Gold diggers, sugar daddies, sugar babes, gigalors, we've all heard of these kind of people and I've had my share coming after me. I could have written a 300 page book on the psychology of this particular segment of the population, but I won't do this to you. Instead, I will discuss today four and only four elements in the psychology or maybe even psychopathology of gold diggers. Now, rough definition, before we embark on our amazing journey, gold diggers are people, usually women but not exclusively women of course. Gigalors are kind of gold diggers, and they are men.  They dismiss hard work, although gold diggers I think is a lot of hard work, but they dismiss classical, accepted, socially sublimated types of hard work, hard study, hard anything. They regard other people's wallets and bank accounts as rightfully theirs, directly or indirectly. Now, only a small minority of these people are psychopaths. In other words, even though they are gold oriented, not all of them or a small minority of them are callous and ruthless and unscrupulous and unethical and immoral and even criminalized. The vast majority are not. They have a peculiar way of looking at the world which I will try to explicate in this short video. At the basis of the foundation of it all, there is insecurity. It's a double-edged sword. On the one hand, these people are insecure about the world. They regard the world as a hostile, frustrating, unforgiving environment. And on the other hand, they are insecure about themselves. They don't trust themselves to be self-efficacious, able to extract the best possible favorable outcomes from the environment, from other people. They don't believe. They couldn't convince themselves that they're able to act in the environment and on the environment in ways which guarantee ultimate happiness, well-being, contentment, accomplishments. So this is a double form of insecurity. I don't trust the world and I don't trust myself to act in the world and on the world. Insecurity is the basis of this kind of behavior. It's as if they're trying to convert other people into the equivalent of a secure base. It's as if they're trying to appropriate other people's accomplishments, confidence, self-confidence, assertiveness, access to contacts or to money and so on. It's as if they're trying to live by proxy vicariously through other people, annexing other people's lives. And this is a solution to their insecurity. And in this sense, gold diggers and so on and so forth, they're clingy, they're needy. One could even venture to say that probably they're codependent, although there are no studies to substantiate this. Next point is entitlement. These people feel entitled to the good life, entitled to luxury, entitled to glittering company, entitled to not work, entitled to not study, entitled to travel all over the world, entitled to complete and utter independence, entitled. This entitlement, which is a hallmark of narcissism, is very common among gold diggers. And it drives them to behave in ways which are essentially extortionate. Everything is a transaction in life. Every marriage, every relationship, this is a given take. That's normal. But what is abnormal with gold diggers is the tendency to externalize aggression via the act of giving and via the act of taking. They, it's kind of sublimated or passive aggression, embedded, built into, baked into, hardwired into the interactions of gold diggers. Their entitlement is aggressive entitlement. They go for it because they're convinced of the outcomes. Gold diggers would try to create the maximum asymmetry and asymmetry in age. So very young, very old and asymmetry in beauty, very beautiful, very handsome, very ugly. They rely on these asymmetries to impose and enforce an agenda on the other party. If you want my youth, if you want my beauty, if you want access to my body, if you want my company, you have to pay. And you have to pay through the nose. Again, it's extortionate. By doing this, the gold digger objectifies her mark or her target. She treats her partner as a kind of tool or instrument or venue or channel or conduit, anything but a human being. As far as the gold digger is concerned, person she's chosen to victimize in a way is actually nothing more than a walking, talking bank account. And so this objectification is very extreme in gold digging. There is no, there isn't even a minimum of emotional attachment or bonding of any kind. There's no compassion. There's no empathy. There's no affection. It's called and calculated to the extreme. And this is, of course, psychopathic. So we have seen by now, codependent traits, narcissistic traits, codependent traits, insecurity and clinging, narcissistic traits, entitlement, aggressive entitlement, and psychopathic traits, objectification. The whole thing is wrapped up in a philosophy and ideology of transactionalism. Everything in life is give and take. Your role is to minimize the giving and maximize the taking. It's a zero sum game. There are winners.  For every loser, there's a winner. There's no win-win situation. The gold digger is after, is after depleting the resources of her partner and moving on to the next partner. She's a scavenger or he is a scavenger in many ways. This parasitism, this derivative life, this extreme transactionalism, characterizes or separates gold digging from all other types of human interactions, which also involve, of course, implicit or explicit transactions. Here, the transaction rules. The relationship is secondary, byproduct, side effect of the transaction, and the transaction is always lopsided and exploitative. Okay, a few thoughts about gold digging. By the way, there are gold digger forums where gold diggers teach each other all kinds of techniques which border very much on extortion and blackmail, but they are still legal. It's emotional blackmail, basically. So there are forums of gold diggers. There are forums of sugar babes. There are even forums of sugar daddies, believe it or not. It's a whole industry, and it's pretty institutionalized. There are even kind of schools online to teach you how to become one, and there are parameters. There are draft agreements. I mean, it's really impressive when you delve deep into it. I use the words mark and target and victim, because ultimately the partner of the gold digger is all free, even if and when the sugar daddy believes that he has got the upper head, that he is getting the better end of the stick, that the deal is tilted in his favor. That's self-deception. Ultimately, the gold digger gets to keep her youth, her sexuality, and the target's money, not a bad business. So, good luck if you choose this career, and drop me a note. Tell me how it went.


Hello, my name is Metia Lombasi. My friends and people who know me call me Metia. I'm a master's student at the School of Forest Resources and Conservation at the University of Florida in the United States of America. I'm studying there because I would like to learn more about community and policy, especially about tropical forests from around the world. The opportunity was so great for me, it feels so grateful because I met with people from around the world. They also work in the forestry sector, but not only that, I also learned about from other disciplines, like from social law. And yeah, I got the opportunity to do the exchange, knowledge exchange with them, especially from people from Latin America who also study forestry because we have similar forests there and the problem that they have, the challenge that they encounter and also the solution. So I can learn from them and compare it with what is happening in Indonesia. I will go to the community to work with them regarding fire and pitland burning, not only with the community, but I will also have a meeting with different stakeholders, such as government, non-governmental organizations and also profit companies that are related to pitland and fire problems in Indonesia. In terms of the environment at the University of Florida, we have a strong concentration in Latin America because of our proximity, of course, to Latin America, but we don't have, very rarely do we have Indonesian students or Asian students in general, so this group bringing a whole cohort there has really enriched the program. And for them, I think it's been really rich because our courses are laced with people from all kinds of countries. I think it's been rich for the Indonesian students too. I think they thought they would just be interacting with Americans, but they're not. They're able to interact with people from all different countries, so that's been really wonderful. So for me, it's been a fantastic experience. I really appreciate it very much. The diversity, the diversity is great. I met with a lot of people and the professor that is expert in the field that they are, or in the subject that they are teaching. Yeah, those are the most important things because by meeting with a lot of people with different skills and expertise, it helps me grow a lot, I learn a lot. Yeah, and give me different perspectives and see the world in the wider scale.


So as Rakesh said, when we think about learning, we often think about information transmission from one mind directly into the other minds. But you all know that that's not how learning works. And if you didn't know that half an hour ago, now you do. Learning is construction, not just reception. And Ken and Emma, I hope, convinced you that the best way of teaching, therefore, is not just to spit out knowledge, but to target personalized teaching to the learner so that students can construct this kind of knowledge for themselves based on what they bring to the educational experience. So the US National Educational Technology Plan lists four aspects of personalization that need to be addressed in any effective program. Individualization, differentiation, connection to what the learner knows, and connecting to the whole learner. And it's these last two that I'm going to talk about, because there is a cultural and social context to learning that we must not ignore. It includes personality, but also other things. For example, researcher Barbara Rogoff showed that children from indigenous families in Mexico are penalized in the classroom for not speaking up. But in those families, children learn from observing. They're not supposed to speak up. Likewise, in Ireland, children from poor families are penalized for all speaking at once. But my student Mike Anani and I showed that, in fact, these students are simply exceptionally capable of speaking and listening at the same time. Now, today, we're facing a revolution in online learning. But this revolution is not necessarily targeting the sociocultural context. For example, three quarters of all students enrolled in MOOCs come from outside the United States. But three quarters of all instructors of MOOCs come from inside the United States. Now, this means that there's a model of learning that is not necessarily the one that works best for all of these students. So in my group and in all of the work that we do, we're looking at actual contexts. These are images of us bringing an interactive tutoring system into South and Central America. Those children collaborate in ways that the software was not originally designed to work with. And why shouldn't they collaborate? We all collaborate as adults in our day-to-day life. And we need to make sure that that's a part of learning. So we've begun to implement technologies that actually take into account the personal, social, cultural context. Here's a very real and important example. Many children come to school speaking a stigmatized dialect. In the US, it might be African-American English. In France, it might be the dialect of the Paris banlieue. In each case, teachers don't necessarily realize the cultural importance of that dialect. And they may say negative things about it. But my students and I have shown that when students learn with a virtual child who speaks their stigmatized dialect, they do better science in the classroom. On the other hand, when students hear a teacher, this is an actual teacher comment, say, students who don't take advantage of their education and sound like they belong in the street end up in the street.  That has a terrible effect on their ability to learn and their faith in themselves. A recent study found that learning gains in MOOCs were not related to watching lecture material, but to interaction with peers. And so many educational systems are targeting rapport with the student. But rapport is not necessarily all niceness. This is actual data from a peer tutoring study of linear algebra. It's not exactly essential to linear algebra what you see up here, but it is essential to rapport. We found that students who insult one another learn more. Now, the goal is not to invent rude technology, although it turns out that when students insult software of this kind, they also learn more. What is the goal then? The goal is to remember that every student is an individual with individual knowledge, individual abilities, but also an individual social and cultural context. And it is only in targeting the whole learner, both for young children, for high school students, and for adults that we're truly able to unlock the entire learning potential of every individual. Thank you.


So we turned on payroll in the system. I'm going to go back to the tab to the left because it was part of the free 30-day trial. So we turned on the payroll. Payroll is a little bit difficult. So if I go into the payroll and the overview up top, it's a little bit difficult to follow along with the payroll in a practice problem because payroll is one of those things that generally needs to be run real time. So if you're working way out into the future, for example, as you're looking at this practice problem, you might not be able to process payroll in exactly the same way. That's part of the problems with the payroll. Also, just realize that the payroll will change from quarter to quarter. So you usually want like a whole years of payroll in one payroll system. You don't really want to change payroll in the middle of the year. You can, but it's not preferred because there's caps on things like social security and federal income tax. So obviously when you do like the 941s or process payroll from one period to the prior period, you compare it to the prior period. That's what we always do with accounting. But it'll change as the year goes as people hit some of these caps for like federal unemployment tax and social security and that kind of stuff. So just a couple things to keep aware of. So we're just going to go in. We've set up the payroll, the payroll set up. We've added our employees. We've got our two employees. We set up to be paying payroll on a monthly basis as opposed to weekly semi-monthly and so on. And so now we'll just go up here and process the payroll. So I'm just going to run the payroll and hope that they'll allow me to run it even though I'm not in the real time here. So I'm going to hit the dropdown. This period by period has been set up when we set up the payroll so that the next period that we would run would be 2023. So February, February 2023, there's the pay range, the period, because we have a monthly period. So it's the full month. The pay date happens to be the same day as the end of the period, which may not always be the case. You might have a pay date that's a little bit after the end of the period. So you have a little bit of time to process the payroll after the pay period, but we're going to keep the same date here to keep it in that second month that we're working on. And then if everything was laid out properly, you might be able to just process from here, but we need to go in and make some adjustments because of the practice problem. And so I'm going to go into Hamilton and actually that's going into his information stuff. I'm going to close that. I'm going to go into the pencil on the right hand side so I can see the calculation this way. So we've got the summary of the information. We've got the pay. He's a salaried employee. So this is the salaried amount.  Where's the calculator? It's not in the recent area. I've been using it all the time. So we're going to say this is going to be, I think it was 55,000 divided by 12. That's where the 4583, 55,000 a year. And then if I go into the employees, this federal income tax is one of the most confusing ones. We would populate it from tables and whatnot in the information that was populated in the W-4. But that's one of the things you're paying for, for QuickBooks because it's not a flat tax. So that's one of the confusing ones to calculate. So I'm going to make a number up that matches our practice problem that's not coming from the W-4. I just wanted to match the numbers in our practice problems so it'll tie out to our bank reconciliations. Now, the social security and Medicare should be easier because that's just going to be the 4583.33 times .062, I think is currently the calculation. So that's a nice, easy one to do because it basically is a flat tax, although there is a cap. So if they get above the wage cap, this number will change. It'll be lower. And that's what I mean about the payroll possibly being different from period to period as you go through the year. And then we've got the Medicare. We've got the 4583.33 times .0145. That gives us the 6646 about I'm not going to do any California tax because I want to make it kind of like a generic problem on the payroll side. And then you've got the employer taxes, which are matching social security and Medicare. So and there would also be the federal unemployment tax, which I didn't add because that's a much smaller tax. And again, I want to keep it kind of generic for our practice problem. So up top then, if we think about this, we've got this would be what they earned. This is what we're taking out of their earnings. These are in essence the mandatory withholdings for federal taxes. You could also have mandatory withholdings for your state and local taxes. As for example, California might be, but that will be changing from place to place. You can also have voluntary withholdings, which might include things like health insurance 401k and that kind of stuff. We have a whole course that goes into at least setting that up and more detail. If you want to dive into that in more detail, it's a whole thing in and of itself. And then down here, we've got the employer taxes, which are matching the social security. So what's going to be the transaction for this one employee as I go through it? Remember that you can think about the financial transactions, what's going to happen to the financial statements on an employee by employee basis, or as though all employees were kind of like one employee. So if I was doing my payroll from a third party provider and entering them into my system, I might think of all the transactions as one, one big employee, right? And enter a journal entry or something like that into the system, although I still need to reconcile the bank's accounts. But that's the way that that's the way that you can think of it. If you're doing this stuff internally, you can't it's useful to think of it as one big employee. What's the impact on the financials, but you also need all this added detail so that you can provide what you need to the employees on the pay stubs and on the reports to 941s to 940 and W2s and W3s. That's why it gets messy. So that means this is going to be a debit or an increase to the payroll expense. And then all of this stuff is going to be decreasing or increasing a liability for the liability account and the difference between the two 4583.33.33 minus the 105.62. That's what's going to be decreasing the cash account. And then down here, this is going to be increasing the the expense account for payroll expense, payroll tax expense, and the other side's going to be increasing a liability account. And then we'll have to pay off the liabilities in the future. Okay, let's save that. Let's just, does that make sense? I think everything is proper. Okay, so let's close that up and let's do this for Erica. Let's check out Erica.   I am the HR department. We're payroll over here. I'm just looking at Erica's wages. So we're going to say Erica, let's say that Erica had hours of 360. And so update the time sheet hours. I'm going to say, so it's trying to link to the time sheet because I put the time sheet on the payroll, but I was basically using the time sheet to populate the information for the invoices more than pull it in for the purposes of the payroll. So I'm going to kind of discard the time sheet here. So that's going to give us 15. That's going to be, that's going to be, then we'll hold on a second. I'm going to put in here, not 360. I'm going to put 160. And so that'll be 2,400. Okay. And then what we're going to withhold, I'm going to change this again. I know it's really high, but I'm going to change it to 360 to tie out to our numbers in our practice problem and remove the California tax. So that means that the 2,400 times .062, that's where they came out with that 14880. And the 2,400 times the .1045 is where they come up with that 3480. And then we've got our match down here. So for this employee, the transaction would be when we record this, we're going to have, you can think of it first as a payroll check. So you might say, well, the payroll check is going to go, cash is going to go down by 2400, 2400 minus the 543.6. It's going to go down by that, by that 185640. And then the other side is going to be payroll expense, but it's going to go on there for the full amount of the 2,400. The difference, the liability, this kind of sounds like sales tax may be to you. The liability, which is their taxes, the employee's taxes, kind of like the sales tax is supposed to be the customer's taxes, is going to go into the liability account for the liabilities. And then we're going to pay taxes over and above. These are our taxes. So we have payroll expense, payroll tax expense for the 18360 and liabilities going up for that amount as well. So again, you can see that check by check and you can also see it in total. So if I was to think of both employees as one large employee, you could think of the transaction that way as well. Let me just double check these numbers. So that looks, that looks good. And that looks, that looks, that looks, that looks good, I think. So and remember, payroll is one of those things you want to measure twice and cut once. You don't want to have to reprocess payroll generally because


All right, so the second part of the session will be concerned with simulations and network science. And that's why we decided to have a bit of an introduction so that everyone's on the same page and everyone's actually can have a good understanding of what people will be presenting. So we'll start with some basic definitions. And the super basic was is complexity science. Complexity science is a branch of science that is concerned with studying complex systems. And when you, as an archaeologist thinking about a complex system, you probably mean complex hierarchical societies. This is not the definition that is used across the science. So let's look what a complex system is using their words. So a complex system is usually simple. It doesn't have to be complicated. But even though it's simple, it's very often very difficult to predict. Most of them consist of many elements, and those elements interact with each other. And their interactions still may be simple, yet the results of those interactions are not. So when you think about it, the most obvious example of a complex system is a human society. It consists of many elements, humans, who interact with each other. And those interactions may be pretty simple. There may be communication of ideas. They may be passing of information from one person to another, or, I don't know, getting together and forming a household. So those interactions not necessarily have to be complex, but the results of them, the pattern that we have in economy and social changes, they are very difficult to predict, and they are not obvious from just by looking at the characteristics of the people, of the entities that actually make the system. So that's a complicated subject, so let's give an example, right? So here are neighborhoods, Jewish Arab presidential patterns in two neighborhoods in Israel. And when you look at them, I don't know who's whom. Let's assume the Jews are green and Arabs are blue. When you look at this, the logical conclusion is they absolutely hate each other. And this may be the case. We don't know, we don't know. But maybe there's another reason why they are so segregated, why they don't live together. So quite a few decades ago, Schelling, who got a Nobel Prize for that, created a model, and the model is very simple. You have triangles and squares. You can call them Jews and Arabs, but you might get into the foggy area. And they only have one pattern of behavior. They basically have preference on how many of their neighbors should be the same as them. They can be like, okay, I want one in six of my neighbors, like I want my neighborhood to be at least one third the same as me. Or you can be like, oh, I really want that it's more than half. So if you then allow them to move every time they're unhappy, if they can change the position of their household, then you get some really interesting patterns. If their preference is for 10% of people living around them, then they're pretty well mixed. But you can see that already, when they have only 35% preference for people like them to live around, you end up with segregated neighborhoods.  I mean, that's quite an overstatement, right?  And the only way of not having segregated neighborhoods is to basically wanting almost everyone of your neighbors to be like you, so being pretty racist, right? Because then nobody's happy and everyone just moves around. So you can see that it's funny that like, even nice people that have no problems with the other type of people are handed up in this social situation that we interpret in a pretty dramatic way. Without using complex system approaches, we would have never guessed that. At least that's what the Nobel Prize Committee believes. So the most common tool for studying the behavior of complex system is simulation. And the most common way of representing the structure of complex system is network. And now Tom will give you the pitch about networks and he's got exactly, and yeah, and the two, they make complexity science. He's got exactly three minutes for that. Three minutes, thank you. I can move your slides. No, no, no, thank you, I'll do that. So yeah, network science is definitely one of those main approaches that we use to study complex systems. Network science allows us to deal with network data. And I very often like to think about how we use GIS as archeologists as a comparison. We use GIS to deal with spatial data. We make maps, we represent spatial data, we manage spatial data in our spatial databases, and we analyze spatial data using GIS systems. And they can do all of those things. Now, network science does exactly the same, but with different type of data. It does that with network data. We use network science to represent network data, to represent dots and lines. We use network science to manage them in our softwares and our databases. And we use network science to analyze that network data. Like in GIS, we ask questions about the relationships between places, between sites, not based on their spatial proximity, but based on how they are related to each other. So we could ask questions about how central is this particular site in this network? How important is this place as an intermediary for the flow of information, given the relational structure between the different sites? These techniques are most commonly applied in archeology to represent our archeological data as networks and to explore the implications of that, or to explore the structure of our network. But also to represent our theories about how we feel or how we think past societies might have interacted with one another as a network model. So these are two examples of those. Now, there's a couple of fields of application that have emerged as proving that network science can make useful contributions to archeology. They tend to focus on road networks on the one hand, which mainly concern those cases from, for example, the Roman Empire or Inca societies where you have physical evidence of actual roads or very well documented information about roads, and we can explore how information and goods and people and the military flow through those, but also network representations of least cost-pass studies that are performing GIS. Another prominent field of applications is that of island connectivity. So for example, John Terrell, back in 1977, theorized that Pacific Islanders had a limited ability to interact with one another. They couldn't interact with all of the islands around them, but rather tend to interact preferentially with the three nearest island communities. So he represented the network model to represent that theory. Also in urban studies and architecture, where we use the techniques like access analysis to represent urban spaces or house spaces and the connections between them, the ability to move from one to the other as a relationship, which is basically graph theory and network science. We also deal with social networks. Now here, this is a perfect example of like archeologists use either data for networks or theories. How many cases do you know in archeology in which you have data about social networks? I happen to know a few because I do Romans and we are just spoiled with data. It's a fantastic place to work, but like the vast majority of archeologists don't have data like that. So very often we have a theory about people in the past that interacted with one another, that created communities, information was spread throughout those communities and that we theorize implications of that. So we use network models to represent our theories. Now, another big body of applications are similarity networks, representations of archeological site assemblages and their similarities. And this kind of application where we represent sites and the poultry for example, the artifacts that are part of the assemblage, we draw a relationship between an artifact type if it's part of that assemblage. This to me is a good representation of the diversity of things we can do with network science. We can just use it to represent very typical archeological data and explore our data set in a different way as a different data representation. But we can also formulate theories about why these relationships matter. We could say as we so often do in archeology that if a pair of sites has some artifact similarity then in the future, those sites will have more increasingly similar assemblages. So we assume that a relationship from site two to type one is probable to happen in the future. This is just an archeological theory about what these relationships mean and why they matter. But these are things that we can express and evaluate with network science. Back to me. That was perfect, three minutes. No, two. So we go back. So that was how we usually describe the structure of complex system. We use network to do that. In order to understand the behavior and the outcomes of interactions in a complex system, we mostly use simulation. So to go from the super low level, let's start with a model. So a model is a simplified version of a real system of something that actually exists in reality. So you have a fire truck here. And this is a model. This is a drawing of this fire truck. It's not a fire truck. Fire trucks are not one two dimensional and they're not made out of paper. This is a model. My kids has a similar one. This is a model of a fire truck and it's made out of plastic and it is red, right? So it has some elements of the original system that are similar and other elements that are different. This is a model. Again, it's red and it's probably more realistic than a plastic one, but it also doesn't exist in the real world because it's a game. And this is also a model of a fire truck. It's probably a very exact simulation of the use of petrol in a fire truck. So you can see that every system can be represented by many different models depending what you're actually interested in.  But if all you're interested is that it roughly looks like a real fire truck and it makes noises that are really annoying and it's red, then that toy is exactly what you want. If you want to build a model and understand how it changes over time, then what you're gonna end up is a simulation. Simulation is basically a model with a time arrow that goes through it. So we use it to model processes. We wouldn't use it to model a fire truck, but we would definitely use it to model how the fire truck behaves on a road, for example. And when do we use it? We use simulation when we're entrusted in a process, but we cannot directly observe. We cannot directly observe it because it's too big or too small, like say, I don't know, changes in galaxies or super tiny things inside an atom. We use it if we cannot observe the process because it is yet to happen. So for example, simulations are used to model how to change your taxes for next year. You know, they don't do it just at random. They actually run a simulation first to check how it's gonna impact on the economy, at least we hope. And Ori, for example, I'm sure this building had a simulation done to see what happens if fire starts. Can people actually escape? So all those things are done because you cannot just do an experiment. And is there something that we would really like to know more about, but we have no access to it? The past, right? I mean, this is like the most obvious example of a system that happened and worked and we're super interested how it worked and we have no way and we'll never be able to understand, you know, just go and observe it. All right, so we have to speed up. Why model in archeology? There are three major reasons why you would like to do it for theory building. It's basically if you're developing your theory instead of writing an essay, you can use a formal method such as simulation to basically see whether what you're proposing will actually have, will produce a data pattern that you see. So for example, if you're interested, okay, let's see, I have my calendar that I study. What if population grow is high? Would I have such an urban sprawl as I see in the data or not? So you can use it to just basically check whether a theory is internally consistent and what would be the data prediction coming out of it? It's perfect for hypothesis testing. You represent, you know, like we have many, many questions where there's quite a few explanations that already sounds pretty plausible. And to choose between one and another, you basically choose on the basis of the color of the eyes of the person that proposed it. It's basically random. One of them is probably right or there's true somewhere in the middle, but there's no way of saying hypothesis testing can be done using simulation because you simulate every single of those hypotheses and then whichever one is the closest to the data, gives the output, the status, the most similar to the data, you give it the first place for now because then people get upset and they change their hypothesis and then you have to do it again. But in the process, you actually get the hypothesis more and more refined and closer to hopefully truth. And then middle range research. Is this idea, you know, like Binford went and looked at hunter-gatherers and then looked at the residuals of their camps and then compared to archeology with the idea that once you have access to a real system that you can observe and the results of their actions, you can compare those results to archeological material and you can conclude that probably if they're similar, the people in the past were engaging in similar behaviors. We'll look at it in a bit more detail here. So when we do data analysis, we have our pods and stone tools and things and we do a description of it. We use typologies, we use statistics, spatial analysis, all sorts of things in order to see the grand population level patterns, the distribution, the change per time, to basically trends in data. When you run a simulation, you build a model where you understand all the interactions and that model has to produce what we call artificial data. And whoever was in the first part of the session, you could see that even 3D models do it. They create this artificial data. In that interfacial data, we'll have the same structure as the real data. So we compare that to and you conclude that the behavior that you modeled plausibly could have produced this type of patterns. So this is the middle range research type that you can engage in using simulation.  We use agent-based modeling. And there will be a lot of presentations about it. Agent-based modeling uses tiny software units, agents, and they can be people, they can be sheep, they can be cars, they can be anything you want. The thing is that they're all heterogeneous. So every single one can be different. They can have different age, different gender, different energy value, different culture, different whatever you want. They interact with each other and they interact with their environment and they make autonomous decisions that are deterministic in a sense of rules of behavior, but they're still autonomous.  So every single one can behave in the way that is best for them at that particular time. And they learn and adapt if you're a good coder. So summary. So issue whatever is actually much more complex and previously believed is the most common conclusion of every archeological research I've ever seen. And this is definitely true. To which Andre Costopoulos says, simulation is our only salvation. There are no other methods that can give you causality of processes in a formal field. Everyone else uses it and it's time that we just get on with it and do the same. So if you're interested, there's some links or come and see me after the presentation. Thank you very much. Thank you.


Okay, folks, Larry Pesavento with the mid-afternoon update for TFNN. As you can see, we've got a very, very strong NASDAQ market, almost at the 61% retracement of the long-term weekly with a big ABCD pattern. We had the Dow Jones up shortly, earlier in the day, it's now down 170, and we've got the S&P up 25 points, and of course, the Russell is still lagging badly. Treasury notes and Treasury bonds are still getting hammered to the downside, and the US dollar is absolutely flying through the air, and the euro is collapsing, much as we had expected this week because of that big 61% retracement that we had in that market the last time that I was on the air, and that was yesterday, and the day before that, the day before that, it hit it six times, or excuse me, four times over the past couple of weeks up there at that 110 level, and now it's approaching, I think it's in the one, almost in the one-sixth range. Yeah, we're almost in the one-sixth range, which will be a very interesting spot to take a look at. We'll cover that when we come up to our show 24-7, Fibonacci 3, what you see will be coming up next. We will enjoy showing you some of the things that are going on in the stock indices because it is really a bifurcated market, as Basil Chapman would say. We got the Nasdaq soaring, and the rest of them are not soaring. The closest to it was the S&P, but the Dow Jones is down, the Russell is down, with a great deal of selling, not just down, but with a great deal of selling. So I think these are things that we have to look at. In fact, we have a new moon coming in here tomorrow. I believe that's what Norm told us. That'll be on the 19th, and so we'll have a really good thing to see volatility come in, because usually when you have markets that are extended like this at full moons and new moons, that's a really good sign. We got one of those coming up in gold and also in the Nasdaq, so we'll have a lot of fun. We'll take a break<PHONE_NUMBER>. We'll be right back.


Hi friends, welcome back to my channel and a very special welcome if you're new here. My name is Jen. I'm a certified weight loss and nutrition coach. I follow weight watchers and I count calories and macros. Happy Monday. It's Monday, so it's meal prep day and I have three amazing recipes for you, including one perfect for your St. Patrick's Day celebration.  Make sure you're subscribed because we do a meal prep every Monday and I upload five videos every single week. Check out the description box down below where you will find nutrition coaching. I do offer personalized two U macros and calories. Highly recommend that is how I lost 90 pounds in the year of 2022 and almost 140 pounds total. I also offer one-on-one coaching for accountability as well. Links and discounts to my favorite things and of course my Facebook group. It is free and we'd love to have you come on over and join us is also down in that description box. All of today's recipes are on my recipe website which I will link at the very top of the description box for you. So let's head on into the kitchen for this week's meal prep. For the week, I'm making strawberry oatmeal cookies. I'm going to pair this with some protein. I am actually having the recipe because I am heading out of town on Thursday and the recipe actually makes 16 cookies. So I'm going to half it to eight. Obviously the point, everything will remain the same but it is five ingredients, super easy, healthy breakfast. So let me show you what's in the recipe. You're going to need some rolled oats. I have Lily's chocolate chips, fresh strawberries, almond butter and a large super duper ripe banana. So to make our cookies, the first thing we're going to do is add a large, like I said, super duper ripe a banana to a bowl and then we're just going to mash that up. Then I'm adding one cup of rolled oats, quarter cup of almond butter and then my chopped up strawberries and we're going to give that a stir until mixed. Then I'm folding in my chocolate chips and remember I have the recipe. I will go ahead and put the full recipe on my website which is the 16 cookies. So my recipe here is going to make eight cookies. Here is what your mixture looks like. Go ahead and preheat your oven to 350 degrees. Pull out a baking sheet and line it with parchment. We want eight cookies total. So I'm going to use just a medium sized cookie scoop. So these strawberry cookies are out of the oven. These smell so good. It gives me kind of a peanut butter and jelly vibe. I'm really excited for these. Like I said, I plan on pairing these with a protein for breakfast. I'm also going to take whatever's left over with me on my trip to San Diego because they don't have to be refrigerated and they would make a great on the go airplane snack. So I'll go ahead and put points, calories, macros here on the screen for you. For lunch this week, I'm making a satay chicken lunch bowl. So basically we're going to make chicken and kind of a slaw to go along with it. So let me show you what's in our recipe. What is not shown is you will need a little bit of water and if you would like, you can add red pepper, chili flakes, I'm omitting that because you know, I don't love spicy. You'll need some powdered peanut butter, ice wine vinegar, sesame oil, Lakonto golden, that's my favorite brown sugar substitute. I will link Lakonto down below with 15% off site wide. You'll need soy sauce, a chopped bell pepper, carrots, cabbage, lime juice, ginger and chicken thighs. So the first thing I need to do is make up the marinade for my chicken satay bowl. So I have a quarter cup of PB2 and then I'm going to add about a tablespoon of water to that and give that a quick mix, basically making my peanut butter. One quarter cup of rice wine vinegar, one and a half tablespoons of soy sauce, two tablespoons of sesame oil, add a teaspoon and a half of lime juice, a couple teaspoons of minced ginger and then a couple teaspoons of Lakonto golden and then give that a stir until you have your marinade mix. So I've added my chicken thighs to a dish here and I'm going to add about half of our marinade right on top. You do want to allow your chicken thighs to marinate in the fridge for about a half of an hour. So I'm actually going to throw these in the fridge and while these are marinating, I will work on my sweet treat for the week. Reserve the other half of your sauce, set that aside.   So I have four storage containers here, starting with some angel hair or shredded cabbage. I'm going to add some of that. I went ahead and grated those carrots. So I'm going to add a few carrots to the top. So those bell peppers were bad. Luckily I have some frozen green bell peppers in my freezer. I'm just going to add a few frozen ones. They will thaw in the refrigerator. And then I'm going to put the leftover marinade in a mason jar and we're going to use that as the dressing for the slaw. So let me go ahead and put together two more storage containers of slaw. So I have my four meal preps ready. I have my extra sauce in a mason jar. Again, that's going to be the marinade. We'll add to both the top of the chicken, but also the slaw. I have my chicken thighs in a 400 degree oven until they're cooked through. You could grill these with this knife if you have nice weather in your area as well. But as soon as the chicken thighs are done, we'll finish putting together our lunch meal prep. I just pulled out the chicken thighs. These look so good. I'm going to go ahead and add them to the meal prep container. And here is the completed meal prep. We'll go ahead and add some of that delicious satay peanut sauce to the top of our slaw and our chicken. But this looks so good. What a low carb, healthy lunch. I'm super excited for this. I'll probably add some fruit to get in some healthy carbs. I'll go ahead and put points, calories, macros here on the screen for you. For a St. Patrick's Day inspired sweet treat, I thought perfect timing for you guys if you wanted to make this. For your St. Patrick's Day celebration, I am making a chocolate mint nanomobile. I don't know if I'm pronouncing that right, but you know what I'm talking about. So let me show you what's in the recipe. First you're going to need powdered sugar. Of course I'm using Lakonto powder.  We have some more Lily's chocolate chips, light butter, milk of your choice. We're only using a couple of tablespoons. I'm using sugar-free jello pudding because the recipe calls for custard powder and I couldn't find that. So I Googled it and it said a substitution is instant pudding. So instant vanilla sugar-free pudding it is. I am using a pre-made graham cracker crust. The original recipe gives you a recipe for a crust. You could do either one, but I'm going to save myself some time and energy and use a pre-done one. You'll need some mint extract and some green food coloring. So the first thing we're going to do is put together the mint layer of our bars. Remember we are using a pre-made crust and then we'll melt the chocolate chips for that chocolate layer. So in a large bowl I'm adding three cups of Lakonto powdered sugar, half of a cup of light butter. In place of that custard powder I'm doing three tablespoons of sugar-free vanilla pudding. Good thing I love protein pudding so I always have these instant pudding mix and sugar-free on hand. And then three tablespoons of the milk of your choice. One teaspoon of mint extract. And then we're going to add some green food coloring. I'm going to add just a little bit, stir this to combine and then you can always add in more green food coloring if you feel like you need it and you can also add in a little bit more milk to get that right consistency. So I went ahead and added our beautiful green, St. Patty's Day mint layer to the pie crust. I'm going to put this in the refrigerator until set because it does have instant pudding. It will set just like you would with regular pudding. I'm going to go ahead and throw my Lily's chocolate chips. I have 250 of these into the microwave to melt them down. Make sure you are stirring them as they're melting so that the chocolate doesn't seize. Once it is set completely, we're going to go ahead and add the chocolate right on top. Oh my gosh, that looks so good. I am going to go ahead and spread that out.  They will continue to set as they stay in the refrigerator. You can also take your spoon and kind of swirl a little bit to get the green mixed with the chocolate, kind of give it that swirled design. It reminds me of a grasshopper bar or a grasshopper cookie. And here are the bars. I have to say these look absolutely incredible. I'm going to go ahead and put it back in the fridge, allow it to finish setting. It makes 16 squares total. I will go ahead and put points, calories, macros here on the screen for 16. I will also on my website list out eight servings. It's not that much different caloric wise or point wise if you want a little bit bigger bar, especially for the St. Patrick's Day holiday. Me for this week's meal prep. I hope you are as excited about these three recipes as I am. Again, be perfect dessert for all of your St. Patrick's Day celebrations. Delicious, low calorie, low point, you can't beat it. Don't forget all of today's recipes are on my website which is linked at the top of the description box along with nutrition coaching, links and discounts to my favorite things and don't forget, come on over during my Facebook group. We'd love to have you. Thank you for watching, happy Monday and I'll see you in the next one. Bye.