Once again, I break my rhythm. Mind you, it happens a lot this year. Since January, it is all about breaking whatever rhythm I have had so far in my life. I am getting used to unusual, and I think it is a good thing. Now, I am breaking the usual rhythm of my blogging. Normally, I have been alternating updates in English with those in French, like one to one, with a pinchful of writing in my mother tongue, Polish, every now and then. Right now, two urgent tasks require my attention: I need to prepare new syllabuses, for English-taught courses in the upcoming academic year, and to revise my draft article on the energy efficiency of national economies.
Before I attend to those tasks, however, a little bit of extended reflection on goals and priorities in my life, somehow in the lines of my last update, « It might be a sign of narcissism ». I have just gotten back from Nice, France, where my son has just started his semester of Erasmus + exchange, with the Sophia Antipolis University. In my youth, I spent a few years in France, I went many times to France since, and man, this time, I just felt the same, very special and very French kind of human energy, which I remember from the 1980ies. Over the last 20 years or so, the French seemed sort of had been sleeping inside their comfort zone but now, I can see people who have just woken up and are wondering what the hell they had wasted so much time on, and they are taking double strides to gather speed in terms of social change. This is the innovative, brilliant, positively cocky France I love. There is sort of a social pattern in France: when the French get vocal, and possibly violent, in the streets, they are up to something as a nation. The French Revolution in 1789 was an expression of popular discontent, yet what followed was not popular satisfaction: it was one-century-long expansion on virtually all plans: political, military, economic, scientific etc. Right now, France is just over the top of the Yellow Vests protest, which one of my French students devoted an essay to (see « Carl Lagerfeld and some guest blogging from Emilien Chalancon, my student »). I wonder who will be the Napoleon Bonaparte of our times.
When entire nations are up to something, it is interesting. Dangerous, too, and yet interesting. Human societies are, as a rule, the most up to something as regards their food and energy base, and so I come to that revision of my article. Here, below, you will find the letter of review I received from the journal “Energy” after I submitted the initial manuscript, referenced as Ms. Ref. No.: EGY-D-19-00258. The link to my manuscript is to find in the first paragraph of this update. For those of you who are making their first steps in science, it can be an illustration of what ‘scientific dialogue’ means. Further below, you will find a first sketch of my revision, accounting for the remarks from reviewers.
Thus, here comes the LETTER OF REVIEW (in italic):
Ms. Ref. No.: EGY-D-19-00258
Title: Apprehending energy efficiency: what is the cognitive value of hypothetical shocks? Energy
Dear Dr. Wasniewski,
The review of your paper is now complete, the Reviewers’ reports are below. As you can see, the Reviewers present important points of criticism and a series of recommendations. We kindly ask you to consider all comments and revise the paper accordingly in order to respond fully and in detail to the Reviewers’ recommendations. If this process is completed thoroughly, the paper will be acceptable for a second review.
If you choose to revise your manuscript it will be due into the Editorial Office by the Jun 23, 2019
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Reviewers’ comments:
Reviewer #1: The paper is, at least according to the title of the paper, and attempt to ‘comprehend energy efficiency’ at a macro-level and perhaps in relation to social structures. This is a potentially a topic of interest to the journal community. However and as presented, the paper is not ready for publication for the following reasons:
1. A long introduction details relationship and ‘depth of emotional entanglement between energy and social structures’ and concomitant stereotypes, the issue addressed by numerous authors. What the Introduction does not show is the summary of the problem which comes out of the review and which is consequently addressed by the paper: this has to be presented in a clear and articulated way and strongly linked with the rest of the paper. In simplest approach, the paper does demonstrate why are stereotypes problematic. In the same context, it appears that proposed methodology heavily relays on MuSIASEM methodology which the journal community is not necessarily familiar with and hence has to be explained, at least to the level used in this paper and to make the paper sufficiently standalone;
2. Assumptions used in formulating the model have to be justified in terms what and how they affect understanding of link/interaction between social structures and function of energy (generation/use) and also why are assumptions formulated in the first place. Also, it is important here to explicitly articulate what is aimed to achieve with the proposed model: as presented this somewhat comes clear only towards the end of the paper. More fundamental question is what is the difference between model presented here and in other publications by the author: these have to be clearly explained.
3. The presented empirical tests and concomitant results are again detached from reality for i) the problem is not explicitly formulated, and ii) real-life interpretation of results are not clear.
On the practical side, the paper needs:
1. To conform to style of writing adopted by the journal, including referencing;
2. All figures have to have captions and to be referred to by it;
3. English needs improvement.
Reviewer #2: Please find the attached file.
Reviewer #3: The article has a cognitive value. The author has made a deep analysis of literature. Methodologically, the article does not raise any objections. However, getting acquainted with its content, I wonder why the analysis does not take into account changes in legal provisions. In the countries of the European Union, energy efficiency is one of the pillars of shaping energy policy. Does this variable have no impact on improving energy efficiency?
When reading an article, one gets the impression that the author has prepared it for editing in another journal. Editing it is incorrect! Line 13, page 10, error – unwanted semicolon.
Now, A FIRST SKETCH OF MY REVISION.
There are the general, structural suggestions from the editors, notably to outline my method of research, and to discuss my data, in separate papers. After that come the critical remarks properly spoken, with a focus on explaining clearly – more clearly than I did it in the manuscript – the assumptions of my model, as well as its connections with the MUSIASEM model. I start with my method, and it is an interesting exercise in introspection. I did the empirical research quite a few months ago, and now I need to look at it from a distance, objectively. Doing well at this exercise amounts, by the way, to phrasing accurately my assumptions. I start with my fundamental variable, i.e. the so-called energy efficiency, measured as the value of real output (i.e. the value of goods and services produced) per unit of energy consumed, measured in kilograms of oil equivalent. It is like: energy efficiency = GDP/ energy consumed.
In my mind, that coefficient is actually a coefficient of coefficients, more specifically: GDP / energy consumed = [GDP per capita] / [consumption of energy per capita ] = [GDP / population] / [energy consumed / population ]. Why so? Well, I assume that when any of us, humans, wants to have a meal, we generally don’t put our fingers in the nearest electric socket. We consume energy indirectly, via the local combination of technologies. The same local combination of technologies makes our GDP. Energy efficiency measures two ends of the same technological toolbox: its intake of energy, and its outcomes in terms of goods and services. Changes over time in energy efficiency, as well as its disparity across space depend on the unfolding of two distinct phenomena: the exact composition of that local basket of technologies, like the overall heap of technologies we have stacked up in our daily life, for one, and the efficiency of individual technologies in the stack, for two. Here, I remember a model I got to know in management science, precisely about how the efficiency changes with new technologies supplanting the older ones. Apparently, a freshly implemented, new technology is always less productive than the one it is kicking out of business. Only after some time, when people learn how to use that new thing properly, it starts yielding net gains in productivity. At the end of the day, when we change our technologies frequently, there could very well not be any gain in productivity at all, as we are constantly going through consecutive phases of learning. Anyway, I see the coefficient of energy efficiency at any given time in a given place as the cumulative outcome of past collective decisions as for the repertoire of technologies we use.
That is the first big assumption I make, and the second one comes from the factorisation: GDP / energy consumed = [GDP per capita] / [consumption of energy per capita ] = [GDP / population] / [energy consumed / population ]. I noticed a semi-intuitive, although not really robust correlation between the two component coefficients. GDP per capita tends to be higher in countries with better developed institutions, which, in turn, tend to be better developed in the presence of relatively high a consumption of energy per capita. Mind you, it is quite visible cross-sectionally, when comparing countries, whilst not happening that obviously over time. If people in country A consume twice as much energy per capita as people in country B, those in A are very likely to have better developed institutions than folks in B. Still, if in any of the two places the consumption of energy per capita grows or falls by 10%, it does not automatically mean corresponding an increase or decrease in institutional development.
Wrapping partially up the above, I can see at least one main assumption in my method: energy efficiency, measured as GDP per kg of oil equivalent in energy consumed is, in itself, a pretty foggy metric, arguably devoid of intrinsic meaning, and it is meaningful as an equilibrium of two component coefficients, namely in GDP per capita, for one, and energy consumption per capita, for two. Therefore, the very name ‘energy efficiency’ is problematic. If the vector [GDP; energy consumption] is really a local equilibrium, as I intuitively see it, then we need to keep in mind an old assumption of economic sciences: all equilibriums are efficient, this is basically why they are equilibriums. Further down this avenue of thinking, the coefficient of GDP per kg of oil equivalent shouldn’t even be called ‘energy efficiency’, or, just in order not to fall into pointless semantic bickering, we should take the ‘efficiency’ part into some sort of intellectual parentheses.
Now, I move to my analytical method. I accept as pretty obvious the fact that, at a given moment in time, different national economies display different coefficients of GDP per kg of oil equivalent consumed. This is coherent with the above-phrased claim that energy efficiency is a local equilibrium rather than a measure of efficiency strictly speaking. What gains in importance, with that intellectual stance, is the study of change over time. In the manuscript paper, I tested a very intuitive analytical method, based on a classical move, namely on using natural logarithms of empirical values rather than empirical values themselves. Natural logarithms eliminate a lot of non-stationarity and noise in empirical data. A short reminder of what are natural logarithms is due at this point. Any number can be represented as a power of another number, like y = xz, where ‘x’ is called the root of the ‘y’, ‘z’ is the exponent of the root, and ‘x’ is also the base of ‘z’.
Some roots are special. One of them is the so-called Euler’s number, or e = 2,718281828459, the base of the natural logarithm. When we treat e ≈ 2,72 as the root of another number, the corresponding exponent z in y = ez has interesting properties: it can be further decomposed as z = t*a, where t is the ordinal number of a moment in time, and a is basically a parameter. In a moment, I will explain why I said ‘basically’. The function y = t*a is called ‘exponential function’ and proves useful in studying processes marked by important hysteresis, i.e. when each consecutive step in the process depends very strongly on the cumulative outcome of previous steps, like y(t) depends on y(t – k). Compound interest is a classic example: when you save money for years, with annual compounding of interest, each consecutive year builds upon the interest accumulated in preceding years. If we represent the interest rate, classically, as ‘r’, the function y = xt*r gives a good approximation of how much you can save, with annually compounded ‘r’, over ‘t’ years.
Slightly different an approach to the exponential function can be formulated, and this is what I did in the manuscript paper I am revising now, in front of your very eyes. The natural logarithm of energy efficiency measured as GDP per kg of oil equivalent can be considered as local occurrence of change with strong a component of hysteresis. The equilibrium of today depends on the cumulative outcomes of past equilibriums. In a classic exponential function, I would approach that hysteresis as y(t) = et*a, with a being a constant parameter of the function. Yet, I can assume that ‘a’ is local instead of being general. In other words, what I did was y(t) = et*a(t) with a(t) being obviously t-specific, i.e. local. I assume that the process of change in energy efficiency is characterized by local magnitudes of change, the a(t)’s. That a(t), in y(t) = et*a(t) is slightly akin to the local first derivative, i.e. y’(t). The difference between the local a(t) and y’(t) is that the former is supposed to capture somehow more accurately the hysteretic side of the process under scrutiny.
In typical econometric tests, the usual strategy is to start with the empirical values of my variables, transform them into their natural logarithms or some sort of standardized values (e.g. standardized over their respective means, or their standard deviations), and then run linear regression on those transformed values. Another path of analysis consists in exponential regression, only there is a problem with this one: it is hard to establish a reliable method of transformation in empirical data. Running exponential regression on natural logarithms looks stupid, as natural logarithms are precisely the exponents of the exponential function, whence my intuitive willingness to invent a method sort of in between linear regression, and the exponential one.
Once I assume that local exponential coefficients a(t) in the exponential progression y(t) = et*a(t) have intrinsic meaning of their own, as local magnitudes of exponential change, an interesting analytical avenue opens up. For each set of empirical values y(t), I can construe a set of transformed values a(t) = ln[y(t)]/t. Now, when you think about it, the actual a(t) depends on how you calculate ‘t’, or, in other words, what calendar you apply. When I start counting time 100 years before the starting year of my empirical data, my a(t) will go like: a(t1) = ln[y(t1)]/101, a(t2) = ln[y(t2)]/102 etc. The denominator ‘t’ will change incrementally slowly. On the other hand, if I assume that the first year of whatever is happening is one year before my empirical time series start, it is a different ball game. My a(t1) = ln[y(t1)]/1, and my a(t2) = ln[y(t2)]/2 etc.; incremental change in denominator is much greater in this case. When I set my t0 at 100 years earlier than the first year of my actual data, thus t0 = t1 – 100, the resulting set of a(t) values transformed from the initial y(t) data simulates a secular, slow trend of change. On the other hand, setting t0 at t0 = t1-1 makes the resulting set of a(t) values reflect quick change, and the t0 = t1 – 1 moment is like a hypothetical shock, occurring just before the actual empirical data starts to tell its story.
Provisionally wrapping it up, my assumptions, and thus my method, consists in studying changes in energy efficiency as a sequence of equilibriums between relative wealth (GDP per capita), on the one hand, and consumption of energy per capita. The passage between equilibriums is a complex phenomenon, combining long term trends and the short-term ones.
I am introducing a novel angle of approach to the otherwise classic concept of economics, namely that of economic equilibrium. I claim that equilibriums are manifestations of collective intelligence in their host societies. In order to form an economic equilibrium, would it be more local and Marshallian, or more general and Walrasian, a society needs institutions that assure collective learning through experimentation. They need some kind of financial market, enforceable contracts, and institutions of collective bargaining. Small changes in energy efficiency come out of consistent, collective learning through those institutions. Big leaps in energy efficiency appear when the institutions of collective learning undergo substantial structural changes.
I am thinking about enriching the empirical part of my paper by introducing additional demonstration of collective intelligence: a neural network, working with the same empirical data, with or without the so-called fitness function. I have that intuitive thought – although I don’t know yet how to get it across coherently – that neural networks endowed with a fitness function are good at representing collective intelligence in structured societies with relatively well-developed institutions.
I go towards my syllabuses for the coming academic year. Incidentally, at least one of the curriculums I am going to teach this fall fits nicely into the line of research I am pursuing now: collective intelligence and the use of artificial intelligence. I am developing the thing as an update on my blog, and I write it directly in English. The course is labelled “Behavioural Modelling and Content Marketing”. My principal goal is to teach students the mechanics of behavioural interaction between human beings and digital technologies, especially in social media, online marketing and content streaming. At my university, i.e. the Andrzej Frycz-Modrzewski Krakow University (Krakow, Poland), we have a general drill of splitting the general goal of each course into three layers of expected didactic outcomes: knowledge, course-specific skills, and general social skills. The longer I do science and the longer I teach, the less I believe into the point of distinguishing knowledge from skills. Knowledge devoid of any skills attached to it is virtually impossible to check, and virtually useless.
As I think about it, I imagine many different teachers and many students. Each teacher follows some didactic goals. How do they match each other? They are bound to. I mean, the community of teachers, in a university, is a local social structure. We, teachers, we have different angles of approach to teaching, and, of course, we teach different subjects. Yet, we all come from more or less the same cultural background. Here comes a quick glimpse of literature I will be referring to when lecturing ‘Behavioural Modelling and Content Marketing’: the article by Molleman and Gachter (2018[1]), entitled ‘Societal background influences social learning in cooperative decision making’, and another one, by Smaldino (2019[2]), under the title ‘Social identity and cooperation in cultural evolution’. Molleman and Gachter start from the well-known assumption that we, humans, largely owe our evolutionary success to our capacity of social learning and cooperation. They give the account of an experiment, where Chinese people, assumed to be collectivist in their ways, are being compared to British people, allegedly individualist as hell, in a social game based on dilemma and cooperation. Turns out the cultural background matters: success-based learning is associated with selfish behaviour and majority-based learning can help foster cooperation. Smaldino goes down more theoretical a path, arguing that the structure society shapes the repertoire of social identities available to homo sapiens in a given place at a given moment, whence the puzzle of emergent, ephemeral groups as a major factor in human cultural evolution. When I decide to form, on Facebook, a group of people Not-Yet-Abducted-By-Aliens, is it a factor of cultural change, or rather an outcome thereof?
When I teach anything, what do I really want to achieve, and what does the conscious formulation of those goals have in common with the real outcomes I reach? When I use a scientific repository, like ScienceDirect, that thing learns from me. When I download a bunch of articles on energy, it suggests me further readings along the same lines. It learns from keywords I use in my searches, and from the journals I browse. You can even have a look at my recent history of downloads from ScienceDirect and make yourself an opinion about what I am interested in. Just CLICK HERE, it opens an Excel spreadsheet.
How can I know I taught anybody anything useful? If a student asks me: ‘Pardon me, sir, but why the hell should I learn all that stuff you teach? What’s the point? Why should I bother?’. Right you are, sir or miss, whatever gender you think you are. The point of learning that stuff… You can think of some impressive human creation, like the Notre Dame cathedral, the Eiffel Tower, or that Da Vinci’s painting, Lady with an Ermine. Have you ever wondered how much work had been put in those things? However big and impressive a cathedral is, it had been built brick by f***ing brick. Whatever depth of colour we can see in a painting, it came out of dozens of hours spent on sketching, mixing paints, trying, cursing, and tearing down the canvas. This course and its contents are a small brick in the edifice of your existence. One more small story that makes your individual depth as a person.
There is that thing, at the very heart of behavioural modelling, and social sciences in general. Fault of a better expression, I call it the Bignetti model. See, for example, Bignetti 2014[3], Bignetti et al. 2017[4], or Bignetti 2018[5] for more reading. Long story short, what professor Bignetti claims is that whatever happens in observable human behaviour, individual or collective, whatever, has already happened neurologically beforehand. Whatever we use to Tweet or whatever we read, it is rooted in that wiring we have between the ears. The thing is that actually observing how that wiring works is still a bit burdensome. You need a lot of technology, and a controlled environment. Strangely enough, opening one’s skull and trying to observe the contents at work doesn’t really work. Reverse-engineered, the Bignetti model suggests behavioural observation, and behavioural modelling, could be a good method to guess how our individual brains work together, i.e. how we are intelligent collectively.
I go back to the formal structure of the course, more specifically to goals and expected outcomes. I split: knowledge, skills, social competences. The knowledge, for one. I expect the students to develop the understanding of the following concepts: a) behavioural pattern b) social life as a collection of behavioural patterns observable in human beings c) behavioural patterns occurring as interactions of humans with digital technologies, especially with online content and online marketing d) modification of human behaviour as a response to online content e) the basics of artificial intelligence, like the weak law of great numbers or the logical structure of a neural network. As for the course-specific skills, I expect my students to sharpen their edge in observing behavioural patterns, and changes thereof in connection with online content. When it comes to general social competences, I would like my students to make a few steps forward on two paths: a) handling projects and b) doing research. It logically implies that assessment in this course should and will be project-based. Students will be graded on the grounds of complex projects, covering the definition, observation, and modification of their own behavioural patterns occurring as interaction with online content.
The structure of an individual project will cover three main parts: a) description of the behavioural sequence in question b) description of online content that allegedly impacts that sequence, and c) the study of behavioural changes occurring under the influence of online content. The scale of students’ grades is based on two component marks: the completeness of a student’s work, regarding (a) – (c), and the depth of research the given student has brought up to support his observations and claims. In Poland, in the academia, we typically use a grading scale from 2 (fail) all the way up to 5 (very good), passing through 3, 3+, 4, and 4+. As I see it, each student – or each team of students, as there will be a possibility to prepare the thing in a team of up to 5 people – will receive two component grades, like e.g. 3+ for completeness and 4 for depth of research, and that will give (3,5 + 4)/2 = 3,75 ≈ 4,0.
Such a project is typical research, whence the necessity to introduce students into the basic techniques of science. That comes as a bit of a paradox, as those students’ major is Film and Television Production, thus a thoroughly practical one. Still, science serves in practical issues: this is something I deeply believe and which I would like to teach my students. As I look upon those goals, and the method of assessment, a structure emerges as regards the plan of in-class teaching. At my university, the bulk of in-class interaction with students is normally spread over 15 lectures of 1,5 clock hour each, thus 30 hours in total. In some curriculums it is accompanied by the so-called ‘workshops’ in smaller groups, with each such smaller group attending 7 – 8 sessions of 1,5 hour each. In this case, i.e. in the course of ‘Behavioural Modelling and Content Marketing’, I have just lectures in my schedule. Still, as I see it, I will need to do practical stuff with my youngsters. This is a good moment to demonstrate a managerial technique I teach in other classes, called ‘regressive planning’, which consists in taking the final goal I want to achieve, assume this is supposed to be the outcome of a sequence of actions, and then reverse engineer that sequence. Sort of ‘what do I need to do if I want to achieve X at the end of the day?’.
If I want to have my students hand me good quality projects by the end of the semester, the last few classes out of the standard 15 should be devoted to discussing collectively the draft projects. Those drafts should be based on prior teaching of basic skills and knowledge, whence the necessity to give those students a toolbox, and provoke in them curiosity to rummage inside. All in all, it gives me the following, provisional structure of lecturing:
{input = 15 classes} => {output = good quality projects by my students}
{input = 15 classes} ó {input = [10 classes of preparation >> 5 classes of draft presentations and discussion thereof]}
{input = 15 classes} ó {input = [5*(1 class of mindfuck to provoke curiosity + 1 class of systematic presentation) + 5*(presentation + questioning and discussion)}
As I see from what I have just written, I need to divide the theory accompanying this curriculum into 5 big chunks. The first of those 5 blocks needs to address the general frame of the course, i.e. the phenomenon of recurrent interaction between humans and online content. I think the most important fact to highlight is that algorithms of online marketing behave like sales people crossed with very attentive servants, who try to guess one’s whims and wants. It is a huge social change: it, I think, the first time in human history when virtually every human with access to Internet interacts with a form of intelligence that behaves like a butler, guessing the user’s preferences. It is transformational for human behaviour, and in that first block I want to show my students how that transformation can work. The opening, mindfucking class will consists in a behavioural experiment in the lines of good, old role playing in psychology. I will demonstrate to my students how a human would behave if they wanted to emulate the behaviour of neural networks in online marketing. I will ask them questions about what they usually do, and about what they did like during the last few days, and I will guess their preferences on the grounds of their described behaviour. I will tell my students to observe that butler-like behaviour of mine and to pattern me. In a next step, I will ask students to play the same role, just for them to get the hang of how a piece of AI works in online marketing. The point of this first class is to define an expected outcome, like a variable, which neural networks attempt to achieve, in terms of human behaviour observable through clicking. The second, theoretical class of that first block will, logically, consist in explaining the fundamentals of how neural networks work, especially in online interactions with human users of online content.
I think in the second two-class block I will address the issue of behavioural patterns as such, i.e. what they are, and how can we observe them. I want the mindfuck class in this block to be provocative intellectually, and I think I will use role playing once again. I will ask my students to play roles of their choice, and I will discuss their performance under a specific angle: how do you know that your play is representative for this type of behaviour or person? What specific pieces of behaviour are, in your opinion, informative about the social identity of that role? Do other students agree that the type of behaviour played is representative for this specific type of person? The theoretical class in this block will be devoted to systematic lecture on the basics of behaviourism. I guess I will serve to my students some Skinner, and some Timberlake, namely Skinner’s ‘Selection by Consequences’ (1981[6]), and Timberlake’s ‘Behaviour Systems and Reinforcement’ (1993[7]).
In the third two-class block I will return to interactions with online content. In the mindfuck class, I will make my students meddle with You Tube, and see how the list of suggested videos changes after we search for or click on specific content, e.g how will it change after clicking 5 videos of documentaries about wildlife, or after searching for videos on race cars. In this class, I want my students to pattern the behaviour of You Tube. The theoretical class of this block will be devoted to the ways those algorithms work. I think I will focus on a hardcore concept of AI, namely the Gaussian mixture. I will explain how crude observations on our clicking and viewing allows an algorithm to categorize us.
As we will pass to the fourth two-class block, I will switch to the concept of collective intelligence, i.e. to how whole societies interact with various forms of online, interactive neural networks. The class devoted to intellectual provocation will be discursive. I will make students debate on the following claim: ‘Internet and online content allow our society to learn faster and more efficiently’. There is, of course, a catch, and it is the definition of learning fast and efficiently. How do we know we are quick and efficient in our collective learning? What would slow and inefficient learning look like? How can we check the role of Internet and online content in our collective learning? Can we apply the John Stuart Mill’s logical canon to that situation? The theoretical class in this block will be devoted to the phenomenon of collective intelligence in itself. I would like to work through like two research papers devoted to online marketing, e.g. Fink et al. (2018[8]) and Takeuchi et al. (2018[9]), in order to show how online marketing unfolds into phenomena of collective intelligence and collective learning.
Good, so I come to the fifth two-class block, the last one before the scheduled draft presentations by my students. It is the last teaching block before they present their projects, and I think it should bring them back to the root idea of these, i.e. to the idea of observing one’s own behaviour when interacting with online content. The first class of the block, the one supposed to stir curiosity, could consist in two steps of brain storming and discussion. Students endorse the role of online marketers. In the first step, they define one or two typical interactions between human behaviour, and the online content they communicate. We use the previously learnt theory to make both the description of behavioural patterns, and that of online marketing coherent and state-of-the-art. In the next step, students discuss under what conditions they would behave according to those pre-defined patterns, and what conditions would them make diverge from it and follow different patterns. In the theoretical class of this block, I would like to discuss two articles, which incite my own curiosity: ‘A place for emotions in behaviour research system’ by Gordon M.Burghart (2019[10]), and ‘Disequilibrium in behaviour analysis: A disequilibrium theory redux’ by Jacobs et al. (2019[11]).
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[1] Molleman, L., & Gächter, S. (2018). Societal background influences social learning in cooperative decision making. Evolution and Human Behavior, 39(5), 547-555.
[2] Smaldino, P. E. (2019). Social identity and cooperation in cultural evolution. Behavioural Processes. Volume 161, April 2019, Pages 108-116
[3] Bignetti, E. (2014). The functional role of free-will illusion in cognition:“The Bignetti Model”. Cognitive Systems Research, 31, 45-60.
[4] Bignetti, E., Martuzzi, F., & Tartabini, A. (2017). A Psychophysical Approach to Test:“The Bignetti Model”. Psychol Cogn Sci Open J, 3(1), 24-35.
[5] Bignetti, E. (2018). New Insights into “The Bignetti Model” from Classic and Quantum Mechanics Perspectives. Perspective, 4(1), 24.
[6] Skinner, B. F. (1981). Selection by consequences. Science, 213(4507), 501-504.
[7] Timberlake, W. (1993). Behavior systems and reinforcement: An integrative approach. Journal of the Experimental Analysis of Behavior, 60(1), 105-128.
[8] Fink, M., Koller, M., Gartner, J., Floh, A., & Harms, R. (2018). Effective entrepreneurial marketing on Facebook–A longitudinal study. Journal of business research.
[9] Takeuchi, H., Masuda, S., Miyamoto, K., & Akihara, S. (2018). Obtaining Exhaustive Answer Set for Q&A-based Inquiry System using Customer Behavior and Service Function Modeling. Procedia Computer Science, 126, 986-995.
[10] Burghardt, G. M. (2019). A place for emotions in behavior systems research. Behavioural processes.
[11] Jacobs, K. W., Morford, Z. H., & King, J. E. (2019). Disequilibrium in behavior analysis: A disequilibrium theory redux. Behavioural processes.