then we have jobs these are the unique variables that we have job availability increases immigration increases immigration is more you can expect increase in labour population less labour population absorbs the jobs a decrease in general job availability has to happen which but after some time the labour population increases the number of jobs but after some time so there is a delay and as jobs increases of course job availability also tends to increase. So just to indicate it this D indicates delay this is a nice diagram we have this captures the same description that we had in English but it is much more easier to read and much more compact. So the idea is not to just make the diagram but also to have our discussions revolved around that suppose we say as job availability is more you expect the immigration to increase that in turn is going to increase our labour population that is going to absorb the jobs as labour population increases that is going to decrease the number of jobs available so as jobs decreases you can expect migration also to slow down the migration rate as migration rate slows down the labour population increase that also slows down and it going to come to some sort of a balance in the system. So this loop will again be a balancing loop this loop is again a balancing loop. So in this model as you can see there are two loops they start the job availability in migration labour population jobs and job availability there is an outer loop and there is an inner loop. So inner loop is negative feedback let us look at outer loop as job availability is more immigration increases as the increase labour population increases as labour population increases jobs increase that increases again job availability. So there is a positive feedback also that is happening in the same direction or strengthening the phenomenon. So this so we have one reinforcing loop or a positive feedback loop this is a balancing loop or a negative feedback loop. In the term positive negatives are all placeholders negative does not mean bad positive does not mean it is good this reinforcing or balancing or positive negative. Throughout the course you will find that it is very easy to explain the concepts in fact that is it that is the entire thing about causal loop diagram I have done. The difficulty comes in when you start practicing it and start trying to say for example read newspapers and try to come up with a causal map of what is actually happening to understand dynamics now that becomes challenging. There are some certain guidelines for this causal loop diagram which I will discuss let me move on to some of those guidelines for the causal loop diagram. So this about description itself is called as a reference mode. So many times we can use this causal loop diagram this kind of mapping to actually understand what the problem is many of us want to become analysts right. So this kind of system thinking tool will really help you make a good analyst or a systems analyst rather than focusing on the domain of the subject you can actually become system analyst but these kind of causal diagram can help understand and link the various variables and help understand the problems. This itself can help discover what the actual problem is that we are trying to solve. So we already seen this the loop polarity links we saw and loops also we saw balancing loop and reinforcing is going by reinforcing it when loop feedback loop response opposes the original perturbation the loop is negative or goal seeking when feedback loop response reinforces original perturbation the loop is positive or reinforcing. So negative loop or goal seeking loop or balancing loop is the same and reinforcing a positive feedback loop are the same ok. So one way to understand that is suppose we have links like this so for example X1 of XX2 of XX3 which again affects X1 right and if you want to do it the right way then what we need to do is split it let us call it X1 say dash let us see how X1 affects X2 and how X2 affects X3 and in turn how X3 affects X1. So in I think we kind of cut the cut one of the variables and say ok let us initially allow X1 to increase and as for X1 changes how does it affect X2 and X2 changes how does it affect X3 and again as X3 changes how do you affect X1 ensure that you again come back and see what is happening to the variable X1 which is which you perturbed initially. And if the original direction of X1 dash and X double dash is the same then we say that it is a reinforcing loop or a positive feedback loop if it is in the opposite direction as many we initially perturbed this by increasing it but then eventually X1 double dash seems to decrease here then it becomes a goal seeking loop or a negative feedback loop. We are not interested in the quantum of increase we are not interested in the quantum of increase we are only looking at the direction it may be that even the positive or negative the direction is very tiny but still we are only interested in that for now when we move into simulation put numbers then we will worry about actual how the system is behaving it will come to that but right now we can only worry about the direction of for example the job availability attracted huge number of migrants but maybe their job creation is very low the new jobs that they add to the system it can be there is because labour population it does not mean that similar number of jobs has to be created but the direction is the same the number of some additional jobs happen that is what you are trying to say. So, even in this so one has shortcut to figure out where is positive or negative feedback loop is simply count the number of positive or negative signs within a loop to the number of negative signs is odd then it is a positive feedback loop. So, here if you see plus plus and there is one minus sign there is odd number of minus signs so it must be a negative feedback loop even in this example I can do one more let us say x, y, z, w, x so here suppose I have minus plus minus plus as x increases so there are two negative feedbacks so x increases y decreases as y decreases z also decreases same direction as z decreases w increases as w increases x again increases. So, it is the same direction finally the variable x. So, short way is there is two negative feedbacks or a even number of negative feedbacks of a negative links then it is a positive feedback system. So, it is odd this x increases y decreases as y decreases z again increases as z increases again w decreases as w decreases x also decreases. So, eventually x went down when you originally started with x increase it. So, the shorter way is you can see there is odd number of negative links that means it must be a negative feedback loop. So, we have two loops here loop job availability in migration labour population job availability this is the loop. The second case job availability in migration labour population jobs job availability. So, that is the loop. So, and all are in positive direction that case you do not have any problem it is all are positive it has to be a positive feedback system. So, only problem comes in when there is one negative link then what happens then count the number of negative links if it is even then it must be a become a positive feedback. If it is odd number of negative links we have then must be a positive feedback. Can I say there are all these small tips that we can give, but then we will we will go through them and then we will do lot of examples. So, the number of negative links in a loop is even the loop is reinforcing number of negative links in loop is odd the loop is balancing.